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An Introduction to Data Collection within Marketing Research.

Data plays a central role in all forms of research, including marketing research. It serves as the eyes and ears for a brand’s marketing initiatives. The data you gather — and its quality — will make a massive difference to how successful your research is, how accurate your findings are, and the impact on your business goals and strategies.

Data collection is arguably the most critical market research stage. It can make or break the rest of the process, so it’s vital to do everything you can to make this stage run smoothly and successfully.

In this article, we’ll take a deep dive into why data collection matters, the different types of data you should focus on, and all the options available to you when it comes to collecting that data. Let’s start by defining what data collection means.

What is the definition of data collection in the context of market research?

Data collection encompasses the meticulous compilation of all essential raw information required for your market research. Some individuals also broaden the scope of this definition to encompass the analysis of the gathered data, extracting invaluable insights to fulfill your research objectives.

It entails a comprehensive and well-planned quest for relevant data conducted by a researcher to validate a hypothesis.

The primary objective of data collection in market research is to ensure the acquisition of dependable data for statistical analysis, thereby enabling brands to make informed decisions supported by robust data. Consequently, it is imperative that your data possesses attributes of high quality, relevance, and sufficient quantity to yield meaningful insights.

Why data collection is so important?

Data collection is a critical step in the research process, often the primary step. You can analyze and store essential information about your existing and potential customers when you collect data. This process saves your organization money and resources, as you can make data-driven decisions. Data collection also allows you to create a library or database of customers (and their information) for marketing to them in the future or retargeting them.

Three main uses of data collection in market research:

• Data collection helps you make informed decisions and analyses, building complete and insightful market research reports that can drive future product launches, market-entry campaigns, marketing strategies, and more. Data collection is the foundational step for various activities that can lead to business growth.
• Data collection allows you to build a database of information about your market for future use. While your primary goal might be to create a research report with a specific objective, the data can still be helpful for future activities.
• Data collection allows you to target marketing and outreach more efficiently, thereby allowing your organization to save money and do more with its resources.

The different types of data collection in marketing research

There are several different types of data to consider at this stage — let’s examine them more closely.

We can break down data into two main categories, which makes it easier to understand the types of data we want to focus on and helps us hone in on the research methods and channels that will be most useful.

Primary data

Primary data is collected directly by your researchers, specifically for your research purposes. This data is primarily collected from interviews, surveys, focus groups, and experiments. In other words, this data did not exist before your team collected it.

Secondary data

Secondary data refers to data that already existed before you started your research. Other researchers have already collected and compiled this data before. You can find this type of data in places like government reports, the analysis of other businesses, polls and surveys, and the work of NGOs. It’s typically cheaper and easier to obtain than your primary data, but it won’t be as relevant to your project.

Qualitative research

Qualitative research is usually the first step in data collection. It’s more textual than statistical and involves collecting non-numerical data like interview transcripts, video recordings, and survey responses.

Qualitative data is typically collected via first-hand observation through focus groups, interviews, and ethnography. It is a way of diving deep into ideas and concepts, allowing researchers to learn more about specific topics that may not be well understood.

Quantitative Research

Where qualitative research is relatively more text-based, quantitative research focuses on numbers and statistics. This data is expressed in charts, graphs, and tables and is typically used to test initial findings.

Methods used to collect quantitative data include more closed-ended survey questions, mobile surveys, and Likert scales. The main benefit of this type of data is that it allows researchers to make more broad generalizations and predictions, but it’s not well-suited for diving deep into particular questions.

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How data collection in marketing research works

There are many steps involved in the data collection process. Some of these steps begin even before you start collecting data.

Prior steps

There are several steps you should take before your data collection begins, such as:

・ Make sure you have all the necessary permission to collect your data. Today, data privacy laws are stronger than ever, so researchers need to take extra care to comply with regulations and have the full consent of their subjects and participants. It’s best to work with a legal compliance team to draft all the required documents, forms, and contracts to share with your research participants from the very beginning.

・ Make sure you have the support of any company decision-makers and stakeholders. It may be helpful at this stage to prepare a preliminary report informing any higher-ups of your plans, goals, sources , and any methods you plan to use.

・ Try to predict and pre-empt any possible challenges or problems, such as privacy regulations, collection methods, infrastructure, or budget. Anticipating any issues now will help you avoid costly problems and make the whole process run more smoothly.

・ Put together a team of skilled and qualified researchers and analysts. Data collection can be a difficult task, and you need to have the right experience and skillsets on your team.

Decide on your data collection methods.

The next stage is to decide which data collection methods you will use to collect data for your marketing research report. You will likely employ various methods here, as each has unique pros and cons. Here are the main methods you should consider:

There are many ways to conduct surveys — in-person, online, post, email, mobile message, others. Surveys differ in content and structure — from simple Likert scales with just five possible numerical responses to more qualitative open-ended questions.

・ Focus groups

Focus groups allow you to bring multiple participants together to discuss the subject of your research and share their opinions. This format can be a great way to brainstorm ideas, and people can often bring good ideas out of each other. To get the best results, everyone should get a chance to speak, and no one person should dominate the group.

・ Interviews

One-to-one interviews are the best ways to dive deep into a person’s opinions about your brand or a specific product. However, they can be time-consuming and may require much planning.

・Observation and experimental research

This type of data collection involves observing individuals as they interact with specific products or services. It helps get around certain biases that people might have in interviews and surveys and cut right through to their true thoughts. However, it isn’t easy and requires an expert touch to get it right.

Identify and prepare for common challenges with data collection.

During the data collection process, you’re likely to encounter several challenges. The good news is that you can avoid these challenges and mitigate any impacts on your research report with proper preparation.

Here’s what to look out for:

・bad methodology results in poor quality data.

A lot can go wrong with your data collection methods — badly identified participants, poorly designed questions, and choosing the wrong methods are just a few examples. This can result in poor quality data, leading to erroneous conclusions and an unsuccessful research report. Take the time to work with experienced researchers and build the right data collection strategy for your needs.

・Logistical challenges

You will also come across many logistical challenges. For instance, you’ll need a big venue to hold everyone if you’re running a focus group. If you want to conduct a stream of interviews, you’ll need to hire a space for a particular time. You may need to arrange transport, refreshments, and a wide range of other logistical demands. If you fail to plan this properly in advance, your team could find itself in a highly stressful situation.

・Using the proper channels

The channels you use to connect with your audience are consequential — what works well for one demographic might completely fail for another. If you choose the wrong media (like Twitter to send surveys to an older demographic), you could have a poor response rate and lack usable data.

How to collect data effectively

Get to know your audience..

You will need to have an intimate and deep understanding of your audience and the people you collect data from. This will ensure you target the right people, ask the appropriate questions, choose the correct methods and channels, and analyze the data in the proper contexts.

There are many ways to get to know your audience better in advance of data collection:

・ Use social media to spend time in the same spaces and groups as your audience members, chat with them, and find out who they are and what makes them tick.

・ Work with your sales and marketing teams — it’s their job to understand your audience, and they’ll have access to valuable insights.

・ Look at who is using your competitors’ brands and products.

Once you understand whom you target, it often helps create detailed user personas, outlining details about your typical audience members like their age groups, income brackets, and education levels. You can then use this information to tailor your data collection strategy to be relevant and valuable.

Prepare for the analysis of your data.

Collecting data is one thing, but you should always have an eye on the analysis of that data. This is where you extract insights and draw tangible value from the data — allowing you to make informed business decisions and create a valuable and applicable market research report .

When planning your collection methods and recording the results, always remember that someone will be analyzing this data. Be organized, clear, and detailed, and work with your analysts to ensure they are aligned with your approach.

Use a wide range of methods and channels.

The best data collection relies on various tools and channels instead of focusing on just one or two. By combining a number of the approaches mentioned in this article, you will connect with a broader part of your market, gaining a better understanding of how different demographics feel and leading to a more valuable and insightful analysis.

For example, if you focus solely on digital channels like social media and online surveys, your responses may skew heavily towards younger people. Some in-person interviews, focus groups, and postal surveys help target a broader range of age groups and accurately reflect your market and their views.

Data collection is a critical part of market research. It serves many important purposes, and it is essential to get it right to create effective research reports and complete a vast range of different business objectives.

At Kadence, we help companies worldwide fine-tune their data collection, laying the foundations for informed and effective market research.

Contact us to learn more about how we can help you do the same.

Helping brands uncover valuable insights

We’ve been working with Kadence on a couple of strategic projects, which influenced our product roadmap roll-out within the region. Their work has been exceptional in providing me the insights that I need. Senior Marketing Executive Arla Foods

Kadence’s reports give us the insight, conclusion and recommended execution needed to give us a different perspective, which provided us with an opportunity to relook at our go to market strategy in a different direction which we are now reaping the benefits from. Sales & Marketing Bridgestone

Kadence helped us not only conduct a thorough and insightful piece of research, its interpretation of the data provided many useful and unexpected good-news stories that we were able to use in our communications and interactions with government bodies. General Manager PR -Internal Communications & Government Affairs Mitsubishi

Kadence team is more like a partner to us. We have run a number of projects together and … the pro-activeness, out of the box thinking and delivering in spite of tight deadlines are some of the key reasons we always reach out to them. Vital Strategies

Kadence were an excellent partner on this project; they took time to really understand our business challenges, and developed a research approach that would tackle the exam question from all directions.  The impact of the work is still being felt now, several years later. Customer Intelligence Director Wall Street Journal

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Privacy Overview

What is Data Collection? Methods, Types, Tools, Examples

Appinio Research · 09.11.2023 · 33min read

Are you ready to unlock the power of data? In today's data-driven world, understanding the art and science of data collection is the key to informed decision-making and achieving your objectives.

This guide will walk you through the intricate data collection process, from its fundamental principles to advanced strategies and ethical considerations. Whether you're a business professional, researcher, or simply curious about the world of data, this guide will equip you with the knowledge and tools needed to harness the potential of data collection effectively.

What is Data Collection?

Data collection is the systematic process of gathering and recording information or data from various sources for analysis, interpretation, and decision-making. It is a fundamental step in research, business operations, and virtually every field where information is used to understand, improve, or make informed choices.

Key Elements of Data Collection

• Sources: Data can be collected from a wide range of sources, including surveys , interviews, observations, sensors, databases, social media, and more.
• Methods: Various methods are employed to collect data, such as questionnaires, data entry, web scraping, and sensor networks. The choice of method depends on the type of data, research objectives, and available resources.
• Data Types: Data can be qualitative (descriptive) or quantitative (numerical), structured (organized into a predefined format) or unstructured (free-form text or media), and primary (collected directly) or secondary (obtained from existing sources).
• Data Collection Tools: Technology plays a significant role in modern data collection, with software applications, mobile apps, sensors, and data collection platforms facilitating efficient and accurate data capture.
• Ethical Considerations: Ethical guidelines, including informed consent and privacy protection, must be followed to ensure that data collection respects the rights and well-being of individuals.
• Data Quality: The accuracy, completeness, and reliability of collected data are critical to its usefulness. Data quality assurance measures are implemented to minimize errors and biases.
• Data Storage: Collected data needs to be securely stored and managed to prevent loss, unauthorized access, and breaches. Data storage solutions range from on-premises servers to cloud-based platforms.

Importance of Data Collection in Modern Businesses

Data collection is of paramount importance in modern businesses for several compelling reasons:

• Informed Decision-Making: Collected data serves as the foundation for informed decision-making at all levels of an organization. It provides valuable insights into customer behavior, market trends, operational efficiency, and more.
• Competitive Advantage: Businesses that effectively collect and analyze data gain a competitive edge. Data-driven insights help identify opportunities, optimize processes, and stay ahead of competitors .
• Customer Understanding: Data collection allows businesses to better understand their customers, their preferences, and their pain points. This insight is invaluable for tailoring products, services, and marketing strategies.
• Performance Measurement: Data collection enables organizations to assess the performance of various aspects of their operations, from marketing campaigns to production processes. This helps identify areas for improvement.
• Risk Management: Businesses can use data to identify potential risks and develop strategies to mitigate them. This includes financial risks, supply chain disruptions, and cybersecurity threats.
• Innovation: Data collection supports innovation by providing insights into emerging trends and customer demands. Businesses can use this information to develop new products or services.
• Resource Allocation: Data-driven decision-making helps allocate resources efficiently. For example, marketing budgets can be optimized based on the performance of different channels.

Goals and Objectives of Data Collection

The goals and objectives of data collection depend on the specific context and the needs of the organization or research project. However, there are some common overarching objectives:

• Information Gathering: The primary goal is to gather accurate, relevant, and reliable information that addresses specific questions or objectives.
• Analysis and Insight: Collected data is meant to be analyzed to uncover patterns, trends, relationships, and insights that can inform decision-making and strategy development.
• Measurement and Evaluation: Data collection allows for the measurement and evaluation of various factors, such as performance, customer satisfaction , or market potential.
• Problem Solving: Data collection can be directed toward solving specific problems or challenges faced by an organization, such as identifying the root causes of quality issues.
• Monitoring and Surveillance: In some cases, data collection serves as a continuous monitoring or surveillance function, allowing organizations to track ongoing processes or conditions.
• Benchmarking: Data collection can be used for benchmarking against industry standards or competitors, helping organizations assess their performance relative to others.
• Planning and Strategy: Data collected over time can support long-term planning and strategy development, ensuring that organizations adapt to changing circumstances.

In summary, data collection is a foundational activity with diverse applications across industries and sectors. Its objectives range from understanding customers and making informed decisions to improving processes, managing risks, and driving innovation. The quality and relevance of collected data are pivotal in achieving these goals.

How to Plan Your Data Collection Strategy?

Before kicking things off, we'll review the crucial steps of planning your data collection strategy. Your success in data collection largely depends on how well you define your objectives, select suitable sources, set clear goals, and choose appropriate collection methods.

Defining Your Research Questions

Defining your research questions is the foundation of any effective data collection effort. The more precise and relevant your questions, the more valuable the data you collect.

• Specificity is Key: Make sure your research questions are specific and focused. Instead of asking, "How can we improve customer satisfaction?" ask, "What specific aspects of our service do customers find most satisfying or dissatisfying?"
• Prioritize Questions: Determine the most critical questions that will have the most significant impact on your goals. Not all questions are equally important, so allocate your resources accordingly.
• Alignment with Objectives: Ensure that your research questions directly align with your overall objectives. If your goal is to increase sales, your research questions should be geared toward understanding customer buying behaviors and preferences.

Identifying Key Data Sources

Identifying the proper data sources is essential for gathering accurate and relevant information. Here are some examples of key data sources for different industries and purposes.

• Customer Data: This can include customer demographics, purchase history, website behavior, and feedback from customer service interactions.
• Market Research Reports: Utilize industry reports, competitor analyses, and market trend studies to gather external data and insights.
• Internal Records: Your organization's databases, financial records, and operational data can provide valuable insights into your business's performance.
• Social Media Platforms: Monitor social media channels to gather customer feedback, track brand mentions , and identify emerging trends in your industry.
• Web Analytics: Collect data on website traffic, user behavior, and conversion rates to optimize your online presence.

Setting Clear Data Collection Goals

Setting clear and measurable goals is essential to ensure your data collection efforts remain on track and deliver valuable results. Goals should be:

• Specific: Clearly define what you aim to achieve with your data collection. For instance, increasing website traffic by 20% in six months is a specific goal.
• Measurable: Establish criteria to measure your progress and success. Use metrics such as revenue growth, customer satisfaction scores, or conversion rates.
• Achievable: Set realistic goals that your team can realistically work towards. Overly ambitious goals can lead to frustration and burnout.
• Relevant : Ensure your goals align with your organization's broader objectives and strategic initiatives.
• Time-Bound: Set a timeframe within which you plan to achieve your goals. This adds a sense of urgency and helps you track progress effectively.

Choosing Data Collection Methods

Selecting the correct data collection methods is crucial for obtaining accurate and reliable data. Your choice should align with your research questions and goals. Here's a closer look at various data collection methods and their practical applications.

Types of Data Collection Methods

Now, let's explore different data collection methods in greater detail, including examples of when and how to use them effectively:

Surveys and Questionnaires

Surveys and questionnaires are versatile tools for gathering data from a large number of respondents. They are commonly used for:

• Customer Feedback: Collecting opinions and feedback on products, services, and overall satisfaction.
• Market Research: Assessing market preferences, identifying trends, and evaluating consumer behavior .
• Employee Surveys : Measuring employee engagement, job satisfaction, and feedback on workplace conditions.

Example: If you're running an e-commerce business and want to understand customer preferences, you can create an online survey asking customers about their favorite product categories, preferred payment methods, and shopping frequency.

To enhance your data collection endeavors, check out Appinio , a modern research platform that simplifies the process and maximizes the quality of insights. Appinio offers user-friendly survey and questionnaire tools that enable you to effortlessly design surveys tailored to your needs. It also provides seamless integration with interview and observation data, allowing you to consolidate your findings in one place.

Discover how Appinio can elevate your data collection efforts. Book a demo today to unlock a world of possibilities in gathering valuable insights!

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Interviews involve one-on-one or group conversations with participants to gather detailed insights. They are particularly useful for:

• Qualitative Research: Exploring complex topics, motivations, and personal experiences.
• In-Depth Analysis: Gaining a deep understanding of specific issues or situations.
• Expert Opinions: Interviewing industry experts or thought leaders to gather valuable insights.

Example: If you're a healthcare provider aiming to improve patient experiences, conducting interviews with patients can help you uncover specific pain points and suggestions for improvement.

Observations

Observations entail watching and recording behaviors or events in their natural context. This method is ideal for:

• Behavioral Studies: Analyzing how people interact with products or environments.
• Field Research: Collecting data in real-world settings, such as retail stores, public spaces, or classrooms.
• Ethnographic Research: Immersing yourself in a specific culture or community to understand their practices and customs.

Example: If you manage a retail store, observing customer traffic flow and purchasing behaviors can help optimize store layout and product placement.

Document Analysis

Document analysis involves reviewing and extracting information from written or digital documents. It is valuable for:

• Historical Research: Studying historical records, manuscripts, and archives.
• Content Analysis: Analyzing textual or visual content from websites, reports, or publications.
• Legal and Compliance: Reviewing contracts, policies, and legal documents for compliance purposes.

Example: If you're a content marketer, you can analyze competitor blog posts to identify common topics and keywords used in your industry.

Web Scraping

Web scraping is the automated process of extracting data from websites. It's suitable for:

• Competitor Analysis: Gathering data on competitor product prices, descriptions, and customer reviews.
• Market Research: Collecting data on product listings, reviews, and trends from e-commerce websites.
• News and Social Media Monitoring: Tracking news articles, social media posts, and comments related to your brand or industry.

Example: If you're in the travel industry, web scraping can help you collect pricing data for flights and accommodations from various travel booking websites to stay competitive.

Social Media Monitoring

Social media monitoring involves tracking and analyzing conversations and activities on social media platforms. It's valuable for:

• Brand Reputation Management: Monitoring brand mentions and sentiment to address customer concerns or capitalize on positive feedback.
• Competitor Analysis: Keeping tabs on competitors' social media strategies and customer engagement.
• Trend Identification: Identifying emerging trends and viral content within your industry.

Example: If you run a restaurant, social media monitoring can help you track customer reviews, comments, and hashtags related to your establishment, allowing you to respond promptly to customer feedback and trends.

By understanding the nuances and applications of these data collection methods, you can choose the most appropriate approach to gather valuable insights for your specific objectives. Remember that a well-thought-out data collection strategy is the cornerstone of informed decision-making and business success.

How to Design Your Data Collection Instruments?

Now that you've defined your research questions, identified data sources, set clear goals, and chosen appropriate data collection methods, it's time to design the instruments you'll use to collect data effectively.

Design Effective Survey Questions

Designing survey questions is a crucial step in gathering accurate and meaningful data. Here are some key considerations:

• Clarity: Ensure that your questions are clear and concise. Avoid jargon or ambiguous language that may confuse respondents.
• Relevance: Ask questions that directly relate to your research objectives. Avoid unnecessary or irrelevant questions that can lead to survey fatigue.
• Avoid Leading Questions: Formulate questions that do not guide respondents toward a particular answer. Maintain neutrality to get unbiased responses.
• Response Options: Provide appropriate response options, including multiple-choice, Likert scales, or open-ended formats, depending on the type of data you need.
• Pilot Testing: Before deploying your survey, conduct pilot tests with a small group to identify any issues with question wording or response options.

Craft Interview Questions for Insightful Conversations

Developing interview questions requires thoughtful consideration to elicit valuable insights from participants:

• Open-Ended Questions: Use open-ended questions to encourage participants to share their thoughts, experiences, and perspectives without being constrained by predefined answers.
• Probing Questions: Prepare follow-up questions to delve deeper into specific topics or clarify responses.
• Structured vs. Semi-Structured Interviews: Decide whether your interviews will follow a structured format with predefined questions or a semi-structured approach that allows flexibility.
• Avoid Biased Questions: Ensure your questions do not steer participants toward desired responses. Maintain objectivity throughout the interview.

Build an Observation Checklist for Data Collection

When conducting observations, having a well-structured checklist is essential:

• Clearly Defined Variables: Identify the specific variables or behaviors you are observing and ensure they are well-defined.
• Checklist Format: Create a checklist format that is easy to use and follow during observations. This may include checkboxes, scales, or space for notes.
• Training Observers: If you have a team of observers, provide thorough training to ensure consistency and accuracy in data collection.
• Pilot Observations: Before starting formal data collection, conduct pilot observations to refine your checklist and ensure it captures the necessary information.

Streamline Data Collection with Forms and Templates

Creating user-friendly data collection forms and templates helps streamline the process:

• Consistency: Ensure that all data collection forms follow a consistent format and structure, making it easier to compare and analyze data.
• Data Validation: Incorporate data validation checks to reduce errors during data entry. This can include dropdown menus, date pickers, or required fields.
• Digital vs. Paper Forms: Decide whether digital forms or traditional paper forms are more suitable for your data collection needs. Digital forms often offer real-time data validation and remote access.
• Accessibility: Make sure your forms and templates are accessible to all team members involved in data collection. Provide training if necessary.

The Data Collection Process

Now that your data collection instruments are ready, it's time to embark on the data collection process itself. This section covers the practical steps involved in collecting high-quality data.

1. Preparing for Data Collection

Adequate preparation is essential to ensure a smooth data collection process:

• Resource Allocation: Allocate the necessary resources, including personnel, technology, and materials, to support data collection activities.
• Training: Train data collection teams or individuals on the use of data collection instruments and adherence to protocols.
• Pilot Testing: Conduct pilot data collection runs to identify and resolve any issues or challenges that may arise.
• Ethical Considerations: Ensure that data collection adheres to ethical standards and legal requirements. Obtain necessary permissions or consent as applicable.

2. Conducting Data Collection

During data collection, it's crucial to maintain consistency and accuracy:

• Follow Protocols: Ensure that data collection teams adhere to established protocols and procedures to maintain data integrity.
• Supervision: Supervise data collection teams to address questions, provide guidance, and resolve any issues that may arise.
• Documentation: Maintain detailed records of the data collection process, including dates, locations, and any deviations from the plan.
• Data Security: Implement data security measures to protect collected information from unauthorized access or breaches.

3. Ensuring Data Quality and Reliability

After collecting data, it's essential to validate and ensure its quality:

• Data Cleaning: Review collected data for errors, inconsistencies, and missing values. Clean and preprocess the data to ensure accuracy.
• Quality Checks: Perform quality checks to identify outliers or anomalies that may require further investigation or correction.
• Data Validation: Cross-check data with source documents or original records to verify its accuracy and reliability.
• Data Auditing: Conduct periodic audits to assess the overall quality of the collected data and make necessary adjustments.

4. Managing Data Collection Teams

If you have multiple team members involved in data collection, effective management is crucial:

• Communication: Maintain open and transparent communication channels with team members to address questions, provide guidance, and ensure consistency.
• Performance Monitoring: Regularly monitor the performance of data collection teams, identifying areas for improvement or additional training.
• Problem Resolution: Be prepared to promptly address any challenges or issues that arise during data collection.
• Feedback Loop: Establish a feedback loop for data collection teams to share insights and best practices, promoting continuous improvement.

By following these steps and best practices in the data collection process, you can ensure that the data you collect is reliable, accurate, and aligned with your research objectives. This lays the foundation for meaningful analysis and informed decision-making.

How to Store and Manage Data?

It's time to explore the critical aspects of data storage and management, which are pivotal in ensuring the security, accessibility, and usability of your collected data.

Choosing Data Storage Solutions

Selecting the proper data storage solutions is a strategic decision that impacts data accessibility, scalability, and security. Consider the following factors:

• Cloud vs. On-Premises: Decide whether to store your data in the cloud or on-premises. Cloud solutions offer scalability, accessibility, and automatic backups, while on-premises solutions provide more control but require significant infrastructure investments.
• Data Types: Assess the types of data you're collecting, such as structured, semi-structured, or unstructured data. Choose storage solutions that accommodate your data formats efficiently.
• Scalability: Ensure that your chosen solution can scale as your data volume grows. This is crucial for preventing storage bottlenecks.
• Data Accessibility: Opt for storage solutions that provide easy and secure access to authorized users, whether they are on-site or remote.
• Data Recovery and Backup: Implement robust data backup and recovery mechanisms to safeguard against data loss due to hardware failures or disasters.

Data Security and Privacy

Data security and privacy are paramount, especially when handling sensitive or personal information.

• Encryption: Implement encryption for data at rest and in transit. Use encryption protocols like SSL/TLS for communication and robust encryption algorithms for storage.
• Access Control: Set up role-based access control (RBAC) to restrict access to data based on job roles and responsibilities. Limit access to only those who need it.
• Compliance: Ensure that your data storage and management practices comply with relevant data protection regulations, such as GDPR, HIPAA, or CCPA.
• Data Masking: Use data masking techniques to conceal sensitive information in non-production environments.
• Monitoring and Auditing: Continuously monitor access logs and perform regular audits to detect unauthorized activities and maintain compliance.

Data Organization and Cataloging

Organizing and cataloging your data is essential for efficient retrieval, analysis, and decision-making.

• Metadata Management: Maintain detailed metadata for each dataset, including data source, date of collection, data owner, and description. This makes it easier to locate and understand your data.
• Taxonomies and Categories: Develop taxonomies or data categorization schemes to classify data into logical groups, making it easier to find and manage.
• Data Versioning: Implement data versioning to track changes and updates over time. This ensures data lineage and transparency.
• Data Catalogs: Use data cataloging tools and platforms to create a searchable inventory of your data assets, facilitating discovery and reuse.
• Data Retention Policies: Establish clear data retention policies that specify how long data should be retained and when it should be securely deleted or archived.

How to Analyze and Interpret Data?

Once you've collected your data, let's take a look at the process of extracting valuable insights from your collected data through analysis and interpretation.

Data Cleaning and Preprocessing

Data cleaning and preprocessing are essential steps to ensure that your data is accurate and ready for analysis.

• Handling Missing Data: Develop strategies for dealing with missing data, such as imputation or removal, based on the nature of your data and research objectives.
• Outlier Detection: Identify and address outliers that can skew analysis results. Consider whether outliers should be corrected, removed, or retained based on their significance.
• Normalization and Scaling: Normalize or scale data to bring it within a common range, making it suitable for certain algorithms and models.
• Data Transformation: Apply data transformations, such as logarithmic scaling or categorical encoding, to prepare data for specific types of analysis.
• Data Imbalance: Address class imbalance issues in datasets, particularly machine learning applications, to avoid biased model training.

Exploratory Data Analysis (EDA)

EDA is the process of visually and statistically exploring your data to uncover patterns, trends, and potential insights.

• Descriptive Statistics: Calculate basic statistics like mean, median, and standard deviation to summarize data distributions.
• Data Visualization: Create visualizations such as histograms, scatter plots, and heatmaps to reveal relationships and patterns within the data.
• Correlation Analysis: Examine correlations between variables to understand how they influence each other.
• Hypothesis Testing: Conduct hypothesis tests to assess the significance of observed differences or relationships in your data.

Statistical Analysis Techniques

Choose appropriate statistical analysis techniques based on your research questions and data types.

• Descriptive Statistics: Use descriptive statistics to summarize and describe your data, providing an initial overview of key features.
• Inferential Statistics: Apply inferential statistics, including t-tests, ANOVA, or regression analysis, to test hypotheses and draw conclusions about population parameters.
• Non-parametric Tests: Employ non-parametric tests when assumptions of normality are not met or when dealing with ordinal or nominal data.
• Time Series Analysis: Analyze time-series data to uncover trends, seasonality, and temporal patterns.

Data Visualization

Data visualization is a powerful tool for conveying complex information in a digestible format.

• Charts and Graphs: Utilize various charts and graphs, such as bar charts, line charts, pie charts, and heatmaps, to represent data visually.
• Interactive Dashboards: Create interactive dashboards using tools like Tableau, Power BI, or custom web applications to allow stakeholders to explore data dynamically.
• Storytelling: Use data visualization to tell a compelling data-driven story, highlighting key findings and insights.
• Accessibility: Ensure that data visualizations are accessible to all audiences, including those with disabilities, by following accessibility guidelines.

Drawing Conclusions and Insights

Finally, drawing conclusions and insights from your data analysis is the ultimate goal.

• Contextual Interpretation: Interpret your findings in the context of your research objectives and the broader business or research landscape.
• Actionable Insights: Identify actionable insights that can inform decision-making, strategy development, or future research directions.
• Report Generation: Create comprehensive reports or presentations that communicate your findings clearly and concisely to stakeholders.
• Validation: Cross-check your conclusions with domain experts or subject matter specialists to ensure accuracy and relevance.

By following these steps in data analysis and interpretation, you can transform raw data into valuable insights that drive informed decisions, optimize processes, and create new opportunities for your organization.

How to Report and Present Data?

Now, let's explore the crucial steps of reporting and presenting data effectively, ensuring that your findings are communicated clearly and meaningfully to stakeholders.

1. Create Data Reports

Data reports are the culmination of your data analysis efforts, presenting your findings in a structured and comprehensible manner.

• Report Structure: Organize your report with a clear structure, including an introduction, methodology, results, discussion, and conclusions.
• Visualization Integration: Incorporate data visualizations, charts, and graphs to illustrate key points and trends.
• Clarity and Conciseness: Use clear and concise language, avoiding technical jargon, to make your report accessible to a diverse audience.
• Actionable Insights: Highlight actionable insights and recommendations that stakeholders can use to make informed decisions.
• Appendices: Include appendices with detailed methodology, data sources, and any additional information that supports your findings.

2. Leverage Data Visualization Tools

Data visualization tools can significantly enhance your ability to convey complex information effectively. Top data visualization tools include:

• Tableau: Tableau offers a wide range of visualization options and interactive dashboards, making it a popular choice for data professionals.
• Power BI: Microsoft's Power BI provides powerful data visualization and business intelligence capabilities, suitable for creating dynamic reports and dashboards.
• Python Libraries: Utilize Python libraries such as Matplotlib, Seaborn, and Plotly for custom data visualizations and analysis.
• Excel: Microsoft Excel remains a versatile tool for creating basic charts and graphs, particularly for smaller datasets.
• Custom Development: Consider custom development for specialized visualization needs or when existing tools don't meet your requirements.

3. Communicate Findings to Stakeholders

Effectively communicating your findings to stakeholders is essential for driving action and decision-making.

• Audience Understanding : Tailor your communication to the specific needs and background knowledge of your audience. Avoid technical jargon when speaking to non-technical stakeholders.
• Visual Storytelling: Craft a narrative that guides stakeholders through the data, highlighting key insights and their implications.
• Engagement: Use engaging and interactive presentations or reports to maintain the audience's interest and encourage participation.
• Question Handling: Be prepared to answer questions and provide clarifications during presentations or discussions. Anticipate potential concerns or objections.
• Feedback Loop: Encourage feedback and open dialogue with stakeholders to ensure your findings align with their objectives and expectations.

Data Collection Examples

To better understand the practical application of data collection in various domains, let's explore some real-world examples, including those in the business context. These examples illustrate how data collection can drive informed decision-making and lead to meaningful insights.

Business Customer Feedback Surveys

Scenario: A retail company wants to enhance its customer experience and improve product offerings. To achieve this, they initiate customer feedback surveys.

Data Collection Approach:

• Survey Creation: The company designs a survey with specific questions about customer preferences , shopping experiences , and product satisfaction.
• Distribution: Surveys are distributed through various channels, including email, in-store kiosks, and the company's website.
• Data Gathering: Responses from thousands of customers are collected and stored in a centralized database.

Data Analysis and Insights:

• Customer Sentiment Analysis: Using natural language processing (NLP) techniques, the company analyzes open-ended responses to gauge customer sentiment.
• Product Performance: Analyzing survey data, the company identifies which products receive the highest and lowest ratings, leading to decisions on which products to improve or discontinue.
• Store Layout Optimization: By examining feedback related to in-store experiences, the company can adjust store layouts and signage to enhance customer flow and convenience.

Healthcare Patient Record Digitization

Scenario: A healthcare facility aims to transition from paper-based patient records to digital records for improved efficiency and patient care.

• Scanning and Data Entry: Existing paper records are scanned, and data entry personnel convert them into digital format.
• Electronic Health Record (EHR) Implementation: The facility adopts an EHR system to store and manage patient data securely.
• Continuous Data Entry: As new patient information is collected, it is directly entered into the EHR system.
• Patient History Access: Physicians and nurses gain instant access to patient records, improving diagnostic accuracy and treatment.
• Data Analytics: Aggregated patient data can be analyzed to identify trends in diseases, treatment outcomes, and healthcare resource utilization.
• Resource Optimization: Analysis of patient data allows the facility to allocate resources more efficiently, such as staff scheduling based on patient admission patterns.

Social Media Engagement Monitoring

Scenario: A digital marketing agency manages social media campaigns for various clients and wants to track campaign performance and audience engagement.

• Social Media Monitoring Tools: The agency employs social media monitoring tools to collect data on post engagement, reach, likes, shares, and comments.
• Custom Tracking Links: Unique tracking links are created for each campaign to monitor traffic and conversions.
• Audience Demographics: Data on the demographics of engaged users is gathered from platform analytics.
• Campaign Effectiveness: The agency assesses which campaigns are most effective in terms of engagement and conversion rates.
• Audience Segmentation: Insights into audience demographics help tailor future campaigns to specific target demographics.
• Content Strategy: Analyzing which types of content (e.g., videos, infographics) generate the most engagement informs content strategy decisions.

These examples showcase how data collection serves as the foundation for informed decision-making and strategy development across diverse sectors. Whether improving customer experiences, enhancing healthcare services, or optimizing marketing efforts, data collection empowers organizations to harness valuable insights for growth and improvement.

Ethical Considerations in Data Collection

Ethical considerations are paramount in data collection to ensure privacy, fairness, and transparency. Addressing these issues is not only responsible but also crucial for building trust with stakeholders.

Informed Consent

Obtaining informed consent from participants is an ethical imperative. Transparency is critical, and participants should fully understand the purpose of data collection, how their data will be used, and any potential risks or benefits involved. Consent should be voluntary, and participants should have the option to withdraw their consent at any time without consequences.

Consent forms should be clear and comprehensible, avoiding overly complex language or legal jargon. Special care should be taken when collecting sensitive or personal data to ensure privacy rights are respected.

Privacy Protection

Protecting individuals' privacy is essential to maintain trust and comply with data protection regulations. Data anonymization or pseudonymization should be used to prevent the identification of individuals, especially when sharing or publishing data. Data encryption methods should be implemented to protect data both in transit and at rest, safeguarding it from unauthorized access.

Strict access controls should be in place to restrict data access to authorized personnel only, and clear data retention policies should be established and adhered to, preventing unnecessary data storage. Regular privacy audits should be conducted to identify and address potential vulnerabilities or compliance issues.

Bias and Fairness in Data Collection

Addressing bias and ensuring fairness in data collection is critical to avoid perpetuating inequalities. Data collection methods should be designed to minimize potential biases , such as selection bias or response bias. Efforts should be made to achieve diverse and representative samples , ensuring that data accurately reflects the population of interest. Fair treatment of all participants and data sources is essential, with discrimination based on characteristics such as race, gender, or socioeconomic status strictly avoided.

If algorithms are used in data collection or analysis, biases that may arise from automated processes should be assessed and mitigated. Ethical reviews or expert consultations may be considered when dealing with sensitive or potentially biased data. By adhering to ethical principles throughout the data collection process, individuals' rights are protected, and a foundation for responsible and trustworthy data-driven decision-making is established.

Data collection is the cornerstone of informed decision-making and insight generation in today's data-driven world. Whether you're a business seeking to understand your customers better, a researcher uncovering valuable trends, or anyone eager to harness the power of data, this guide has equipped you with the essential knowledge and tools. Remember, ethical considerations are paramount, and the quality of data matters.

Furthermore, as you embark on your data collection journey, always keep in mind the impact and potential of the information you gather. Each data point is a piece of the puzzle that can help you shape strategies, optimize operations, and make a positive difference. Data collection is not just a task; it's a powerful tool that empowers you to unlock opportunities, solve challenges, and stay ahead in a dynamic and ever-changing landscape. So, continue to explore, analyze, and draw valuable insights from your data, and let it be your compass on the path to success.

How to Collect Data in Minutes?

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How to conduct data collection in market research

Market research should be a critical part of every organization’s business strategy. It enables businesses to learn more about their target audience, what they look for in a product or service, what’s important to them, and how they want to engage with a business. 

When you’re conducting marketing research, you need to ensure that the data you gather is reliable and valid. Read on to learn about the importance of data collection in market research, different methods for collecting data, and software that makes market research data collection easy and effective.

Why data collection is important 

Collecting data is integral to conducting market research. Organizations connect with stakeholders — such as prospects, customers, competitors, investors, and employees — to learn more about their target market and how they can better serve them. The data an organization collects can steer its entire business strategy, so it’s vital for the data to be high- quality, secure, and relevant. 

“Data collection is the first and most-needed step to research the market,” says Daniela Sawyer, the founder of FindPeopleFast , a SaaS platform. “Product demand and the possible price are fixed after researching the market.”

Collecting data directly from a source (meaning firsthand feedback from your audiences, as opposed to secondhand data from other sources) ensures its accuracy. For example, if your business is considering going after a new target market, you may want to survey that audience to see whether they’re actually interested in the company’s offerings. 

If you use secondhand data, such as a report on a similar demographic, you may not achieve the same results. Because the data doesn’t apply to your company and its products/services specifically, it may not be as reliable for developing a successful business strategy.

Data collection methods for marketing teams

There are different ways to collect data in market research. Here are a few examples:

• Market survey: Sawyer notes this is one of the most effective methods of market research because you hear directly from the target audience about their level of interest in your product or service.
• Online forms: This is a quick and easy way to get information from website visitors, such as their contact information and preferences about what types of information they want to receive from your company.
• Customer service questionnaires: This is a great way for businesses to evaluate their customer service performance.
• Focus group surveys: “Direct interviews with the [product’s] users can give the most accurate data,” says Sawyer. This is a good way to get nuanced insights.

Depending on the goals of data collection, organizations may want to gather demographic data — such as age, income, location — from their prospects. If you want to improve your offerings, you may poll existing customers to learn more about their levels of engagement and satisfaction. Organizations can also conduct market research by surveying their employees and learning about their experiences with specific types of customers.

Better data collection with Jotform

Regardless of how an organization collects data for market research, it’s important to use the right software to ensure the process is seamless for both the company and its audience. 

Jotform offers market research teams a wide array of templates to enhance the data collection process, so organizations can learn more about their audience, what they want and don’t want, and how they can better serve them.

Examples of templates a marketing team can use include demographic surveys, subscribe forms, Net Promoter Score forms, pre-sales questionnaires, user experience surveys, and more. Each template is fully customizable, so you can add or change form fields based on your needs to gather the right kind of data. You can also add your own branding to the templates to create a consistent user experience.

So, you’ve learned about the importance of data collection in market research and the different ways to collect data. And now you know which software to use for gathering insights. There’s no better time to get started with your own market research efforts.

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How to Do Market Research: The Complete Guide

Learn how to do market research with this step-by-step guide, complete with templates, tools and real-world examples.

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What are your customers’ needs? How does your product compare to the competition? What are the emerging trends and opportunities in your industry? If these questions keep you up at night, it’s time to conduct market research.

Market research plays a pivotal role in your ability to stay competitive and relevant, helping you anticipate shifts in consumer behavior and industry dynamics. It involves gathering these insights using a wide range of techniques, from surveys and interviews to data analysis and observational studies.

In this guide, we’ll explore why market research is crucial, the various types of market research, the methods used in data collection, and how to effectively conduct market research to drive informed decision-making and success.

What is market research?

Market research is the systematic process of gathering, analyzing and interpreting information about a specific market or industry. The purpose of market research is to offer valuable insight into the preferences and behaviors of your target audience, and anticipate shifts in market trends and the competitive landscape. This information helps you make data-driven decisions, develop effective strategies for your business, and maximize your chances of long-term growth.

Why is market research important? 

By understanding the significance of market research, you can make sure you’re asking the right questions and using the process to your advantage. Some of the benefits of market research include:

• Informed decision-making: Market research provides you with the data and insights you need to make smart decisions for your business. It helps you identify opportunities, assess risks and tailor your strategies to meet the demands of the market. Without market research, decisions are often based on assumptions or guesswork, leading to costly mistakes.
• Customer-centric approach: A cornerstone of market research involves developing a deep understanding of customer needs and preferences. This gives you valuable insights into your target audience, helping you develop products, services and marketing campaigns that resonate with your customers.
• Competitive advantage: By conducting market research, you’ll gain a competitive edge. You’ll be able to identify gaps in the market, analyze competitor strengths and weaknesses, and position your business strategically. This enables you to create unique value propositions, differentiate yourself from competitors, and seize opportunities that others may overlook.
• Risk mitigation: Market research helps you anticipate market shifts and potential challenges. By identifying threats early, you can proactively adjust their strategies to mitigate risks and respond effectively to changing circumstances. This proactive approach is particularly valuable in volatile industries.
• Resource optimization: Conducting market research allows organizations to allocate their time, money and resources more efficiently. It ensures that investments are made in areas with the highest potential return on investment, reducing wasted resources and improving overall business performance.
• Adaptation to market trends: Markets evolve rapidly, driven by technological advancements, cultural shifts and changing consumer attitudes. Market research ensures that you stay ahead of these trends and adapt your offerings accordingly so you can avoid becoming obsolete. 

As you can see, market research empowers businesses to make data-driven decisions, cater to customer needs, outperform competitors, mitigate risks, optimize resources and stay agile in a dynamic marketplace. These benefits make it a huge industry; the global market research services market is expected to grow from $76.37 billion in 2021 to $108.57 billion in 2026 . Now, let’s dig into the different types of market research that can help you achieve these benefits.

Types of market research 

• Qualitative research
• Quantitative research
• Exploratory research
• Descriptive research
• Causal research
• Cross-sectional research
• Longitudinal research

Despite its advantages, 23% of organizations don’t have a clear market research strategy. Part of developing a strategy involves choosing the right type of market research for your business goals. The most commonly used approaches include:

1. Qualitative research

Qualitative research focuses on understanding the underlying motivations, attitudes and perceptions of individuals or groups. It is typically conducted through techniques like in-depth interviews, focus groups and content analysis — methods we’ll discuss further in the sections below. Qualitative research provides rich, nuanced insights that can inform product development, marketing strategies and brand positioning.

2. Quantitative research

Quantitative research, in contrast to qualitative research, involves the collection and analysis of numerical data, often through surveys, experiments and structured questionnaires. This approach allows for statistical analysis and the measurement of trends, making it suitable for large-scale market studies and hypothesis testing. While it’s worthwhile using a mix of qualitative and quantitative research, most businesses prioritize the latter because it is scientific, measurable and easily replicated across different experiments.

3. Exploratory research

Whether you’re conducting qualitative or quantitative research or a mix of both, exploratory research is often the first step. Its primary goal is to help you understand a market or problem so you can gain insights and identify potential issues or opportunities. This type of market research is less structured and is typically conducted through open-ended interviews, focus groups or secondary data analysis. Exploratory research is valuable when entering new markets or exploring new product ideas.

4. Descriptive research

As its name implies, descriptive research seeks to describe a market, population or phenomenon in detail. It involves collecting and summarizing data to answer questions about audience demographics and behaviors, market size, and current trends. Surveys, observational studies and content analysis are common methods used in descriptive research. 

5. Causal research

Causal research aims to establish cause-and-effect relationships between variables. It investigates whether changes in one variable result in changes in another. Experimental designs, A/B testing and regression analysis are common causal research methods. This sheds light on how specific marketing strategies or product changes impact consumer behavior.

6. Cross-sectional research

Cross-sectional market research involves collecting data from a sample of the population at a single point in time. It is used to analyze differences, relationships or trends among various groups within a population. Cross-sectional studies are helpful for market segmentation, identifying target audiences and assessing market trends at a specific moment.

7. Longitudinal research

Longitudinal research, in contrast to cross-sectional research, collects data from the same subjects over an extended period. This allows for the analysis of trends, changes and developments over time. Longitudinal studies are useful for tracking long-term developments in consumer preferences, brand loyalty and market dynamics.

Each type of market research has its strengths and weaknesses, and the method you choose depends on your specific research goals and the depth of understanding you’re aiming to achieve. In the following sections, we’ll delve into primary and secondary research approaches and specific research methods.

Primary vs. secondary market research

Market research of all types can be broadly categorized into two main approaches: primary research and secondary research. By understanding the differences between these approaches, you can better determine the most appropriate research method for your specific goals.

Primary market research 

Primary research involves the collection of original data straight from the source. Typically, this involves communicating directly with your target audience — through surveys, interviews, focus groups and more — to gather information. Here are some key attributes of primary market research:

• Customized data: Primary research provides data that is tailored to your research needs. You design a custom research study and gather information specific to your goals.
• Up-to-date insights: Because primary research involves communicating with customers, the data you collect reflects the most current market conditions and consumer behaviors.
• Time-consuming and resource-intensive: Despite its advantages, primary research can be labor-intensive and costly, especially when dealing with large sample sizes or complex study designs. Whether you hire a market research consultant, agency or use an in-house team, primary research studies consume a large amount of resources and time.

Secondary market research 

Secondary research, on the other hand, involves analyzing data that has already been compiled by third-party sources, such as online research tools, databases, news sites, industry reports and academic studies.

Here are the main characteristics of secondary market research:

• Cost-effective: Secondary research is generally more cost-effective than primary research since it doesn’t require building a research plan from scratch. You and your team can look at databases, websites and publications on an ongoing basis, without needing to design a custom experiment or hire a consultant. 
• Leverages multiple sources: Data tools and software extract data from multiple places across the web, and then consolidate that information within a single platform. This means you’ll get a greater amount of data and a wider scope from secondary research.
• Quick to access: You can access a wide range of information rapidly — often in seconds — if you’re using online research tools and databases. Because of this, you can act on insights sooner, rather than taking the time to develop an experiment. 

So, when should you use primary vs. secondary research? In practice, many market research projects incorporate both primary and secondary research to take advantage of the strengths of each approach.

One rule of thumb is to focus on secondary research to obtain background information, market trends or industry benchmarks. It is especially valuable for conducting preliminary research, competitor analysis, or when time and budget constraints are tight. Then, if you still have knowledge gaps or need to answer specific questions unique to your business model, use primary research to create a custom experiment. 

Market research methods

• Surveys and questionnaires
• Focus groups
• Observational research
• Online research tools
• Experiments
• Content analysis
• Ethnographic research

How do primary and secondary research approaches translate into specific research methods? Let’s take a look at the different ways you can gather data: 

1. Surveys and questionnaires

Surveys and questionnaires are popular methods for collecting structured data from a large number of respondents. They involve a set of predetermined questions that participants answer. Surveys can be conducted through various channels, including online tools, telephone interviews and in-person or online questionnaires. They are useful for gathering quantitative data and assessing customer demographics, opinions, preferences and needs. On average, customer surveys have a 33% response rate , so keep that in mind as you consider your sample size.

2. Interviews

Interviews are in-depth conversations with individuals or groups to gather qualitative insights. They can be structured (with predefined questions) or unstructured (with open-ended discussions). Interviews are valuable for exploring complex topics, uncovering motivations and obtaining detailed feedback. 

3. Focus groups

The most common primary research methods are in-depth webcam interviews and focus groups. Focus groups are a small gathering of participants who discuss a specific topic or product under the guidance of a moderator. These discussions are valuable for primary market research because they reveal insights into consumer attitudes, perceptions and emotions. Focus groups are especially useful for idea generation, concept testing and understanding group dynamics within your target audience.

4. Observational research

Observational research involves observing and recording participant behavior in a natural setting. This method is particularly valuable when studying consumer behavior in physical spaces, such as retail stores or public places. In some types of observational research, participants are aware you’re watching them; in other cases, you discreetly watch consumers without their knowledge, as they use your product. Either way, observational research provides firsthand insights into how people interact with products or environments.

5. Online research tools

You and your team can do your own secondary market research using online tools. These tools include data prospecting platforms and databases, as well as online surveys, social media listening, web analytics and sentiment analysis platforms. They help you gather data from online sources, monitor industry trends, track competitors, understand consumer preferences and keep tabs on online behavior. We’ll talk more about choosing the right market research tools in the sections that follow.

6. Experiments

Market research experiments are controlled tests of variables to determine causal relationships. While experiments are often associated with scientific research, they are also used in market research to assess the impact of specific marketing strategies, product features, or pricing and packaging changes.

7. Content analysis

Content analysis involves the systematic examination of textual, visual or audio content to identify patterns, themes and trends. It’s commonly applied to customer reviews, social media posts and other forms of online content to analyze consumer opinions and sentiments.

8. Ethnographic research

Ethnographic research immerses researchers into the daily lives of consumers to understand their behavior and culture. This method is particularly valuable when studying niche markets or exploring the cultural context of consumer choices.

How to do market research

• Set clear objectives
• Identify your target audience
• Choose your research methods
• Use the right market research tools
• Collect data
• Analyze data 
• Interpret your findings
• Identify opportunities and challenges
• Make informed business decisions
• Monitor and adapt

Now that you have gained insights into the various market research methods at your disposal, let’s delve into the practical aspects of how to conduct market research effectively. Here’s a quick step-by-step overview, from defining objectives to monitoring market shifts.

1. Set clear objectives

When you set clear and specific goals, you’re essentially creating a compass to guide your research questions and methodology. Start by precisely defining what you want to achieve. Are you launching a new product and want to understand its viability in the market? Are you evaluating customer satisfaction with a product redesign? 

Start by creating SMART goals — objectives that are specific, measurable, achievable, relevant and time-bound. Not only will this clarify your research focus from the outset, but it will also help you track progress and benchmark your success throughout the process. 

You should also consult with key stakeholders and team members to ensure alignment on your research objectives before diving into data collecting. This will help you gain diverse perspectives and insights that will shape your research approach.

2. Identify your target audience

Next, you’ll need to pinpoint your target audience to determine who should be included in your research. Begin by creating detailed buyer personas or stakeholder profiles. Consider demographic factors like age, gender, income and location, but also delve into psychographics, such as interests, values and pain points.

The more specific your target audience, the more accurate and actionable your research will be. Additionally, segment your audience if your research objectives involve studying different groups, such as current customers and potential leads.

If you already have existing customers, you can also hold conversations with them to better understand your target market. From there, you can refine your buyer personas and tailor your research methods accordingly.

3. Choose your research methods

Selecting the right research methods is crucial for gathering high-quality data. Start by considering the nature of your research objectives. If you’re exploring consumer preferences, surveys and interviews can provide valuable insights. For in-depth understanding, focus groups or observational research might be suitable. Consider using a mix of quantitative and qualitative methods to gain a well-rounded perspective. 

You’ll also need to consider your budget. Think about what you can realistically achieve using the time and resources available to you. If you have a fairly generous budget, you may want to try a mix of primary and secondary research approaches. If you’re doing market research for a startup , on the other hand, chances are your budget is somewhat limited. If that’s the case, try addressing your goals with secondary research tools before investing time and effort in a primary research study. 

4. Use the right market research tools

Whether you’re conducting primary or secondary research, you’ll need to choose the right tools. These can help you do anything from sending surveys to customers to monitoring trends and analyzing data. Here are some examples of popular market research tools:

• Market research software: Crunchbase is a platform that provides best-in-class company data, making it valuable for market research on growing companies and industries. You can use Crunchbase to access trusted, first-party funding data, revenue data, news and firmographics, enabling you to monitor industry trends and understand customer needs.

• Survey and questionnaire tools: SurveyMonkey is a widely used online survey platform that allows you to create, distribute and analyze surveys. Google Forms is a free tool that lets you create surveys and collect responses through Google Drive.
• Data analysis software: Microsoft Excel and Google Sheets are useful for conducting statistical analyses. SPSS is a powerful statistical analysis software used for data processing, analysis and reporting.
• Social listening tools: Brandwatch is a social listening and analytics platform that helps you monitor social media conversations, track sentiment and analyze trends. Mention is a media monitoring tool that allows you to track mentions of your brand, competitors and keywords across various online sources.
• Data visualization platforms: Tableau is a data visualization tool that helps you create interactive and shareable dashboards and reports. Power BI by Microsoft is a business analytics tool for creating interactive visualizations and reports.

5. Collect data

There’s an infinite amount of data you could be collecting using these tools, so you’ll need to be intentional about going after the data that aligns with your research goals. Implement your chosen research methods, whether it’s distributing surveys, conducting interviews or pulling from secondary research platforms. Pay close attention to data quality and accuracy, and stick to a standardized process to streamline data capture and reduce errors. 

6. Analyze data

Once data is collected, you’ll need to analyze it systematically. Use statistical software or analysis tools to identify patterns, trends and correlations. For qualitative data, employ thematic analysis to extract common themes and insights. Visualize your findings with charts, graphs and tables to make complex data more understandable.

If you’re not proficient in data analysis, consider outsourcing or collaborating with a data analyst who can assist in processing and interpreting your data accurately.

7. Interpret your findings

Interpreting your market research findings involves understanding what the data means in the context of your objectives. Are there significant trends that uncover the answers to your initial research questions? Consider the implications of your findings on your business strategy. It’s essential to move beyond raw data and extract actionable insights that inform decision-making.

Hold a cross-functional meeting or workshop with relevant team members to collectively interpret the findings. Different perspectives can lead to more comprehensive insights and innovative solutions.

8. Identify opportunities and challenges

Use your research findings to identify potential growth opportunities and challenges within your market. What segments of your audience are underserved or overlooked? Are there emerging trends you can capitalize on? Conversely, what obstacles or competitors could hinder your progress?

Lay out this information in a clear and organized way by conducting a SWOT analysis, which stands for strengths, weaknesses, opportunities and threats. Jot down notes for each of these areas to provide a structured overview of gaps and hurdles in the market.

9. Make informed business decisions

Market research is only valuable if it leads to informed decisions for your company. Based on your insights, devise actionable strategies and initiatives that align with your research objectives. Whether it’s refining your product, targeting new customer segments or adjusting pricing, ensure your decisions are rooted in the data.

At this point, it’s also crucial to keep your team aligned and accountable. Create an action plan that outlines specific steps, responsibilities and timelines for implementing the recommendations derived from your research. 

10. Monitor and adapt

Market research isn’t a one-time activity; it’s an ongoing process. Continuously monitor market conditions, customer behaviors and industry trends. Set up mechanisms to collect real-time data and feedback. As you gather new information, be prepared to adapt your strategies and tactics accordingly. Regularly revisiting your research ensures your business remains agile and reflects changing market dynamics and consumer preferences.

Online market research sources

As you go through the steps above, you’ll want to turn to trusted, reputable sources to gather your data. Here’s a list to get you started:

• Crunchbase: As mentioned above, Crunchbase is an online platform with an extensive dataset, allowing you to access in-depth insights on market trends, consumer behavior and competitive analysis. You can also customize your search options to tailor your research to specific industries, geographic regions or customer personas.

• Academic databases: Academic databases, such as ProQuest and JSTOR , are treasure troves of scholarly research papers, studies and academic journals. They offer in-depth analyses of various subjects, including market trends, consumer preferences and industry-specific insights. Researchers can access a wealth of peer-reviewed publications to gain a deeper understanding of their research topics.
• Government and NGO databases: Government agencies, nongovernmental organizations and other institutions frequently maintain databases containing valuable economic, demographic and industry-related data. These sources offer credible statistics and reports on a wide range of topics, making them essential for market researchers. Examples include the U.S. Census Bureau , the Bureau of Labor Statistics and the Pew Research Center .
• Industry reports: Industry reports and market studies are comprehensive documents prepared by research firms, industry associations and consulting companies. They provide in-depth insights into specific markets, including market size, trends, competitive analysis and consumer behavior. You can find this information by looking at relevant industry association databases; examples include the American Marketing Association and the National Retail Federation .
• Social media and online communities: Social media platforms like LinkedIn or Twitter (X) , forums such as Reddit and Quora , and review platforms such as G2 can provide real-time insights into consumer sentiment, opinions and trends. 

Market research examples

At this point, you have market research tools and data sources — but how do you act on the data you gather? Let’s go over some real-world examples that illustrate the practical application of market research across various industries. These examples showcase how market research can lead to smart decision-making and successful business decisions.

Example 1: Apple’s iPhone launch

Apple ’s iconic iPhone launch in 2007 serves as a prime example of market research driving product innovation in tech. Before the iPhone’s release, Apple conducted extensive market research to understand consumer preferences, pain points and unmet needs in the mobile phone industry. This research led to the development of a touchscreen smartphone with a user-friendly interface, addressing consumer demands for a more intuitive and versatile device. The result was a revolutionary product that disrupted the market and redefined the smartphone industry.

Example 2: McDonald’s global expansion

McDonald’s successful global expansion strategy demonstrates the importance of market research when expanding into new territories. Before entering a new market, McDonald’s conducts thorough research to understand local tastes, preferences and cultural nuances. This research informs menu customization, marketing strategies and store design. For instance, in India, McDonald’s offers a menu tailored to local preferences, including vegetarian options. This market-specific approach has enabled McDonald’s to adapt and thrive in diverse global markets.

Example 3: Organic and sustainable farming

The shift toward organic and sustainable farming practices in the food industry is driven by market research that indicates increased consumer demand for healthier and environmentally friendly food options. As a result, food producers and retailers invest in sustainable sourcing and organic product lines — such as with these sustainable seafood startups — to align with this shift in consumer values. 

The bottom line? Market research has multiple use cases and is a critical practice for any industry. Whether it’s launching groundbreaking products, entering new markets or responding to changing consumer preferences, you can use market research to shape successful strategies and outcomes.

Market research templates

You finally have a strong understanding of how to do market research and apply it in the real world. Before we wrap up, here are some market research templates that you can use as a starting point for your projects:

• Smartsheet competitive analysis templates : These spreadsheets can serve as a framework for gathering information about the competitive landscape and obtaining valuable lessons to apply to your business strategy.
• SurveyMonkey product survey template : Customize the questions on this survey based on what you want to learn from your target customers.
• HubSpot templates : HubSpot offers a wide range of free templates you can use for market research, business planning and more.
• SCORE templates : SCORE is a nonprofit organization that provides templates for business plans, market analysis and financial projections.
• SBA.gov : The U.S. Small Business Administration offers templates for every aspect of your business, including market research, and is particularly valuable for new startups. 

Strengthen your business with market research

When conducted effectively, market research is like a guiding star. Equipped with the right tools and techniques, you can uncover valuable insights, stay competitive, foster innovation and navigate the complexities of your industry.

Throughout this guide, we’ve discussed the definition of market research, different research methods, and how to conduct it effectively. We’ve also explored various types of market research and shared practical insights and templates for getting started. 

Now, it’s time to start the research process. Trust in data, listen to the market and make informed decisions that guide your company toward lasting success.

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Data collection for market research: techniques for gathering customer insights.

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Accurate data is key to understanding your target audience and making informed business decisions that appeal to customer wants and needs. However, the quality of your data greatly depends on the type of data and the collection methods employed. Below, we delve into this topic in greater detail, illustrating how first-party data is the secret ingredient to a winning marketing strategy.

What is data collection?

Data collection is the process of aggregating quantitative and qualitative data regarding a specific topic. In the case of market research, data collection is centered around consumer thoughts, opinions, and behavior. This information is used by company executives to make key business decisions, such as whether or not to launch a new product or how to best appeal to segmented markets.

Market researchers employ various methods to collect this data. They may, for example, survey consumers directly to learn more about how brand awareness has evolved over time. Or, a market researcher may choose to analyze social media data aggregated and sold by a third-party to better understand what appeals to millennial consumers.

Types of data collected

Data is integral to understanding your target audience and making informed business decisions. However, not all data is created equal. As a market researcher, there are three types of data at your disposal and each vary significantly in quality.

First-party data

First-party data is quantitative and qualitative information a company collects directly from its target audience. Your business may, for example, conduct a brand awareness survey  using an online panel. Your business may also glean insight from a customer’s purchase history.

Other examples of first-party data include:

• Customer demographics
• Sales interactions
• Website activity
• Mobile app data
• Email engagement

First-party data is considered superior to second- and third-party data because it reflects the interests, sentiments, and behaviors of the people who matter most: your customers. As a result, executives can confidently use this information to:

• Improve the customer buying experience
• Develop new products
• Break into new markets
• Understand customer lifecycles

Despite these advantages, collecting first-party data can be time-consuming for brands to tackle on their own. That’s where the Kantar Profiles Audience Network  comes in. As a leader in market research, we simplify primary data collection by connecting companies with more than 170 million compliant panelists across the world.

Second-party data

Comparatively, second-party data is information that brands do not collect themselves. Instead, they leverage or purchase the data from a trusted partner, typically a company with a vested interest in the respective audience. For example, a hotel booking website may purchase data from a car rental company. Or, a shoe designer may purchase data from a fashion publisher.

Much like first-party data, this information can provide valuable insights into your target audience. Second-party data can also be combined with first-party data to better understand consumers and strengthen predictive models.

Third-party data

Lastly, third-party data is information garnered from a business or organization without a direct connection to your target audience. This data is normally compiled from multiple sources (e.g., governmental, academic, nonprofit) and made available on a digital marketplace.

The key advantages of third-party data are breadth of data and cost; companies are afforded access to large amounts of data that would be financially challenging to obtain through other means.

Third-party data may also offer a breadth of data that may not otherwise be accessed as broadly through first-party data collection; for example, first-party purchase transactions may only cover a brand’s purchases through their retail or e-commerce outlets, while third-party compiled purchase data may offer insight into competitive brands and categories or retailers where shoppers are purchasing, which may offer deeper insight to inform brand marketing strategies.

Methods for data collection

How data is collected depends on the type of information being gathered. If your company hopes to collect first-party data, then you will employ primary data collection methods like in-person interviews and panel surveys. Otherwise, your company should expect to use secondary data collection methods such as observation and transactional tracking.

Primary data collection

Primary data collection is the process of collecting data from a first-hand source. This process may involve various data collection methods, including panel surveys, in-person interviews, focus groups, and forms.

Panel survey

A panel survey  is a study used to gauge ever-evolving consumer opinions and behaviours.

The goal of panel surveys varies. However, the primary goal of longitudinal studies is to collect information that reflects how the target population’s attitudes evolve over time. Similarly, a company may use a panel survey to evaluate how customer opinions about prices have changed.

The quantitative and qualitative information gleaned from this process illustrates consumer attitudes. A market researcher may, for example, be able to determine if brand awareness is increasing or decreasing. Or, if changes to company policy are bolstering customer satisfaction.

In-person interviews

A mainstay of market research, in-person interviews require that panelists physically arrive at a location. A market researcher then asks a series of questions, which are answered verbally.

There are valuable benefits to in-person interviews. Namely, the market researcher can answer any questions the panelists may have. Comparatively, if an individual becomes confused while taking an online survey, they may either offer a disingenuous answer or abandon the questionnaire altogether .

However, in-person interviews are onerous and expensive to orchestrate. Panelists may also feel less inclined to answer sensitive questions (e.g., ‘What is your annual salary’) honestly.

Focus groups

A focus group is a data collection method that brings together a small group of consumers. At the prompting of a moderator, group members share their thoughts and opinions on a specific topic.

This data collection method allows participants to express themselves and elaborate on their answers in a way that online questionnaires don’t allow. Because of this, market researchers are afforded richer, more meaningful qualitative data.

There are disadvantages, however. Some participants may not feel comfortable sharing information in a group setting, for instance. The qualitative data gleaned from focus groups can also be very difficult to analyze.

A form is simply a short questionnaire that a consumer completes, typically online. A form may request contact information, such as the consumer’s email address and phone number. It may also request demographic information.

Forms are fairly straightforward and cost-effective. If properly designed, these market research tools yield high-quality data that can be used to make informed business decisions.

Nevertheless, forms only capture a limited amount of information. Ergo, the data yielded may be one-dimensional compared to panel surveys, which aim to understand consumer opinions and how they evolve over time.

Secondary data collection

Unlike with primary data collection, secondary data collection does not require direct interaction with your target audience. Instead, this process involves aggregating data that is already available using methods such as transactional tracking, observation, online tracking, social media monitoring, and data review.

Transactional tracking

Transactional tracking refers to the act of monitoring and recording each time a customer makes a purchase. A company may purchase second-party transactional data from a partner to better understand what motivates consumer buying behavior.

Observation

In a traditional observation study, a market researcher (i.e., an observer) scrutinizes people in a specific situation. However, observation studies can also be automated. For example, a website analysis tool may track how many product pages a customer visits before making a purchase.

Online tracking

Online tracking is the practice of using tracking cookies to monitor a user’s online activity such as clicks, device specifications, location, and search history. Since this data can offer invaluable insights into consumer behaviors, third-party affiliate networks typically sell or share this information for marketing purposes.

Social media monitoring

Similarly, social media platforms such as Facebook and Instagram sell user data (e.g., browsing history, privacy settings, duration and frequency of activity) to third-party companies. These third-party companies act as middlemen, aggregating the data before reselling it to consumer companies.

Data review

Data review, or cleansing, is an integral step in secondary data collection. During this process, data is pulled from a second- or third-party dataset and then reviewed for duplicates, incomplete or incorrectly formatted data points, and other errors.

Importance of first-party data collection

Collecting high-quality first-party data is key to your company appealing to customers and securing a competitive edge. Why? Because first-party data affords accurate and relevant insight into the consumer psyche. Using this information, your C-suite can make confident choices about everything from adjusting pricing to launching a new product.

Start collecting first-party data with Kantar

Collecting high-quality first-party data that offers insight into your target market isn’t complicated when you partner with Kantar. In a world where the accuracy and reliability of second and third-party sources are diminishing, we assist companies with all steps of the market research process, including survey design, data collection, and data visualization.

Want to know more? Speak to our award-winning market research team  to learn how we deliver data from online research panels and sources you can act with, quickly.

Want more like this?

Read: Survey sample questions and templates 

Read: Everything you need to know about data quality 

Read: Guide to market research surveys

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7 Data Collection Methods in Business Analytics

• 02 Dec 2021

Data is being generated at an ever-increasing pace. According to Statista , the total volume of data was 64.2 zettabytes in 2020; it’s predicted to reach 181 zettabytes by 2025. This abundance of data can be overwhelming if you aren’t sure where to start.

So, how do you ensure the data you use is relevant and important to the business problems you aim to solve? After all, a data-driven decision is only as strong as the data it’s based on. One way is to collect data yourself.

Here’s a breakdown of data types, why data collection is important, what to know before you begin collecting, and seven data collection methods to leverage.

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What Is Data Collection?

Data collection is the methodological process of gathering information about a specific subject. It’s crucial to ensure your data is complete during the collection phase and that it’s collected legally and ethically . If not, your analysis won’t be accurate and could have far-reaching consequences.

In general, there are three types of consumer data:

• First-party data , which is collected directly from users by your organization
• Second-party data , which is data shared by another organization about its customers (or its first-party data)
• Third-party data , which is data that’s been aggregated and rented or sold by organizations that don’t have a connection to your company or users

Although there are use cases for second- and third-party data, first-party data (data you’ve collected yourself) is more valuable because you receive information about how your audience behaves, thinks, and feels—all from a trusted source.

Data can be qualitative (meaning contextual in nature) or quantitative (meaning numeric in nature). Many data collection methods apply to either type, but some are better suited to one over the other.

In the data life cycle , data collection is the second step. After data is generated, it must be collected to be of use to your team. After that, it can be processed, stored, managed, analyzed, and visualized to aid in your organization’s decision-making.

Before collecting data, there are several factors you need to define:

• The question you aim to answer
• The data subject(s) you need to collect data from
• The collection timeframe
• The data collection method(s) best suited to your needs

The data collection method you select should be based on the question you want to answer, the type of data you need, your timeframe, and your company’s budget.

The Importance of Data Collection

Collecting data is an integral part of a business’s success; it can enable you to ensure the data’s accuracy, completeness, and relevance to your organization and the issue at hand. The information gathered allows organizations to analyze past strategies and stay informed on what needs to change.

The insights gleaned from data can make you hyperaware of your organization’s efforts and give you actionable steps to improve various strategies—from altering marketing strategies to assessing customer complaints.

Basing decisions on inaccurate data can have far-reaching negative consequences, so it’s important to be able to trust your own data collection procedures and abilities. By ensuring accurate data collection, business professionals can feel secure in their business decisions.

Explore the options in the next section to see which data collection method is the best fit for your company.

7 Data Collection Methods Used in Business Analytics

Surveys are physical or digital questionnaires that gather both qualitative and quantitative data from subjects. One situation in which you might conduct a survey is gathering attendee feedback after an event. This can provide a sense of what attendees enjoyed, what they wish was different, and areas in which you can improve or save money during your next event for a similar audience.

While physical copies of surveys can be sent out to participants, online surveys present the opportunity for distribution at scale. They can also be inexpensive; running a survey can cost nothing if you use a free tool. If you wish to target a specific group of people, partnering with a market research firm to get the survey in front of that demographic may be worth the money.

Something to watch out for when crafting and running surveys is the effect of bias, including:

• Collection bias : It can be easy to accidentally write survey questions with a biased lean. Watch out for this when creating questions to ensure your subjects answer honestly and aren’t swayed by your wording.
• Subject bias : Because your subjects know their responses will be read by you, their answers may be biased toward what seems socially acceptable. For this reason, consider pairing survey data with behavioral data from other collection methods to get the full picture.

Related: 3 Examples of Bad Survey Questions & How to Fix Them

2. Transactional Tracking

Each time your customers make a purchase, tracking that data can allow you to make decisions about targeted marketing efforts and understand your customer base better.

Often, e-commerce and point-of-sale platforms allow you to store data as soon as it’s generated, making this a seamless data collection method that can pay off in the form of customer insights.

3. Interviews and Focus Groups

Interviews and focus groups consist of talking to subjects face-to-face about a specific topic or issue. Interviews tend to be one-on-one, and focus groups are typically made up of several people. You can use both to gather qualitative and quantitative data.

Through interviews and focus groups, you can gather feedback from people in your target audience about new product features. Seeing them interact with your product in real-time and recording their reactions and responses to questions can provide valuable data about which product features to pursue.

As is the case with surveys, these collection methods allow you to ask subjects anything you want about their opinions, motivations, and feelings regarding your product or brand. It also introduces the potential for bias. Aim to craft questions that don’t lead them in one particular direction.

One downside of interviewing and conducting focus groups is they can be time-consuming and expensive. If you plan to conduct them yourself, it can be a lengthy process. To avoid this, you can hire a market research facilitator to organize and conduct interviews on your behalf.

4. Observation

Observing people interacting with your website or product can be useful for data collection because of the candor it offers. If your user experience is confusing or difficult, you can witness it in real-time.

Yet, setting up observation sessions can be difficult. You can use a third-party tool to record users’ journeys through your site or observe a user’s interaction with a beta version of your site or product.

While less accessible than other data collection methods, observations enable you to see firsthand how users interact with your product or site. You can leverage the qualitative and quantitative data gleaned from this to make improvements and double down on points of success.

5. Online Tracking

To gather behavioral data, you can implement pixels and cookies. These are both tools that track users’ online behavior across websites and provide insight into what content they’re interested in and typically engage with.

You can also track users’ behavior on your company’s website, including which parts are of the highest interest, whether users are confused when using it, and how long they spend on product pages. This can enable you to improve the website’s design and help users navigate to their destination.

Inserting a pixel is often free and relatively easy to set up. Implementing cookies may come with a fee but could be worth it for the quality of data you’ll receive. Once pixels and cookies are set, they gather data on their own and don’t need much maintenance, if any.

It’s important to note: Tracking online behavior can have legal and ethical privacy implications. Before tracking users’ online behavior, ensure you’re in compliance with local and industry data privacy standards .

Online forms are beneficial for gathering qualitative data about users, specifically demographic data or contact information. They’re relatively inexpensive and simple to set up, and you can use them to gate content or registrations, such as webinars and email newsletters.

You can then use this data to contact people who may be interested in your product, build out demographic profiles of existing customers, and in remarketing efforts, such as email workflows and content recommendations.

Related: What Is Marketing Analytics?

7. Social Media Monitoring

Monitoring your company’s social media channels for follower engagement is an accessible way to track data about your audience’s interests and motivations. Many social media platforms have analytics built in, but there are also third-party social platforms that give more detailed, organized insights pulled from multiple channels.

You can use data collected from social media to determine which issues are most important to your followers. For instance, you may notice that the number of engagements dramatically increases when your company posts about its sustainability efforts.

Building Your Data Capabilities

Understanding the variety of data collection methods available can help you decide which is best for your timeline, budget, and the question you’re aiming to answer. When stored together and combined, multiple data types collected through different methods can give an informed picture of your subjects and help you make better business decisions.

Do you want to become a data-driven professional? Explore our eight-week Business Analytics course and our three-course Credential of Readiness (CORe) program to deepen your analytical skills and apply them to real-world business problems. Not sure which course is right for you? Download our free flowchart .

This post was updated on October 17, 2022. It was originally published on December 2, 2021.

About the Author

The Power of Data Collection: From Market Research to Marketing Success

In today’s business scenario, data is the ultimate power. From product research, planning and sales to marketing, you can genuinely deliver a better experience to your customers- if you have deployed the right methods to collect data.

Role of data collection in market research

Role of data collection in success of marketing campaigns, challenges and considerations in data collection, strategies for overcoming challenges and considerations, choosing the right data collection methods, building a culture of data-driven decision making from market research to marketing.

Data collection is a powerful tool for market research, enabling businesses to gain valuable insights and drive marketing success. As per Statista in 2021, $52 billion worth of marketing data was used globally.

By understanding the purpose, benefits, and types of data collected, as well as the methods and tools used, businesses can harness the power of data collection to achieve marketing success and maintain a competitive edge in the market.

Purpose of data collection in market research

The primary purpose of data collection in market research is to gather information about target markets, customers, competitors, and industry trends. This information enables businesses to:

• Understand customer needs and preferences
• Identify market opportunities and threats
• Develop effective marketing strategies
• Monitor and evaluate marketing performance

Benefits of data collection in market research

Data collection in market research offers several benefits, including:

• Informed decision-making: High-quality data enables businesses to make better-informed decisions, leading to more effective marketing strategies and improved results.
• Competitive advantage: Understanding market trends and customer preferences allows businesses to stay ahead of the competition and capitalize on emerging opportunities.
• Risk mitigation: Data collection helps businesses identify potential risks and develop strategies to address them, reducing the likelihood of costly mistakes.

Types of data collected in market research

Market research typically involves collecting two types of data:

• Quantitative data: Numerical data that can be measured and analyzed statistically, such as sales figures, market size, and customer demographics.
• Qualitative data: non-numerical data that provides insights into customer opinions, motivations, and preferences, such as customer feedback, reviews, and interview responses.

How is data collected for market research

Various methods and tools are used to collect data for market research, like:

• Surveys and questionnaires: Structured questionnaires administered to a sample of respondents, either online, in-person, or via phone, to gather quantitative and qualitative data.
• Interviews and focus groups: In-depth, one-on-one interviews or group discussions used to gather qualitative data and explore customer opinions, experiences, and motivations.
• Observational research: The systematic observation and recording of customer behavior, interactions, or environmental factors to gather qualitative data.
• Social media monitoring: Tracking and analyzing social media conversations, mentions, and trends to gather insights into customer opinions, preferences, and sentiment.

Like for example, most famous brands like Starbucks, Apple, and LEGO depend on market research. Here’s how:

• Starbucks tracks cultural trends, monitors social media, gathers customer feedback and in-store product testing by obtaining consumer feedback through its My Starbucks Idea platform.
• Apple hugely depends on market research to understand its consumers’ needs. Through Apple Customer Pulse, they conduct extensive customer satisfaction surveys.
• Over the years, LEGO has been primarily a boy-oriented toy company. Recently, they conducted a study for 3500 girls and their mothers to expand into a new market. LEGO used market research to determine the use of bright colors for its packaging and figurines’ size.

People also read: Top 5 data collection outsourcing companies in India

Purpose of data collection in execution of marketing campaigns

The primary purpose of data collection in marketing is to gather information that can be used to:

• Identify target audiences and understand their needs, preferences, and behaviors
• Develop and refine marketing messages and communication channels
• Monitor and evaluate the effectiveness of marketing campaigns
• Optimize marketing strategies based on data-driven insights

Data collection plays a crucial role in the success of marketing campaigns by:

• Informing marketing strategies: High-quality data enables businesses to develop effective marketing strategies based on consumer preferences, behavior, and market trends.
• Measuring campaign performance: Data collection allows businesses to track and evaluate the success of their marketing campaigns, enabling them to optimize strategies and improve results.
• Facilitating personalization and customization: Data-driven insights help businesses tailor their marketing messages and offers to individual customers, enhancing engagement and conversion rates.

Benefits of data collection for marketing

Data collection offers several benefits for marketing, including:

• Target audience analysis: Data collection helps businesses identify and understand their target audiences, enabling them to develop targeted marketing strategies.
• Consumer behavior understanding: Data-driven insights into consumer behavior can inform marketing tactics and help businesses better meet customer needs and preferences.
• Personalization and customization: Data collection enables businesses to create personalized marketing strategies that resonate with individual customers, leading to increased engagement and conversion rates.
• Effective messaging and communication: Data-driven insights can help businesses craft compelling marketing messages and select the most effective communication channels for their target audiences.

Techniques Used for Analyzing and Interpreting Data for Marketing analytics and visualization

Several techniques are used to analyze and interpret data for marketing purposes, including:

• Data analytics and visualization: Analyzing and visualizing data can help businesses identify patterns, trends, and insights that inform marketing strategies.
• Segmentation and targeting: Data analysis can be used to segment customers based on demographics, behavior, or preferences, enabling businesses to target specific groups with tailored marketing messages.
• A/B testing experimentation: A/B testing allows businesses to compare the performance of different marketing tactics, helping them optimize strategies based on data-driven insights.
• Predictive modeling and forecasting: Predictive modeling and forecasting techniques can help businesses anticipate future trends and customer behaviors, enabling them to develop proactive marketing strategies.

Data collection is a powerful tool that can drive marketing success by informing strategies, enabling personalization, and facilitating data-driven decision-making. By leveraging data collection and analysis techniques, businesses can create more effective marketing campaigns, better understand their target audiences, and ultimately achieve greater success in the market.

For example, Kellogg’s has achieved remarkable success in recent years by leveraging data to create personalized and innovative branded advertising campaigns. The company meticulously analyzes data from multiple sources, including its Family Rewards program, which boasts over 33 million American members.

Additionally, Kellogg’s examines data from its e-commerce platforms, tracking user behavior such as browsing patterns and time spent on specific products. This data-driven approach enables Kellogg’s to engage consumers effectively and tailor its marketing strategies for maximum impact.

• Data quality: Ensuring the accuracy, completeness, and consistency of collected data is crucial for reliable insights and decision-making. Businesses must implement data validation and cleansing processes to maintain high-quality data.
• Data privacy and security: With increasing concerns about data privacy and the rise of data protection regulations, businesses must ensure that they collect, store, and process data in compliance with applicable laws and ethical guidelines. This includes obtaining proper consent from data subjects and implementing robust data security measures.
• Data representativeness: To draw meaningful conclusions from collected data, companies must ensure that their data is representative of the target population. This involves selecting appropriate sampling methods and considering potential biases in data collection.
• Data integration: Businesses often collect data from various sources, which may have different formats and structures. Integrating and harmonizing this data can be challenging but is essential for comprehensive analysis and insights.
• Resource constraints: Data collection can be time-consuming and resource intensive. Businesses must allocate sufficient resources, including budget and personnel, to ensure effective data collection and management.
• Implement data quality best practices: Establish data quality standards and processes, such as data validation, cleansing, and monitoring, to maintain high-quality data.
• Adhere to data privacy and security guidelines: Develop and implement data privacy and security policies, obtain proper consent from data subjects, and invest in robust data security measures to protect collected data.
• Ensure data representativeness: Select appropriate sampling methods and consider potential biases in data collection to ensure that your data is representative of the target population.
• Leverage data integration tools: Utilize data integration tools and platforms to harmonize data from various sources, enabling comprehensive analysis and insights.
• Allocate sufficient resources: Plan and allocate adequate resources, including budget and personnel, for data collection and management to ensure the success of your marketing campaigns.

Fine-tune your data collection. Create a strong foundation for effective market research.

Overview of primary and secondary data sources

• Primary data sources: Primary data is collected directly from the source, such as through surveys, interviews, or observations. This type of data is tailored to specific research objectives and provides unique insights into customer behavior, preferences, and opinions.
• Secondary data sources: Secondary data is obtained from existing sources, such as published reports, articles, or databases. This type of data can provide valuable context and background information for market research but may not be as specific or up to date as primary data.

Selecting appropriate data collection methods based on research objectives

To choose the right data collection methods, consider the following factors:

• Research objectives: Determine the specific information you need to achieve your research goals and select data collection methods that can provide this information.
• Time and resources: Consider the time and resources available for data collection and choose methods that are feasible within these constraints.
• Data quality and reliability: Select data collection methods that ensure the accuracy, completeness, and consistency of the data.

Commonly used data collection techniques

• Surveys and questionnaires: Structured questionnaires administered to a sample of respondents to gather quantitative and qualitative data.

Analyzing and interpreting collected data

Once data is collected, it must be analyzed and interpreted to extract actionable insights. This process involves:

• Organizing and cleaning data for analysis: Prepare the data for analysis by organizing it into structured format and cleaning it to ensure accuracy and consistency.
• Utilizing statistical techniques for data analysis: Apply statistical techniques, such as descriptive statistics, inferential statistics, or regression analysis, to analyze the data and identify patterns, trends, and relationships.
• Data visualization for effective interpretation: Use data visualization tools, such as charts, graphs, or heatmaps, to present the data in a visually appealing and easily understandable format.
• Extracting actionable insights from research findings: Interpret the data analysis results and extract actionable insights that can inform marketing strategies and decision-making.

To fully harness the power of data collection, businesses must build a culture of data-driven decision-making that spans from market research to marketing execution.

Creating a data-driven mindset within the organization

To foster a data-driven culture, businesses should:

• Encourage employees to base decisions on data and evidence, rather than intuition or assumptions.
• Provide training and resources to help employees develop data literacy and analytical skills.
• Recognize and reward data-driven decision-making and continuous learning.

Investing in data infrastructure and analytics capabilities

To support data-driven decision-making, businesses must invest in:

• Robust data infrastructure that enables efficient data collection, storage, and management.
• Advanced analytics tools and platforms that facilitate data analysis and visualization.
• Skilled data professionals, such as data analysts, data scientists, and data engineers.

Promoting collaboration between marketing and research teams

Effective data-driven marketing requires collaboration between marketing and research teams. To promote collaboration:

• Establish clear communication channels and processes for sharing data and insights.
• Encourage cross-functional teamwork and joint problem-solving.
• Align research objectives with marketing goals and strategies.

Encouraging continuous learning and adaptation based on data insights

A data-driven culture thrives on continuous learning and adaptation. Businesses should:

• Regularly review and evaluate marketing strategies and tactics based on data insights.
• Encourage experimentation and testing to identify optimal marketing approaches.
• Foster a culture of learning from both successes and failures.

Leveraging data insights for competitive advantage:

• Understanding target market and consumer preferences: Data-driven insights help businesses better understand their target market and tailor marketing strategies to meet customer needs and preferences.
• Identifying market gaps and untapped opportunities: Data analysis can reveal market gaps and untapped opportunities, enabling businesses to develop innovative products, services, and marketing campaigns.
• Monitoring competitor strategies and benchmarking performance: Data-driven market research allows businesses to monitor competitor strategies, benchmark their performance, and identify areas for improvement.
• Developing tailored marketing campaigns and messaging: Data insights enable businesses to create personalized marketing campaigns and messaging that resonate with their target audience, leading to increased engagement and conversion rates.
• Pricing: Data analysis can help businesses identify the optimal pricing strategy for their products or services, taking into account factors such as customer price sensitivity, competitor pricing, and market demand.
• Product development: Data-driven market research can reveal customer needs, preferences, and pain points, enabling businesses to develop innovative products and features that address these needs and differentiate them from competitors.
• Marketing strategies: Data insights can inform the development of tailored marketing campaigns, messaging, and communication channels that resonate with the target audience, leading to increased engagement and conversion rates.

In conclusion, data collection is a critical component of market research and marketing success, providing valuable insights that drive informed strategies and decision-making. By prioritizing data collection and leveraging its power, businesses can create a competitive advantage, optimize their marketing strategies, and achieve greater success in the market.

As the business landscape continues to evolve, data-driven decision-making will become increasingly important, shaping the future of marketing and business success. It is essential for businesses to embrace data collection and cultivate a data-driven culture to stay ahead of the curve and maintain a competitive edge in the ever-evolving data-driven world.

Use the right data to power your market research and marketing.

About Author

Chirag Shivalker heads the digital content for HabileData , a global data management solutions outsourcing company, rated as one of the top BPO companies in India. Chirag's focus has been on enterprise wide data digitization, data governance, data quality, and BI capabilities.

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How To Present Your Market Research Results And Reports In An Efficient Way

Table of Contents

1) What Is A Market Research Report?

2) Market Research Reports Examples

3) Why Do You Need Market Research Reports

4) How To Make A Market Research Report?

5) Types Of Market Research Reports

6) Challenges & Mistakes Market Research Reports

Market research analyses are the go-to solution for many professionals, and for good reason: they save time, offer fresh insights, and provide clarity on your business. In turn, market research reports will help you to refine and polish your strategy. Plus, a well-crafted report will give your work more credibility while adding weight to any marketing recommendations you offer a client or executive.

But, while this is the case, today’s business world still lacks a way to present market-based research results efficiently. The static, antiquated nature of PowerPoint makes it a bad choice for presenting research discoveries, yet it is still widely used to present results. 

Fortunately, things are moving in the right direction. There are online data visualization tools that make it easy and fast to build powerful market research dashboards. They come in handy to manage the outcomes, but also the most important aspect of any analysis: the presentation of said outcomes, without which it becomes hard to make accurate, sound decisions. 

Here, we consider the benefits of conducting research analyses while looking at how to write and present market research reports, exploring their value, and, ultimately, getting the very most from your research results by using professional market research software .

Let’s get started.

What Is a Market Research Report?

A market research report is an online reporting tool used to analyze the public perception or viability of a company, product, or service. These reports contain valuable and digestible information like customer survey responses and social, economic, and geographical insights.

On a typical market research results example, you can interact with valuable trends and gain insight into consumer behavior and visualizations that will empower you to conduct effective competitor analysis. Rather than adding streams of tenuous data to a static spreadsheet, a full market research report template brings the outcomes of market-driven research to life, giving users a data analysis tool to create actionable strategies from a range of consumer-driven insights.

With digital market analysis reports, you can make your business more intelligent more efficient, and, ultimately, meet the needs of your target audience head-on. This, in turn, will accelerate your commercial success significantly.

Your Chance: Want to test a market research reporting software? Explore our 14-day free trial & benefit from interactive research reports!

How To Present Your Results: 4 Essential Market Research Report Templates

When it comes to sharing rafts of invaluable information, research dashboards are invaluable.

Any market analysis report example worth its salt will allow everyone to get a firm grip on their results and discoveries on a single page with ease. These dynamic online dashboards also boast interactive features that empower the user to drill down deep into specific pockets of information while changing demographic parameters, including gender, age, and region, filtering the results swiftly to focus on the most relevant insights for the task at hand.

These four market research report examples are different but equally essential and cover key elements required for market survey report success. You can also modify each and use it as a client dashboard .

While there are numerous types of dashboards that you can choose from to adjust and optimize your results, we have selected the top 3 that will tell you more about the story behind them. Let’s take a closer look.

1. Market Research Report: Brand Analysis

Our first example shares the results of a brand study. To do so, a survey has been performed on a sample of 1333 people, information that we can see in detail on the left side of the board, summarizing the gender, age groups, and geolocation.

**click to enlarge**

At the dashboard's center, we can see the market-driven research discoveries concerning first brand awareness with and without help, as well as themes and celebrity suggestions, to know which image the audience associates with the brand.

Such dashboards are extremely convenient to share the most important information in a snapshot. Besides being interactive (but it cannot be seen on an image), it is even easier to filter the results according to certain criteria without producing dozens of PowerPoint slides. For instance, I could easily filter the report by choosing only the female answers, only the people aged between 25 and 34, or only the 25-34 males if that is my target audience.

Primary KPIs:

a) Unaided Brand Awareness

The first market research KPI in this most powerful report example comes in the form of unaided brand awareness. Presented in a logical line-style chart, this particular market study report sample KPI is invaluable, as it will give you a clear-cut insight into how people affiliate your brand within their niche.

As you can see from our example, based on a specific survey question, you can see how your brand stacks up against your competitors regarding awareness. Based on these outcomes, you can formulate strategies to help you stand out more in your sector and, ultimately, expand your audience.

b) Aided Brand Awareness

This market survey report sample KPI focuses on aided brand awareness. A visualization that offers a great deal of insight into which brands come to mind in certain niches or categories, here, you will find out which campaigns and messaging your target consumers are paying attention to and engaging with.

By gaining access to this level of insight, you can conduct effective competitor research and gain valuable inspiration for your products, promotional campaigns, and marketing messages.

c) Brand image

When it comes to research reporting, understanding how others perceive your brand is one of the most golden pieces of information you could acquire. If you know how people feel about your brand image, you can take informed and very specific actions that will enhance the way people view and interact with your business.

By asking a focused question, this visual of KPIs will give you a definitive idea of whether respondents agree, disagree, or are undecided on particular descriptions or perceptions related to your brand image. If you’re looking to present yourself and your message in a certain way (reliable, charming, spirited, etc.), you can see how you stack up against the competition and find out if you need to tweak your imagery or tone of voice - invaluable information for any modern business.

d) Celebrity analysis

This indicator is a powerful part of our research KPI dashboard on top, as it will give you a direct insight into the celebrities, influencers, or public figures that your most valued consumers consider when thinking about (or interacting with) your brand.

Displayed in a digestible bar chart-style format, this useful metric will not only give you a solid idea of how your brand messaging is perceived by consumers (depending on the type of celebrity they associate with your brand) but also guide you on which celebrities or influencers you should contact.

By working with the right influencers in your niche, you will boost the impact and reach of your marketing campaigns significantly, improving your commercial awareness in the process. And this is the KPI that will make it happen.

2. Market Research Results On Customer Satisfaction

Here, we have some of the most important data a company should care about: their already-existing customers and their perception of their relationship with the brand. It is crucial when we know that it is five times more expensive to acquire a new consumer than to retain one.

This is why tracking metrics like the customer effort score or the net promoter score (how likely consumers are to recommend your products and services) is essential, especially over time. You need to improve these scores to have happy customers who will always have a much bigger impact on their friends and relatives than any of your amazing ad campaigns. Looking at other satisfaction indicators like the quality, pricing, and design, or the service they received is also a best practice: you want a global view of your performance regarding customer satisfaction metrics .

Such research results reports are a great tool for managers who do not have much time and hence need to use them effectively. Thanks to these dashboards, they can control data for long-running projects anytime.

Primary KPIs :

a) Net Promoter Score (NPS)

Another pivotal part of any informative research presentation is your NPS score, which will tell you how likely a customer is to recommend your brand to their peers.

Centered on overall customer satisfaction, your NPS Score can cover the functions and output of many departments, including marketing, sales, and customer service, but also serve as a building block for a call center dashboard . When you’re considering how to present your research effectively, this balanced KPI offers a masterclass. It’s logical, it has a cohesive color scheme, and it offers access to vital information at a swift glance. With an NPS Score, customers are split into three categories: promoters (those scoring your service 9 or 10), passives (those scoring your service 7 or 8), and detractors (those scoring your service 0 to 6). The aim of the game is to gain more promoters. By gaining an accurate snapshot of your NPS Score, you can create intelligent strategies that will boost your results over time.

b) Customer Satisfaction Score (CSAT)

The next in our examples of market research reports KPIs comes in the form of the CSAT. The vast majority of consumers that have a bad experience will not return. Honing in on your CSAT is essential if you want to keep your audience happy and encourage long-term consumer loyalty.

This magnificent, full report KPI will show how satisfied customers are with specific elements of your products or services. Getting to grips with these scores will allow you to pinpoint very specific issues while capitalizing on your existing strengths. As a result, you can take measures to improve your CSAT score while sharing positive testimonials on your social media platforms and website to build trust.

c) Customer Effort Score (CES)

When it comes to presenting research findings, keeping track of your CES Score is essential. The CES Score KPI will give you instant access to information on how easy or difficult your audience can interact with or discover your company based on a simple scale of one to ten.

By getting a clear-cut gauge of how your customers find engagement with your brand, you can iron out any weaknesses in your user experience (UX) offerings while spotting any friction, bottlenecks, or misleading messaging. In doing so, you can boost your CES score, satisfy your audience, and boost your bottom line.

3. Market Research Results On Product Innovation

This final market-driven research example report focuses on the product itself and its innovation. It is a useful report for future product development and market potential, as well as pricing decisions.

Using the same sample of surveyed people as for the first market-focused analytical report , they answer questions about their potential usage and purchase of the said product. It is good primary feedback on how the market would receive the new product you would launch. Then comes the willingness to pay, which helps set a price range that will not be too cheap to be trusted nor too expensive for what it is. That will be the main information for your pricing strategy.

a) Usage Intention

The first of our product innovation KPI-based examples comes in the form of usage intention. When you’re considering how to write a market research report, including metrics centered on consumer intent is critical.

This simple yet effective visualization will allow you to understand not only how users see your product but also whether they prefer previous models or competitor versions . While you shouldn’t base all of your product-based research on this KPI, it is very valuable, and you should use it to your advantage frequently.

b) Purchase Intention

Another aspect to consider when looking at how to present market research data is your audience’s willingness or motivation to purchase your product. Offering percentage-based information, this effective KPI provides a wealth of at-a-glance information to help you make accurate forecasts centered on your product and service offerings.

Analyzing this information regularly will give you the confidence and direction to develop strategies that will steer you to a more prosperous future, meeting the ever-changing needs of your audience on an ongoing basis.

c) Willingness To Pay (WPS)

Our final market research example KPI is based on how willing customers are to pay for a particular service or product based on a specific set of parameters. This dynamic visualization, represented in an easy-to-follow pie chart, will allow you to realign the value of your product (USPs, functions, etc.) while setting price points that are most likely to result in conversions. This is a market research presentation template that every modern organization should use to its advantage.

4. Market Research Report On Customer Demographics 

This particular example of market research report, generated with a modern dashboard creator , is a powerful tool, as it displays a cohesive mix of key demographic information in one intuitive space.

By breaking down these deep pockets of consumer-centric information, you can gain the power to develop more impactful customer communications while personalizing every aspect of your target audience’s journey across every channel or touchpoint. As a result, you can transform theoretical insights into actionable strategies that will result in significant commercial growth. 

Every section of this responsive marketing research report works in unison to build a profile of your core audience in a way that will guide your company’s consumer-facing strategies with confidence. With in-depth visuals based on gender, education level, and tech adoption, you have everything you need to speak directly to your audience at your fingertips.

Let’s look at the key performance indicators (KPIs) of this invaluable market research report example in more detail.

a) Customer By Gender

This KPI is highly visual and offers a clear-cut representation of your company’s gender share over time. By gaining access to this vital information, you can deliver a more personalized experience to specific audience segments while ensuring your messaging is fair, engaging, and inclusive.

b) Customers by education level

The next market analysis report template is a KPI that provides a logical breakdown of your customers’ level of education. By using this as a demographic marker, you can refine your products to suit the needs of your audience while crafting your content in a way that truly resonates with different customer groups.

c) Customers by technology adoption

Particularly valuable if you’re a company that sells tech goods or services, this linear KPI will show you where your customers are in terms of technological know-how or usage. By getting to grips with this information over time, you can develop your products or services in a way that offers direct value to your consumers while making your launches or promotions as successful as possible.

d) Customer age groups

By understanding your customers’ age distribution in detail, you can gain a deep understanding of their preferences. And that’s exactly what this market research report sample KPI does. Presented in a bar chart format, this KPI will give you a full breakdown of your customers’ age ranges, allowing you to build detailed buyer personas and segment your audience effectively.

Why Do You Need Market Research Reports?

As the adage goes, “Look before you leap“ – which is exactly what a research report is here for. As the headlights of a car, they will show you the pitfalls and fast lanes on your road to success: likes and dislikes of a specific market segment in a certain geographical area, their expectations, and readiness. Among other things, a research report will let you:

• Get a holistic view of the market : learn more about the target market and understand the various factors involved in the buying decisions. A broader view of the market lets you benchmark other companies you do not focus on. This, in turn, will empower you to gather the industry data that counts most. This brings us to our next point.
• Curate industry information with momentum: Whether you’re looking to rebrand, improve on an existing service, or launch a new product, time is of the essence. By working with the best market research reports created with modern BI reporting tools , you can visualize your discoveries and data, formatting them in a way that not only unearths hidden insights but also tells a story - a narrative that will gain a deeper level of understanding into your niche or industry. The features and functionality of a market analysis report will help you grasp the information that is most valuable to your organization, pushing you ahead of the pack in the process.
• Validate internal research: Doing the internal analysis is one thing, but double-checking with a third party also greatly helps avoid getting blinded by your own data.
• Use actionable data and make informed decisions: Once you understand consumer behavior as well as the market, your competitors, and the issues that will affect the industry in the future, you are better armed to position your brand. Combining all of it with the quantitative data collected will allow you to more successful product development. To learn more about different methods, we suggest you read our guide on data analysis techniques .
• Strategic planning: When you want to map out big-picture organizational goals, launch a new product development, plan a geographic market expansion, or even a merger and acquisition – all of this strategic thinking needs solid foundations to fulfill the variety of challenges that come along.
• Consistency across the board: Collecting, presenting, and analyzing your results in a way that’s smarter, more interactive, and more cohesive will ensure your customer communications, marketing campaigns, user journey, and offerings meet your audience’s needs consistently across the board. The result? Faster growth, increased customer loyalty, and more profit.
• Better communication: The right market research analysis template (or templates) will empower everyone in the company with access to valuable information - the kind that is relevant and comprehensible. When everyone is moving to the beat of the same drum, they will collaborate more effectively and, ultimately, push the venture forward thanks to powerful online data analysis techniques.
• Centralization: Building on the last point, using a powerful market research report template in the form of a business intelligence dashboard will make presenting your findings to external stakeholders and clients far more effective, as you can showcase a wealth of metrics, information, insights, and invaluable feedback from one centralized, highly visual interactive screen. 
• Brand reputation: In the digital age, brand reputation is everything. By making vital improvements in all of the key areas above, you will meet your customers’ needs head-on with consistency while finding innovative ways to stand out from your competitors. These are the key ingredients of long-term success.

How To Present Market Research Analysis Results?

Here we look at how you should present your research reports, considering the steps it takes to connect with the outcomes you need to succeed:

• Collect your data 

As with any reporting process, you first and foremost need to collect the data you’ll use to conduct your studies. Businesses conduct research studies to analyze their brand awareness, identity, and influence in the market. For product development and pricing decisions, among many others. That said, there are many ways to collect information for a market research report. Among some of the most popular ones, we find: 

• Surveys: Probably the most common way to collect research data, surveys can come in the form of open or closed questions that can be answered anonymously. They are the cheapest and fastest way to collect insights about your customers and business. 
• Interviews : These are face-to-face discussions that allow the researcher to analyze responses as well as the body language of the interviewees. This method is often used to define buyer personas by analyzing the subject's budget, job title, lifestyle, wants, and needs, among other things. 
• Focus groups : This method involves a group of people discussing a topic with a mediator. It is often used to evaluate a new product or new feature or to answer a specific question that the researcher might have. 
• Observation-based research : In this type of research, the researcher or business sits back and watches customers interact with the product without any instructions or help. It allows us to identify pain points as well as strong features. 
• Market segmentation : This study allows you to identify and analyze potential market segments to target. Businesses use it to expand into new markets and audiences. 

These are just a few of the many ways in which you can gather your information. The important point is to keep the research objective as straightforward as possible. Supporting yourself with professional BI solutions to clean, manage, and present your insights is probably the smartest choice.

2. Hone in on your research:

When looking at how to source consumer research in a presentation, you should focus on two areas: primary and secondary research. Primary research comes from your internal data, monitoring existing organizational practices, the effectiveness of sales, and the tools used for communication, for instance. Primary research also assesses market competition by evaluating the company plans of the competitors. Secondary research focuses on existing data collected by a third party, information used to perform benchmarking and market analysis. Such metrics help in deciding which market segments are the ones the company should focus its efforts on or where the brand is standing in the minds of consumers. Before you start the reporting process, you should set your goals, segmenting your research into primary and secondary segments to get to grips with the kind of information you need to work with to achieve effective results.

3. Segment your customers:

To give your market research efforts more context, you should segment your customers into different groups according to the preferences outlined in the survey or feedback results or by examining behavioral or demographic data.

If you segment your customers, you can tailor your market research and analysis reports to display only the information, charts, or graphics that will provide actionable insights into their wants, needs, or industry-based pain points. 

• Identify your stakeholders:

Once you’ve drilled down into your results and segmented your consumer groups, it’s important to consider the key stakeholders within the organization that will benefit from your information the most. 

By looking at both internal and external stakeholders, you will give your results a path to effective presentation, gaining the tools to understand which areas of feedback or data are most valuable, as well as most redundant. As a consequence, you will ensure your results are concise and meet the exact information needs of every stakeholder involved in the process.

• Set your KPIs:

First, remember that your reports should be concise and accurate - straight to the point without omitting any essential information. Work to ensure your insights are clean and organized, with participants grouped into relevant categories (demographics, profession, industry, education, etc.). Once you’ve organized your research, set your goals, and cleaned your data, you should set your KPIs to ensure your report is populated with the right visualizations to get the job done. Explore our full library of interactive KPI examples for inspiration.

• Include competitor’s analysis 

Whether you are doing product innovation research, customer demographics, pricing, or any other, including some level of insights about competitors in your reports is always recommended as it can help your business or client better understand where they stand in the market. That being said, competitor analysis is not as easy as picking a list of companies in the same industry and listing them. Your main competitor can be just a company's division in an entirely different industry. For example, Apple Music competes with Spotify even though Apple is a technology company. Therefore, it is important to carefully analyze competitors from a general but detailed level. 

Providing this kind of information in your reports can also help you find areas that competitors are not exploiting or that are weaker and use them to your advantage to become a market leader. 

• Produce your summary:

To complement your previous efforts, writing an executive summary of one or two pages that will explain the general idea of the report is advisable. Then come the usual body parts:

• An introduction providing background information, target audience, and objectives;
• The qualitative research describes the participants in the research and why they are relevant to the business;
• The survey research outlines the questions asked and answered;
• A summary of the insights and metrics used to draw the conclusions, the research methods chosen, and why;
• A presentation of the findings based on your research and an in-depth explanation of these conclusions.
• Use a mix of visualizations:

When presenting your results and discoveries, you should aim to use a balanced mix of text, graphs, charts, and interactive visualizations.

Using your summary as a guide, you should decide which type of visualization will present each specific piece of market research data most effectively (often, the easier to understand and more accessible, the better).

Doing so will allow you to create a story that will put your research information into a living, breathing context, providing a level of insight you need to transform industry, competitor, or consumer info or feedback into actionable strategies and initiatives.

• Be careful not to mislead 

Expanding on the point above, using a mix of visuals can prove highly valuable in presenting your results in an engaging and understandable way. That being said, when not used correctly, graphs and charts can also become misleading. This is a popular practice in the media, news, and politics, where designers tweak the visuals to manipulate the masses into believing a certain conclusion. This is a very unethical practice that can also happen by mistake when you don’t pick the right chart or are not using it in the correct way. Therefore, it is important to outline the message you are trying to convey and pick the chart type that will best suit those needs. 

Additionally, you should also be careful with the data you choose to display, as it can also become misleading. This can happen if you, for example, cherry-pick data, which means only showing insights that prove a conclusion instead of the bigger picture. Or confusing correlation with causation, which means assuming that because two events happened simultaneously, one caused the other. 

Being aware of these practices is of utmost importance as objectivity is crucial when it comes to dealing with data analytics, especially if you are presenting results to clients. Our guides on misleading statistics and misleading data visualizations can help you learn more about this important topic. 

• Use professional dashboards:

To optimize your market research discoveries, you must work with a dynamic business dashboard . Not only are modern dashboards presentable and customizable, but they will offer you past, predictive, and real-time insights that are accurate, interactive, and yield long-lasting results.

All market research reports companies or businesses gathering industry or consumer-based information will benefit from professional dashboards, as they offer a highly powerful means of presenting your data in a way everyone can understand. And when that happens, everyone wins.

Did you know? The interactive nature of modern dashboards like datapine also offers the ability to quickly filter specific pockets of information with ease, offering swift access to invaluable insights.

• Prioritize interactivity 

The times when reports were static are long gone. Today, to extract the maximum value out of your research data, you need to be able to explore the information and answer any critical questions that arise during the presentation of results. To do so, modern reporting tools provide multiple interactivity features to help you bring your research results to life. 

For instance, a drill-down filter lets you go into lower levels of hierarchical data without generating another graph. For example, imagine you surveyed customers from 10 different countries. In your report, you have a chart displaying the number of customers by country, but you want to analyze a specific country in detail. A drill down filter would enable you to click on a specific country and display data by city on that same chart. Even better, a global filter would allow you to filter the entire report to show only results for that specific country. 

Through the use of interactive filters, such as the one we just mentioned, you’ll not only make the presentation of results more efficient and profound, but you’ll also avoid generating pages-long reports to display static results. All your information will be displayed in a single interactive page that can be filtered and explored upon need.  

• Customize the reports 

This is a tip that is valuable for any kind of research report, especially when it comes to agencies that are reporting to external clients. Customizing the report to match your client’s colors, logo, font, and overall branding will help them grasp the data better, thanks to a familiar environment. This is an invaluable tip as often your audience will not feel comfortable dealing with data and might find it hard to understand or intimidating. Therefore, providing a familiar look that is also interactive and easier to understand will keep them engaged and collaborative throughout the process. 

Plus, customizing the overall appearance of the report will also make your agency look more professional, adding extra value to your service. 

• Know your design essentials 

When you’re presenting your market research reports sample to internal or external stakeholders, having a firm grasp on fundamental design principles will make your metrics and insights far more persuasive and compelling.

By arranging your metrics in a balanced and logical format, you can guide users toward key pockets of information exactly when needed. In turn, this will improve decision-making and navigation, making your reports as impactful as possible.

For essential tips, read our 23 dashboard design principles & best practices to enhance your analytics process.

• Think of security and privacy 

Cyberattacks are increasing at a concerning pace, making security a huge priority for organizations of all sizes today. The costs of having your sensitive information leaked are not only financial but also reputational, as customers might not trust you again if their data ends up in the wrong hands. Given that market research analysis is often performed by agencies that handle data from clients, security and privacy should be a top priority.  

To ensure the required security and privacy, it is necessary to invest in the right tools to present your research results. For instance, tools such as datapine offer enterprise-level security protocols that ensure your information is encrypted and protected at all times. Plus, the tool also offers additional security features, such as being able to share your reports through a password-protected URL or to set viewer rights to ensure only the right people can access and manipulate the data. 

• Keep on improving & evolving

Each time you gather or gain new marketing research reports or market research analysis report intel, you should aim to refine your existing dashboards to reflect the ever-changing landscape around you.

If you update your reports and dashboards according to the new research you conduct and new insights you connect with, you will squeeze maximum value from your metrics, enjoying consistent development in the process.

Types of Market Research Reports: Primary & Secondary Research

With so many market research examples and such little time, knowing how to best present your insights under pressure can prove tricky.

To squeeze every last drop of value from your market research efforts and empower everyone with access to the right information, you should arrange your information into two main groups: primary research and secondary research.

A. Primary research

Primary research is based on acquiring direct or first-hand information related to your industry or sector and the customers linked to it.

Exploratory primary research is an initial form of information collection where your team might set out to identify potential issues, opportunities, and pain points related to your business or industry. This type of research is usually carried out in the form of general surveys or open-ended consumer Q&As, which nowadays are often performed online rather than offline . 

Specific primary research is definitive, with information gathered based on the issues, information, opportunities, or pain points your business has already uncovered. When doing this kind of research, you can drill down into a specific segment of your customers and seek answers to the opportunities, issues, or pain points in question.

When you’re conducting primary research to feed into your market research reporting efforts, it’s important to find reliable information sources. The most effective primary research sources include:

• Consumer-based statistical data
• Social media content
• Polls and Q&A
• Trend-based insights
• Competitor research
• First-hand interviews

B. Secondary research

Secondary research refers to every strand of relevant data or public records you have to gain a deeper insight into your market and target consumers. These sources include trend reports, market stats, industry-centric content, and sales insights you have at your disposal.  Secondary research is an effective way of gathering valuable intelligence about your competitors. 

You can gather very precise, insightful secondary market research insights from:

• Public records and resources like Census data, governmental reports, or labor stats
• Commercial resources like Gartner, Statista, or Forrester
• Articles, documentaries, and interview transcripts

Another essential branch of both primary and secondary research is internal intelligence. When it comes to efficient market research reporting examples that will benefit your organization, looking inward is a powerful move. 

Existing sales, demographic, or marketing performance insights will lead you to valuable conclusions. Curating internal information will ensure your market research discoveries are well-rounded while helping you connect with the information that will ultimately give you a panoramic view of your target market. 

By understanding both types of research and how they can offer value to your business, you can carefully choose the right informational sources, gather a wide range of intelligence related to your specific niche, and, ultimately, choose the right market research report sample for your specific needs.

If you tailor your market research report format to the type of research you conduct, you will present your visualizations in a way that provides the right people with the right insights, rather than throwing bundles of facts and figures on the wall, hoping that some of them stick.

Taking ample time to explore a range of primary and secondary sources will give your discoveries genuine context. By doing so, you will have a wealth of actionable consumer and competitor insights at your disposal at every stage of your organization’s development (a priceless weapon in an increasingly competitive digital age). 

Dynamic market research is the cornerstone of business development, and a dashboard builder is the vessel that brings these all-important insights to life. Once you get into that mindset, you will ensure that your research results always deliver maximum value.

Common Challenges & Mistakes Of Market Research Reporting & Analysis

We’ve explored different types of market research analysis examples and considered how to conduct effective research. Now, it’s time to look at the key mistakes of market research reporting.  Let’s start with the mistakes.

The mistakes

One of the biggest mistakes that stunt the success of a company’s market research efforts is strategy. Without taking the time to gather an adequate mix of insights from various sources and define your key aims or goals, your processes will become disjointed. You will also suffer from a severe lack of organizational vision.

For your market research-centric strategy to work, everyone within the company must be on the same page. Your core aims and objectives must align throughout the business, and everyone must be clear on their specific role. If you try to craft a collaborative strategy and decide on your informational sources from the very start of your journey, your strategy will deliver true growth and intelligence.

• Measurement

Another classic market research mistake is measurement – or, more accurately, a lack of precise measurement. When embarking on market intelligence gathering processes, many companies fail to select the right KPIs and set the correct benchmarks for the task at hand. Without clearly defined goals, many organizations end up with a market analysis report format that offers little or no value in terms of decision-making or market insights.

To drive growth with your market research efforts, you must set clearly defined KPIs that align with your specific goals, aims, and desired outcomes.

• Competition

A common mistake among many new or scaling companies is failing to explore and examine the competition. This will leave you with gaping informational blindspots. To truly benefit from market research, you must gather valuable nuggets of information from every key source available. Rather than solely looking at your consumers and the wider market (which is incredibly important), you should take the time to see what approach your direct competitors have adopted while getting to grips with the content and communications.

One of the most effective ways of doing so (and avoiding such a monumental market research mistake) is by signing up for your competitors’ mailing lists, downloading their apps, and examining their social media content. This will give you inspiration for your own efforts while allowing you to exploit any gaps in the market that your competitors are failing to fill.

The challenges

• Informational quality

We may have an almost infinite wealth of informational insights at our fingertips, but when it comes to market research, knowing which information to trust can prove an uphill struggle.

When working with metrics, many companies risk connecting with inaccurate insights or leading to a fruitless informational rabbit hole, wasting valuable time and resources in the process. To avoid such a mishap, working with a trusted modern market research and analysis sample is the only way forward.

• Senior buy-in

Another pressing market research challenge that stunts organizational growth is the simple case of senior buy-in. While almost every senior decision-maker knows that market research is an essential component of a successful commercial strategy, many are reluctant to invest an ample amount of time or money in the pursuit.

The best way to overcome such a challenge is by building a case that defines exactly how your market research strategies will offer a healthy ROI to every key aspect of the organization, from marketing and sales to customer experience (CX) and beyond.

• Response rates

Low interview, focus group, or poll response rates can have a serious impact on the success and value of your market research strategy. Even with adequate senior buy-in, you can’t always guarantee that you will get enough responses from early-round interviews or poll requests. If you don’t, your market research discoveries run the risk of being shallow or offering little in the way of actionable insight.

To overcome this common challenge, you can improve the incentive you offer your market research prospects while networking across various platforms to discover new contact opportunities. Changing the tone of voice of your ads or emails will also help boost your consumer or client response rates.

Bringing Your Reports a Step Further

Even if it is still widespread for market-style research results presentation, using PowerPoint at this stage is a hassle and presents many downsides and complications. When busy managers or short-on-time top executives grab a report, they want a quick overview that gives them an idea of the results and the big picture that addresses the objectives: they need a dashboard. This can be applied to all areas of a business that need fast and interactive data visualizations to support their decision-making.

We all know that a picture conveys more information than simple text or figures, so managing to bring it all together on an actionable dashboard will convey your message more efficiently. Besides, market research dashboards have the incredible advantage of always being up-to-date since they work with real-time insights: the synchronization/updating nightmare of dozens of PowerPoint slides doesn’t exist for you anymore. This is particularly helpful for tracking studies performed over time that recurrently need their data to be updated with more recent ones.

In today’s fast-paced business environment, companies must identify and grab new opportunities as they arise while staying away from threats and adapting quickly. In order to always be a step further and make the right decisions, it is critical to perform market research studies to get the information needed and make important decisions with confidence.

We’ve asked the question, “What is a market research report?”, and examined the dynamics of a modern market research report example, and one thing’s for sure: a visual market research report is the best way to understand your customer and thus increase their satisfaction by meeting their expectations head-on. 

From looking at a sample of a market research report, it’s also clear that modern dashboards help you see what is influencing your business with clarity, understand where your brand is situated in the market, and gauge the temperature of your niche or industry before a product or service launch. Once all the studies are done, you must present them efficiently to ensure everyone in the business can make the right decisions that result in real progress. Market research reports are your key allies in the matter.

To start presenting your results with efficient, interactive, dynamic research reports and win on tomorrow’s commercial battlefield, try our dashboard reporting software and test every feature with our 14-day free trial !

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Charts that Speak: Market Research Report Examples Explored

A Market Research Report Example serves as a pivotal tool for businesses aiming to understand market dynamics and make informed decisions.

A fast-growing fashion retailer, XYZ Inc., desires to enter the US market. They are curious whether the US market will accept their product line. They opt to compile a market research report to find out.

They use surveys, interviews, focus groups, and other data sources to compile the report’s qualitative and quantitative data. The report is then analyzed to get an understanding of the US market.

XYZ Inc. determines after evaluating the data that the US market is ready for its product line. This information enables them to join the US market successfully.

A market research report is a crucial resource for your business. You can tweak your strategies for greater success from the insights it offers.

In this blog post, we’ll discuss what a market research report is and why it’s important. We will also use a market research report example to learn how to present it.

Table of Contents:

What is a market research report, how to collect market research data, types of market research reports with examples, top 3 market research report examples.

• Presenting Market Research Results
• Importance of Marketing Research Report

A market research report documents the results of a market research project. It contains useful data and analysis about a given market. You can use it in guiding strategic marketing and new product development.

You can also use market research reports for a variety of purposes, such as determining needs and preferences as well as spotting market opportunities.

Typically, Market Research Report Examples encompass details such as:

• Target audience characteristics.
• Market size.
• Market potential.
• Competition analysis.

A crucial step in creating a market research report is data collection. Surveys, focus groups, interviews, and observational studies are some of the methods you can use.

When collecting market research information, it is advisable to utilize data from a representative sample of the target market. The accuracy of insights into the market is greatly enhanced through the use of this representative sampling, making Market Research Report Examples more valuable.

Here are some common types of market research reports:

1. Topline Market Research Report

Market Research Report Examples streamline the processes of data analysis and research interpretation, providing businesses with a simplified understanding. Topline market research reports provide a comprehensive summary of the research findings. They present the crucial insights and data points from the study.

This report contains market size, demographic details, consumer habits, and competitor analysis.

It simplifies the data analysis and research interpretation processes for businesses.

Business decisions, such as product development and marketing strategy, rely on the insights provided by these reports.

In addition, they help with communication with investors and other stakeholders.

2. Full Market Research Report

A full market research report investigates the current market landscape, trends, and opportunities. Furthermore, it highlights promising future developments and key growth areas.

It also offers information on major participants in the sector.

The report might also include information about government regulations and distribution methods.

Ultimately, a full market research report provides a thorough market analysis. Therefore it is a valuable resource for businesses looking to gain a competitive edge.

3. Product Detail Market Research Report

This is an exhaustive analysis of a product or service’s potential in the market. Features, benefits, target audience, competitors, and pricing are all spelled out here.

This report helps with understanding the market’s state and the possibilities for expansion. In addition, it shows how your business can differentiate itself from rivals.

You can also use it to measure the success of a product and adjust where necessary.

Presenting marketing research data can be a daunting task. Luckily, ChartExpo exists to aid in the creation of appealing and understandable data visualizations.

You can communicate marketing research findings effectively with charts and graphs. They simplify the presentation of complex data.

Here are a few examples of Market Research reports you can use to present your marketing results.

Market Research Report Example # 1: Customer Feedback Report

Customer Feedback Report is one of the best examples of Market Research Report. You can easily create this report using a CSAT Score Bar Chart.

A CSAT Score Bar Chart is a special graph plotting the CSAT scores against the number of records. It works well for presenting market research data. Viewers can digest crucial information like customer satisfaction rates in a snap.

The chart has two axes, one displaying the CSAT score for each metric. The other axis shows the corresponding number of customers or respondents.

CSAT Score Bar Chart enables you to compare customer feedback on various metrics. For instance, you can compare feedback on delivery and feedback on customer service. Finding out where you’re succeeding and where you’re falling short of customers’ expectations is a huge benefit.

Here is a marketing research example visualized in a CSAT Score Bar Chart.

Market Research Report Example # 2: Customer Satisfaction Report

Customer Satisfaction Report is one of the best examples of Market Research Report. You can easily create this report using a Customer Satisfaction Chart.

The Customer Satisfaction Chart is one of the most valuable marketing tools. It presents market research data in an understandable format. Therefore, it is helpful when developing an effective marketing strategy.

The Customer Satisfaction Chart is a versatile tool for presenting market research data. For instance, you can see how various products or services compare in client satisfaction. Thus you can find the most sought-after products or services by consumers.

You can also use it to monitor satisfaction levels over time. This can reveal any shifts in how satisfied customers are with your business.

The graphic also allows you to assess how satisfied certain groups of customers are. As a result, it helps identify the most important subsets of customers to focus on in your marketing.

Below is a market research report example presented in a Customer Satisfaction Chart.

Market Research Report Example # 3: Product Analysis Report

Product Analysis Report is one of the best examples of Market Research Report. You can easily create this report using a Likert Scale Chart.

The Likert Scale Chart is an effective tool for presenting market research data. Researchers use it to study how people think and act. It displays how strongly respondents agree or disagree with a statement or question.

Options lie on a scale ranging from “strongly agree” to “strongly disagree.” The scale aids in eliminating ambiguity in the responses and easing interpretation.

In addition to its simplicity, the Likert Scale Chart is also easy to read. Furthermore, you can alter it to meet the specific requirements of the study. For instance, you can alter the number of points to allow for more nuanced responses. Or else you can change the labels to match the survey’s language.

Enjoy the visualization below of a marketing research report example in a Likert Scale Chart.

Presenting Market Research Report with Example

Using ChartExpo, you can effectively display your marketing research data. You can quickly create stunning charts and graphs. Therefore, you can communicate your data with ease to your audience.

It has a variety of visualizations you can create to make your data outstanding and interesting.

You can modify the charts in ChartExpo to meet your specific needs in several ways. With its intuitive design controls, you can customize your data presentation to convey the right message.

How to Install ChartExpo in Excel?

• Open your Excel application.
• Open the worksheet and click on the “ Insert ” menu.
• You’ll see the “ My Apps ”.
• In office Add-ins window, click on “ Store ” and search for ChartExpo on my Apps Store.
• Click on “ Add ” button to install ChartExpo in your Excel.

ChartExpo charts and graphs are available both in Google Sheets and Microsoft Excel. Please use the following CTA’s to install the tool of your choice and create beautiful visualizations in a few clicks in your favorite tool.

Market Research Report Example with Data:

Let’s use the marketing report example below to learn how to create one in Excel.

Suppose you need feedback from your customers to improve your products. You create a questionnaire with a scale of 1 to 5 and conduct a survey.

• 1 = Strongly Disagree
• 2 = Disagree
• 3 = Neutral
• 5 = Strongly Agree

Let’s say you get the data tabulated below.

• To get started with ChartExpo, install ChartExpo in Excel .
• Now Click on My Apps from the INSERT menu.

• Choose ChartExpo from My Apps , then click Insert.

• Once ChartExpo is loaded. Click on “ Likert Scale Chart ” from the list of charts.

• Click “ Create Chart From Selection ” button after selecting the data from the sheet, as shown.

• The Likert Scale Chart will look like as follows.

• If you want to have the title of chart, click on Edit Chart , as shown in the above image.
• To change the title of the chart, click on the pencil icon that is available very next to Chart Header .
• It will open the properties dialog. Under the Text section, you can add a heading in Line 1 and enable the Show Give the appropriate title of your chart and click on Apply button.
• For saving changes click on Save Changes . This will persist the changes.

• The final chart will look as follows.

• 71% of respondents were content with the product’s reliability, while 13% expressed dissatisfaction.
• 59% said they found the product easy to use, and 22% had difficulty.
• 66% were satisfied with the speed of delivery, while 16% disagreed.
• Altogether, 65% of respondents said they were pleased with the product.

Why Do You Need Market Research Reports?

Market Research Reports play a crucial role in strategic decision-making and business planning. Here are various reasons that underscore their importance:

Gain Insights into the Industry

You can get comprehensive insights into the market, including its trends and challenges. This is essential for a business that wants to maximize its potential. You can use this data to study your rivals’ strategies and find market gaps. Consequently, you learn how your goods and services might better serve your clients’ demands.

A Holistic View of the Market

A marketing research report will give you a comprehensive understanding of the market. This covers its present situation, difficulties, and opportunities.

Understanding your current and potential customers’ motives, actions, and preferences will help you improve your services.

Decision-Making

Marketing research reports inform wise and data-driven marketing decisions. This boosts your chances of succeeding. You can also use it to determine the best marketing strategies to use.

Enhancing Credibility and Reputation

This report will give you the information you need to build a credible brand image. It will allow you to highlight your strengths, distinctive selling propositions, and appealing qualities.

Consequently, you can develop a brand identity that resonates with your target market.

Strategic Planning

You can gain knowledge about the future of your sector via a marketing research report. You can use this information to inform your judgments and stay abreast of the times. It can also aid in your preparation for potential challenges and developments in the market.

What is a market research report?

A market research report presents an in-depth examination of a selected market. It highlights the state of the market, opportunities, trends, or challenges currently available. It also sheds light on customers’ likes and dislikes and how they might change.

What’s included in a market research report?

Typically, it has an in-depth analysis of the target market. It dissects market segmentation, price strategy, and promotional approaches. Also, it includes elements that help you make informed decisions on your offerings and promotional strategies.

How can I use market research reports in decision-making?

It contains detailed assessments of the state of the market and its prospects. Market research reports are a valuable resource due to their wealth of information. You can identify opportunities and make better strategy and management decisions from their insights.

How can Excel help in the analysis of market research data?

Excel is capable of quickly analyzing massive volumes of data. This enables for in-depth analysis of trends and patterns. It offers a variety of functions and visual representations for examining this data.

Can you provide a sample Market Research Report example for a specific industry?

This question seeks to obtain a practical illustration, allowing users to understand how a market research report is structured and presented in a real-world context.

How can a Market Research Report example benefit my business decision-making process?

This question delves into the practical advantages of utilizing market research report examples, emphasizing the impact on informed decision-making and strategic planning within a business context.

Market Research Report Examples offer a comprehensive overview of the entire industry, enabling businesses to make well-informed marketing and strategic decisions. Conducting market research is an essential part of any business. It helps cultivate a stronger reputation and boosts brand loyalty among its customers.

You can get a bird’s-eye view of the entire industry with a market research report. You can use this information to make informed marketing and business choices. As a result, it aids in enhancing credibility.

You can get the advantage you need over the competition with the help of market research reports. You can use the data to fine-tune your campaigns and zero in on expansion opportunities.

But how do you create a marketing research report?

You use Excel and ChartExpo to create appealing visualizations for your market research data. As we have shown with the marketing report example above.

You can create an insightful report and present it to your stakeholders in a few clicks

How much did you enjoy this article?

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• Knowledge Base

Methodology

• Data Collection | Definition, Methods & Examples

Data Collection | Definition, Methods & Examples

Published on June 5, 2020 by Pritha Bhandari . Revised on June 21, 2023.

Data collection is a systematic process of gathering observations or measurements. Whether you are performing research for business, governmental or academic purposes, data collection allows you to gain first-hand knowledge and original insights into your research problem .

While methods and aims may differ between fields, the overall process of data collection remains largely the same. Before you begin collecting data, you need to consider:

• The  aim of the research
• The type of data that you will collect
• The methods and procedures you will use to collect, store, and process the data

To collect high-quality data that is relevant to your purposes, follow these four steps.

Table of contents

Step 1: define the aim of your research, step 2: choose your data collection method, step 3: plan your data collection procedures, step 4: collect the data, other interesting articles, frequently asked questions about data collection.

Before you start the process of data collection, you need to identify exactly what you want to achieve. You can start by writing a problem statement : what is the practical or scientific issue that you want to address and why does it matter?

Next, formulate one or more research questions that precisely define what you want to find out. Depending on your research questions, you might need to collect quantitative or qualitative data :

• Quantitative data is expressed in numbers and graphs and is analyzed through statistical methods .
• Qualitative data is expressed in words and analyzed through interpretations and categorizations.

If your aim is to test a hypothesis , measure something precisely, or gain large-scale statistical insights, collect quantitative data. If your aim is to explore ideas, understand experiences, or gain detailed insights into a specific context, collect qualitative data. If you have several aims, you can use a mixed methods approach that collects both types of data.

• Your first aim is to assess whether there are significant differences in perceptions of managers across different departments and office locations.
• Your second aim is to gather meaningful feedback from employees to explore new ideas for how managers can improve.

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Based on the data you want to collect, decide which method is best suited for your research.

• Experimental research is primarily a quantitative method.
• Interviews , focus groups , and ethnographies are qualitative methods.
• Surveys , observations, archival research and secondary data collection can be quantitative or qualitative methods.

Carefully consider what method you will use to gather data that helps you directly answer your research questions.

When you know which method(s) you are using, you need to plan exactly how you will implement them. What procedures will you follow to make accurate observations or measurements of the variables you are interested in?

For instance, if you’re conducting surveys or interviews, decide what form the questions will take; if you’re conducting an experiment, make decisions about your experimental design (e.g., determine inclusion and exclusion criteria ).

Operationalization

Sometimes your variables can be measured directly: for example, you can collect data on the average age of employees simply by asking for dates of birth. However, often you’ll be interested in collecting data on more abstract concepts or variables that can’t be directly observed.

Operationalization means turning abstract conceptual ideas into measurable observations. When planning how you will collect data, you need to translate the conceptual definition of what you want to study into the operational definition of what you will actually measure.

• You ask managers to rate their own leadership skills on 5-point scales assessing the ability to delegate, decisiveness and dependability.
• You ask their direct employees to provide anonymous feedback on the managers regarding the same topics.

You may need to develop a sampling plan to obtain data systematically. This involves defining a population , the group you want to draw conclusions about, and a sample, the group you will actually collect data from.

Your sampling method will determine how you recruit participants or obtain measurements for your study. To decide on a sampling method you will need to consider factors like the required sample size, accessibility of the sample, and timeframe of the data collection.

Standardizing procedures

If multiple researchers are involved, write a detailed manual to standardize data collection procedures in your study.

This means laying out specific step-by-step instructions so that everyone in your research team collects data in a consistent way – for example, by conducting experiments under the same conditions and using objective criteria to record and categorize observations. This helps you avoid common research biases like omitted variable bias or information bias .

This helps ensure the reliability of your data, and you can also use it to replicate the study in the future.

Creating a data management plan

Before beginning data collection, you should also decide how you will organize and store your data.

• If you are collecting data from people, you will likely need to anonymize and safeguard the data to prevent leaks of sensitive information (e.g. names or identity numbers).
• If you are collecting data via interviews or pencil-and-paper formats, you will need to perform transcriptions or data entry in systematic ways to minimize distortion.
• You can prevent loss of data by having an organization system that is routinely backed up.

Finally, you can implement your chosen methods to measure or observe the variables you are interested in.

The closed-ended questions ask participants to rate their manager’s leadership skills on scales from 1–5. The data produced is numerical and can be statistically analyzed for averages and patterns.

To ensure that high quality data is recorded in a systematic way, here are some best practices:

• Record all relevant information as and when you obtain data. For example, note down whether or how lab equipment is recalibrated during an experimental study.
• Double-check manual data entry for errors.
• If you collect quantitative data, you can assess the reliability and validity to get an indication of your data quality.

Prevent plagiarism. Run a free check.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Likert scale

Research bias

• Implicit bias
• Framing effect
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
• You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

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Writing a market research report is a tough skill to master. Read our 5 top tips to get you started for writing a successful market research report.

While data collection and results analysis can be highly in-depth and time-consuming processes to complete, they still only mark the beginning of your market research project. The next step is writing a market research report, which is a tough skill to master. The report must effectively communicate your research findings such as consumer trends, market trends, and competitor behaviour surrounding your target audience .

A market research report is a summary of research findings and insights uncovered during the data collection and analysis processes. Research reports usually contain information about a company’s competition, industry trends/opportunities, and recommendations for next steps based on the research questions being addressed.

A good research report helps guide decision-making and highlight market opportunities. You should be clear and concise but also detailed and comprehensive, keeping in mind that stakeholders must be able to interpret your findings with ease. This is no easy task, which is why we have listed our 5 top tips to get you started for writing a successful market research report.

Use language stakeholders can understand

Your market research report will be presented to many stakeholders, not all of which will have a strong understanding of market research terms, so it is important that you write in clear, simple language.

Do not assume stakeholders will understand without explanation, for example, all diagrams should be clearly labelled and accurately describe what they are displaying. It is helpful to imagine you are writing the research report for a reader who has no prior knowledge on the topic to ensure you are explaining your findings comprehensively.

Report on insights through storytelling

Writing a seamless research report is not only easier to read but also ensures you have covered all necessary elements. Work chronologically to unpack your research — What is it about? What did you discover? What should you do next? Your research report should build upon your “story” the further it reads and further support your final recommendations .

Share insights through visual reporting

Visual elements such as diagrams and charts deliver numerical information more clearly than writing. They also help to break up text and keep the reader engaged with the research report and can be easily referenced during presentations. Similarly, images and icons can be used to draw attention to certain findings and make formatting more presentable.

Turn data into actionable insights

Data is meaningless to stakeholders unless it is interpreted and presented with a set of actions or “next steps”. Your goal is to explain how the data you have collected can drive smart business decisions and why these decisions are the best course of action. Outline step-by-step connections to ensure all readers can clearly understand the relationship between data and action.

Avoid vague reporting

It is important to keep your research report brief, including only the most substantial points you want to communicate. All reporting must be supplemented with firm evidence and written in an assertive tone to convey certainty of your findings. Keep recommendations clear and concise, without straying too far from your main points — writing that goes off on tangents can distract from your main points.

Read these articles next:

Ux testing vs. market research for evaluating software.

UX testing is widely used in software development, while market research remains underutilised. This article compares these approaches and discusses how to use both for the best results.

Can you make perceptual maps from fake data? (A replication study)

This study investigates the claim that synthetic LLM-generated data could be used effectively for creating perceptual maps in market research contexts.

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What is a Marketing Research Report and How to Write It?

Table of contents

There is nothing more embarrassing for a marketer than to hear a client say “…this doesn’t quite address the business questions that we need to answer.” And unfortunately, this is a rather common occurrence in market research reporting that most marketers would care to admit.

So, why do most market research reports fail to meet client expectations? Well, in most cases, because there is more emphasis on methodology and analytic techniques used to craft the report rather than relying on data visualization, creative story-telling, and outlining actionable direction/steps.

Now, our next big question is, how do you avoid your client’s dreaded deer-in-the-headlights reaction when presenting such a report? This blog post will answer this and much more, as we go through the following:

What Is a Market Research Report?

Why is market research important, differences between primary and secondary market research, types of market research, market research reports advantages and disadvantages, how to do market research, how to prepare a market research report: 5 steps, marketing research report templates, marketing research reports best practices, bring your market research reports a step further with databox.

The purpose of creating a market research report is to make calculated decisions about business ideas. Market research is done to evaluate the feasibility of a new product or service, through research conducted with potential consumers. The information obtained from conducting market research is then documented in a formal report that should contain the following details:

• The characteristics of your ideal customers
• You customers buying habits
• The value your product or service can bring to those customers
• A list of your top competitors

Every business aims to provide the best possible product or service at the lowest cost possible. Simply said, market research is important because it helps you understand your customers and determine whether the product or service that you are about to launch is worth the effort.

Here is an example of a customer complaint that may result in more detailed market research:

Suppose you sell widgets, and you want your widget business to succeed over the long term. Over the years, you have developed many different ways of making widgets. But a couple of years ago, a customer complained that your widgets were made of a cheap kind of foam that fell apart after six months. You didn’t think at the time that this was a major problem, but now you know it.

The customer is someone you really want to keep. So, you decide to research this complaint. You set up a focus group of people who use widgets and ask them what they think about the specific problem. After the conducted survey you’ll get a better picture of customer opinions, so you can either decide to make the changes regarding widget design or just let it go.

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• New Contacts from Sessions . How well is your campaign driving new contacts and customers?
• Marketing Performance KPIs . Tracking the number of MQLs, SQLs, New Contacts and similar will help you identify how your marketing efforts contribute to sales.
• Email Performance . Measure the success of your email campaigns from HubSpot. Keep an eye on your most important email marketing metrics such as number of sent emails, number of opened emails, open rate, email click-through rate, and more.
• Blog Posts and Landing Pages . How many people have viewed your blog recently? How well are your landing pages performing?

Now you can benefit from the experience of our Google Analytics and HubSpot Marketing experts, who have put together a plug-and-play Databox template that contains all the essential metrics for monitoring your leads. It’s simple to implement and start using as a standalone dashboard or in marketing reports, and best of all, it’s free!

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To set up the dashboard, follow these 3 simple steps:

Step 1: Get the template 

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Marketing research requires both primary and secondary market research. But what does that mean and what are the main differences?

Primary market research takes in information directly from customers, usually as participants in surveys. Usually, it is consisted of:

• Exploratory Primary Research – This type of research helps to identify possible problem areas, and it’s not focused on discovering specific information about customers. As with any research, exploratory primary research should be conducted carefully. Researchers need to craft an interviewing or surveying plan, and gather enough respondents to ensure reasonable levels of statistical reliability.
• Specific Primary Research – This type of research is one of the best ways to approach a problem because it relies on existing customer data. Specific research provides a deeper, more thorough understanding of the problem and its potential solutions. The greatest advantage of specific research is that it lets you explore a very specific question, and focus on a specific problem or an opportunity.

Secondary market research collects information from other sources such as databases, trend reports, market or government statistics, industry content, etc. We can divide secondary market research into 3 categories:

• Public market data – Public sources range from academic journals and government reports to tax returns and court documents. These sources aren’t always easy to find. Many are available only in print in libraries and archives. You have to look beyond search engines like Google to find public source documents.
• Commercial data – Those are typically created by specialized agencies like Pew, Gartner or Forrester. the research agencies are quite expensive, but they provide a lot of useful information.
• Internal data – Your organization’s databases are gold mines for market research. In the best cases, your salespeople can tell you what they think about customers. Your salespeople are your direct sources of information about the market. Don’t underestimate your internal data.

In general, primary research is more reliable than secondary research, because researchers have to interview people directly. But primary research is expensive and time-consuming. Secondary research can be quicker and less expensive.

There are plenty of ways to conduct marketing research reports. Mostly, the type of research done will depend on your goals. Here are some types of market research often conducted by marketers.

Focus Groups

Product/service use research, observation-based research, buyer persona research, market segmentation research, pricing research, competitive analysis research, customer satisfaction and loyalty research, brand awareness research, campaign research.

An interview is an interactive process of asking and answering questions and observing your respondent’s responses. Interviews are one of the most commonly used tools in market research . An interview allows an organization to observe, in detail, how its consumers interact with its products and services. It also allows an organization to address specific questions.

A focus group is a group of people who get together to discuss a particular topic. A moderator leads the discussion and takes notes. The main benefit of focus groups is that they are quick and easy to conduct. You can gather a group of carefully-selected people, give them a product to try out, and get their feedback within a few hours/days.

Product or service use research helps you obtain useful information about your product or service such as:

• What your current customers do with the product/service
• Which features of the product/service are particularly important to your customers
• What they dislike about the product/service
• What they would change about the product/service

Observation-based research helps you to observe your target audience interacting with your product or service. You will see the interactions and which aspects work well and which could be improved. The main point is to directly experience the feedback from your target audience’s point of view.

Personas are an essential sales tool. By knowing your buyers’ pain points and the challenges they face, you can create better content, target messaging, and campaigns for them. Buyer persona research is based on market research, and it’s built around data that describes your customers’ demographics, behaviors, motivations, and concerns. Sales reporting software can significantly help you develop buyer personas when you gain insights after you collected all information.

Market segmentation research is carried out to better understand existing and potential market segments. The objective is to determine how to target different market segments and how they differ from each other. The three most important steps in writing a market segmentation research report are:

• Defining the problem
• Determining the solution [and]
• Defining the market

Related : 9 Customer Segmentation Tips to Personalize Ecommerce Marketing and Drive More Sales

A price that is too high, or too low, can kill a business. And without good market research, you don’t really know what is a good price for your product. Pricing research helps you define your pricing strategy.

In a competitive analysis, you define your “competition” as any other entity that competes with you in your market, whether you’re selling a widget or a piece of real estate. With competitive analysis research, you can find out things like:

• Who your competitors are
• What they’ve done in the past
• What’s working well for them
• Their weaknesses
• How they’re positioned in the market
• How they market themselves
• What they’re doing that you’re not

Related : How to Do an SEO Competitive Analysis: A Step-by-Step Guide

In today’s marketplace, companies are increasingly focused on customer loyalty. What your customers want is your product, but, more importantly, they want it delivered with a service that exceeds their expectations. Successful companies listen to their customers and respond accordingly. That’s why customer satisfaction and loyalty research is a critical component of that basic equation.

Related : 11 Tactics for Effectively Measuring Your Customer Service ROI

Who you are, what you stand for, what you offer, what you believe in, and what your audience thinks of you is all wrapped up in brand. Brand awareness research tells what your target audience knows about your brand and what’s their experience like.

A campaign research report is a detailed account of how your marketing campaign performed. It includes all the elements that went into creating the campaign: planning, implementation, and measurement.

Here are some of the top advantages and disadvantages of doing market research and crafting market research reports.

• Identify business opportunities – A market research report can be used to analyze potential markets and new products. It can give information about customer needs, preferences, and attitudes. Also, it compare products and services.
• A clear understanding of your customers – A market report gives company’s marketing department an in-depth picture about customers’ needs and wants. This knowledge can be used to improve products, prices, and advertising.
• Mitigates risks – 30% of small businesses fail within the first two years. Why is this so? The answer is that entrepreneurs are risk takers. However, there are risks that could be avoided. A good marketing research will help you identify those risks and allow you to mitigate them.
• Clear data-driven insights – Market research encompasses a wide range of activities, from determining market size and segment to forecasting demand, and from identifying competitors to monitoring pricing. All of these are quantified and measurable which means that gives you a clear path for building unique decisions based on numbers.

Disadvantages

• It’s not cheap – Although market research can be done for as little as $500, large markets like the United States can run into millions of dollars. If a research is done for a specific product, the budget may be even much higher. The budget also depends on the quality of the research. The more expensive it is, the more time the research will take.
• Some insights could be false – For example, if you are conducting a survey, data may be inadequate or inaccurate because respondents can, well, simply be dishonest and lie.

Here are the essential steps you need to take when doing market research:

Define your buyer persona

Identify a persona group to engage, prepare research questions for your market research participants, list your primary competitors, summarize your findings.

The job of a marketing persona is to describe your ideal customer and to tell you what they want, what motivates them, what frustrates them, and what limits them. Finding out these things means you have a better chance of designing your products, services, marketing messages, and brand around real customers. There is no one right way to create a buyer persona, though.

For example, if you’re in an industry focused on education, you could include things like:

• Educational level
• Education background

It’s recommended that you create 3-5 buyer personas for your products, based on your ideal customer.

This should be a representative sample of your target customers so you can better understand their behavior. You want to find people who fit both your target personas and who represent the broader demographic of your market. People who recently made a purchase or purposefully decided not to make one are a good sample to start with.

The questions you use determine the quality of your results. Of course, the quality of your results also depends on the quality of your participants.

Don’t ask questions that imply a yes or no answer. Instead, use open questions. For example, if you are researching customers about yogurt products, you could ask them: „ What have you heard about yogurt ?” or “ What do you think of yogurt ?“.

Avoid questions that use numbers, such as “ How many times a week do you eat yogurt ?”

Avoid questions that suggest a set of mutually exclusive answers, such as “ Do you like yogurt for breakfast, lunch, or dinner ?”

Avoid questions that imply a scale, such as “ Do you like chocolate-flavored yogurt ?”

Market researchers sometimes call one company the top competitor, another middle competitor, and the third one small competitor. However you classify them, you want to identify at least three companies in each category. Now, for each business on your list, list its key characteristics. For example, if your business sells running shoes, a key characteristic might be the product’s quality.

Next, make a list of your small business’s competitive advantages. These include the unique qualities or features of your business that make it the best choice of customers for the products or services it offers. Make a list of these competitive advantages and list them next to the key characteristics you listed for your business.

You have just finished writing your marketing research report. Everything is out there quantified or qualified. You just have to sum it up and focus on the most important details that are going to make a big impact on your decisions. Clear summary leads to a winning strategy!

Related : How to Prepare a Complete Marketing Report: The KPIs, Analysis, & Action Plan You Need

Here’s how to prepare a market research report in 5 simple steps:

Step 1: Cluster the data

Step 2: prepare an outline, step 3: mention the research methods, step 4: include visuals with narrative explanations, step 5: conclude the report with recommendations.

Your first step is to cluster all the available information into a manageable set. Clustering is the process of grouping information together in a way that emphasizes commonalities and minimizes differences. So, in market research, this will help to organize all the information you have about a product, service, or target market and identify your focus areas.

A marketing research report should be written so that other people can understand it:

• Include background information at the beginning to explain who your audience is and what problem you are trying to solve for them.
• In the body of the report, include a description of the methodology – Explain to the reader how your research was done, what was involved, and why you selected the methodology you used.
• Also in the body of the report, include the results of your market research. These may be quantitative or qualitative, but either way they should answer the questions you posed at the beginning.
• Include the executive summary – A summary of the entire report.

The market research methodology section includes details on the type of research, sample size, any limitations of the studies, research design, sample selection, data collection procedures, and statistical analyses used.

Visuals are an essential part of the presentation. Even the best-written text can be difficult to understand. Charts and graphs are easier to understand than text alone, and they help the reader see how the numbers fit the bigger picture.

But visuals are not the whole story. They are only one part of the presentation. Visuals are a cue for the reader. The narrative gives the story, not just the numbers.

Recommendations tend to follow logically from conclusions and are a response to a certain problem. The recommendation should always be relevant to the research rationale, that is, the recommendation should be based on the results of the research reported in the body of the report.

Now, let’s take a look at some dashboard reporting templates you could use to enhance your market research:

• Semrush (Position Tracking) Report

Brand Awareness Report

Sales pipeline performance report, customer success overview report, stripe (mrr & churn) report, semrush (position tracking) report template.

This free SEMRush dashboard template will help you monitor how your website’s search visibility on search engines evolves on a monthly basis. This dashboard contains all of the information you need to make changes and improve the ranking results of your business in Google Search.

This Brand Awareness Report will help you to get a sense of your brand awareness performance in Google Analytics, Google Organic Search, and Facebook. Use this dashboard to track brand awareness the same way you track other marketing campaigns.

Are your sales and marketing funnel healthy and growing? How is your sales and marketing funnel performing? What are the key conversion rates between your lifecycle stages? With a pipeline performance dashboard , you’ll get all of the answers quickly.

This Customer Success Overview Dashboard allows you to analyze how your customer service team’s responsiveness impacts your business. Use this dashboard to assess the correlation between your customer service performance and churn rate. 

This Stripe dashboard tracks your churn rate and MRR growth in real-time and shows you which customers (and how many of them) you have at any given point in time. All you have to do to get started is to connect your Stripe account.

As we said earlier, there are no strict rules when it comes to writing marketing research reports. On the other hand, you must find your focus if you want to write a report that will make a difference. Here are some best practices you should keep in mind when writing a research report.

• Objectives – The objective of a market research report is to define the problems, identify key issues, and suggest recommendations for further research. If you answer them successfully, you’re on the right way.
• Don’t worry about the format – Be creative. The report could be in a form of a PowerPoint presentation, Excel sheet, interactive dashboard or even a video. Use the format that best fits your audience, but make sure to make it easy to read.
• Include an executive summary, scorecard , or a dashboard – This is really important because time is money, and most people don’t have time to waste. So, how to put everything important in a short role? Address all of the objectives and put them in a graphic dashboard or scorecard. Also, you can write an executive summary template (heart of the report) that can be easily updated and read by managers or CEOs.
• Use storytelling –  A good story always makes a great point because it’s so memorable. Your research report results can double the effect with a catchy story.
• Keep it short – It’s not a secret that we are reading so little in the digital era. Use a lot of white space and bullet points. Too much text on a page means less focus for the reader.
• Be organized – Maintain the order of information. It’s important for the reader to navigate through the report easily. If they want to find some details or specific information it would be great to divide all sections with appropriate references.
• Methodological information – Methodological details could be boring. Include only the most important details that the reader needs to know to understand the big picture.
• Use images (or other visualizations) whenever you can – A good picture speaks for 1.000 words! If you can communicate the point visually, don’t hesitate to do it. It would be a lot easier for those who don’t like a lot of text to understand your results. But don’t push them where you can’t.
• Create readable graphs – The crown of marketing research reports is a comprehensive graph. Make sure to design precise and attractive graphs that will power up and round your story.
• Use the Appendix  – You can include all secondary information such as methodological details and other miscellaneous data in the Appendix at the end of the report.

Market research reports are all about presenting your data in an easy-to-understand way and making calculated decisions about business ideas. But this is something easier said than done.

When busy stakeholders and executives grab a report, they need something that will give them an idea of the results – the big picture that addresses company wide-business goals.

Can a PowerPoint presentation or a PDF report meet those expectations? Most likely not. But a dashboard can.

Keep in mind that even with the best market analysis in the world, your market research report won’t be actionable if you don’t present the data efficiently and in a way that everyone understands what the next steps are. Databox is your key ally in the matter.

Databox dashboards are designed to help you present your market research data with clarity – from identifying what is influencing your business, and understanding where your brand is situated in the market, to gauging the temperature of your niche or industry before a new product/service launch.

Present your research results with efficient, interactive dashboards now by signing up for a free trial .

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• 11 Effective data collection methods for market research

One of the most important ways to make money today is to use the benefits of the digital world at the maximum level. Collecting data is also one of the requirements of this digital world. To be successful, you need to have information and know how to use this information correctly. You may have different reasons for collecting data, but companies mainly use the data to identify potential customers and see customer feedback and satisfaction.

There are various data collection methods in accordance with your purpose and possibilities . The purpose and benefits of using each method vary. Some are more useful for learning the customer base , while others can be used for market research of the product or service you sell. In this blog post, we will discuss the purposes and uses of 11 data collection methods. 

• What is market research?

Market research involves deciding whether your new product or service is viable by contacting buyer personas directly. There are different ways to do market research, including market research surveys , product research surveys , and customer research surveys. When you prepare the survey questions to get information about the sector and the customer, you can get more precise results for your market research.

• 11 effective data collection methods for market research

Thanks to 11 different data collection methods, you can effectively research both your existing products and the products you are preparing to sell. After determining the target audiences , it is easier to prepare market research questionnaires. You can learn the purposes and usage areas of data collection methods and see customer feedback by reading the following in detail.

1 - Surveys

Surveys are one of the most preferred and effective methods of market research. The first reason why it is the most effective is that everyone can access it because there are online market surveys. In addition to paper surveys, you can reach more people via email, social media, and your website, thanks to online surveys. There are many different types of surveys, and you can collect data on various subjects. A few survey types are as follows:

• Customer satisfaction surveys : You can understand whether your customers are satisfied with your product or service after purchasing them and whether they have positive or negative opinions.
• Market research surveys : Market research surveys are used to understand all the characteristics of potential customers by asking demographic questions before product marketing. You can quickly create a survey with the marketing questionnaire templates in forms.app.
• Product research surveys : It is used to understand whether the product you are preparing for marketing has the potential to meet people's problems or expectations. 

Customer satisfaction and market research are the most effective survey types . They are necessary to get people's needs, expectations, and positive and negative opinions before marketing a product or service. Also, with the questions for Saas surveys , you can get suggestions and thoughts not only for products but also for applications. You can find online market research survey templates and customer satisfaction survey templates in forms.app.

A customer needs survey example

2 - Focus groups

Focus groups are also one of the data collection methods. In these groups, you gather more than one person in a room and ask them questions about a product or service. Everyone will have various opinions, as there will be people with different demographics. Thanks to the differences of opinion and brainstorming , you can get a lot of useful data. In addition, you can get better results for a certain strategy by asking them market research questions like in surveys.

Focus groups

3 - Observation

Observation is a data collection method where you try to learn the ideas of the participants by giving them a certain period of time. You prepare a lot of questions for the participants about your product or in the market area. Next, you should observe how the participant reacts . Both verbal and non-verbal reactions are very important because they take place in a natural setting. The observer should not interfere with anything other than conveying the questions.

Forms are one of the data collection information that has the same purpose as surveys . In addition to paper forms, there are online forms accessible to everyone. Especially thanks to online forms, you will speed up your research or data collection process . You can send online forms to everyone on your social media, website, or via e-mail. You will get much better results because you collect data from many people. With forms.app's many form templates; you can quickly create your own forms.

Online feedback form templates

5 - Lead quizzes

Lead quizzes are one of the important ways to collect data and gain potential customers. You can easily learn the tendency and ideas to buy your product or service through lead quizzes. You can easily prepare lead quizzes with forms.app, one of the online form builders. Online lead quizzes play a very important role in converting your potential customers into paying customers . Moreover, you can create your lead quizzes from interactive questions or personality quizzes to attract more target audiences.

A lead quiz example

6 - Secondary sources (Business reports, etc.)

Secondary sources are also one of the data collection methods that are generally used during market research. Instead of getting the information firsthand, you may prefer to benefit from the up-to-date data collected previously. To use this method, all you have to do is scan specific resources. Some of these resources are as follows:

• Government reports : With government reports, you can see people's income scale and spending habits. Thus, you can benefit from this information in accordance with your own business area.
• NGO resources : Non-government organizations also conduct continuous research on different subjects, such as government reports. As a result of these researches, you can access people's demographic information.
• Business reports : You can also use the reports of companies that conduct research in different fields. You can easily access various data about both the market and the customers.

7 - Online tracking

Online tracking is one of the data collection methods that clearly shows your customers' purchasing tendencies and interests . You can quickly track which product they look at the most, at what times they visit, and which product they like the most, thanks to the analysis. In light of this information, you can make various changes to the design of your website. You can also bring your products to the fore to increase the visitors' purchasing motivation.

Tracking customer metrics online

8 - Transactional tracking

Transactional tracking is a very similar method to online tracking. You can usually access transactional tracking results from e-commerce sites . You can easily follow the e-commerce sites that show how much of your product is sold or how much interest is in which product. With these results, you can make changes to your products. Additionally, customer survey statistics can be a handy tool here.

9 - Social media monitoring

Social media monitoring is a very useful data collection method if you have many followers on your social media accounts. Many social media platforms have their own analytics , and you can use them to find out which of your followers like the most. You can also see what your followers are clicking on, so you can easily find out what they like and what they are interested in.

10 - Questionnaire

Questionnaires are another popular data collection method. It is one of the easiest ways to get ideas, suggestions, and opinions on a subject you have determined. For example, you have an application, and with questionnaires, you can get opinions supporting your development, from how the application works to its interface. 

Using online questionnaires to collect data

11 - Interviews

Interviews are one of the last data collection methods. Interviews are helpful in getting opinions about marketing or purchasing trends as a result of face-to-face interviews with target audiences . Moreover, you can get feedback from people about the products of other competitors and develop your own products as a result of these opinions.

• Combining different data collection methods

You may not be able to decide which of these 11 data collection methods to use. All of them have various advantages and disadvantages. For this reason, using several different methods at the same time will bring you more precise results . 

Although interviews and focus groups are effective methods, it can take a long time to bring many people together. Since online surveys, forms and quizzes can reach more people, it is much more reasonable to use these methods. In addition, you can do market research quickly with the many free market survey templates in forms.app.

Collecting and gathering data on customer experience is very significant, especially for people interested in e-commerce. To sell your product, firstly, you should know your potential customers’ motivation and interests. To obtain this information, you have learned in this article what the critical 11 data collection methods are and what they do.

Online tracking, secondary sources, and surveys are crucial methods. Furthermore, You will also have ideas on how to create surveys thanks to the market research survey examples on forms.app. If you also need to collect data, you can quickly start collecting data using forms.app's ready-made forms on various topics!

Ebru is an Outreach Operations Specialist and content writer at forms.app. Writing is her passion, particularly on topics such as eCommerce, social media, customer engagement, surveys, and online forms. During her free time, Ebru enjoys watching movies and exploring new destinations.

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Home » Data Collection – Methods Types and Examples

Data Collection – Methods Types and Examples

Table of Contents

Data Collection

Definition:

Data collection is the process of gathering and collecting information from various sources to analyze and make informed decisions based on the data collected. This can involve various methods, such as surveys, interviews, experiments, and observation.

In order for data collection to be effective, it is important to have a clear understanding of what data is needed and what the purpose of the data collection is. This can involve identifying the population or sample being studied, determining the variables to be measured, and selecting appropriate methods for collecting and recording data.

Types of Data Collection

Types of Data Collection are as follows:

Primary Data Collection

Primary data collection is the process of gathering original and firsthand information directly from the source or target population. This type of data collection involves collecting data that has not been previously gathered, recorded, or published. Primary data can be collected through various methods such as surveys, interviews, observations, experiments, and focus groups. The data collected is usually specific to the research question or objective and can provide valuable insights that cannot be obtained from secondary data sources. Primary data collection is often used in market research, social research, and scientific research.

Secondary Data Collection

Secondary data collection is the process of gathering information from existing sources that have already been collected and analyzed by someone else, rather than conducting new research to collect primary data. Secondary data can be collected from various sources, such as published reports, books, journals, newspapers, websites, government publications, and other documents.

Qualitative Data Collection

Qualitative data collection is used to gather non-numerical data such as opinions, experiences, perceptions, and feelings, through techniques such as interviews, focus groups, observations, and document analysis. It seeks to understand the deeper meaning and context of a phenomenon or situation and is often used in social sciences, psychology, and humanities. Qualitative data collection methods allow for a more in-depth and holistic exploration of research questions and can provide rich and nuanced insights into human behavior and experiences.

Quantitative Data Collection

Quantitative data collection is a used to gather numerical data that can be analyzed using statistical methods. This data is typically collected through surveys, experiments, and other structured data collection methods. Quantitative data collection seeks to quantify and measure variables, such as behaviors, attitudes, and opinions, in a systematic and objective way. This data is often used to test hypotheses, identify patterns, and establish correlations between variables. Quantitative data collection methods allow for precise measurement and generalization of findings to a larger population. It is commonly used in fields such as economics, psychology, and natural sciences.

Data Collection Methods

Data Collection Methods are as follows:

Surveys involve asking questions to a sample of individuals or organizations to collect data. Surveys can be conducted in person, over the phone, or online.

Interviews involve a one-on-one conversation between the interviewer and the respondent. Interviews can be structured or unstructured and can be conducted in person or over the phone.

Focus Groups

Focus groups are group discussions that are moderated by a facilitator. Focus groups are used to collect qualitative data on a specific topic.

Observation

Observation involves watching and recording the behavior of people, objects, or events in their natural setting. Observation can be done overtly or covertly, depending on the research question.

Experiments

Experiments involve manipulating one or more variables and observing the effect on another variable. Experiments are commonly used in scientific research.

Case Studies

Case studies involve in-depth analysis of a single individual, organization, or event. Case studies are used to gain detailed information about a specific phenomenon.

Secondary Data Analysis

Secondary data analysis involves using existing data that was collected for another purpose. Secondary data can come from various sources, such as government agencies, academic institutions, or private companies.

How to Collect Data

The following are some steps to consider when collecting data:

• Define the objective : Before you start collecting data, you need to define the objective of the study. This will help you determine what data you need to collect and how to collect it.
• Identify the data sources : Identify the sources of data that will help you achieve your objective. These sources can be primary sources, such as surveys, interviews, and observations, or secondary sources, such as books, articles, and databases.
• Determine the data collection method : Once you have identified the data sources, you need to determine the data collection method. This could be through online surveys, phone interviews, or face-to-face meetings.
• Develop a data collection plan : Develop a plan that outlines the steps you will take to collect the data. This plan should include the timeline, the tools and equipment needed, and the personnel involved.
• Test the data collection process: Before you start collecting data, test the data collection process to ensure that it is effective and efficient.
• Collect the data: Collect the data according to the plan you developed in step 4. Make sure you record the data accurately and consistently.
• Analyze the data: Once you have collected the data, analyze it to draw conclusions and make recommendations.
• Report the findings: Report the findings of your data analysis to the relevant stakeholders. This could be in the form of a report, a presentation, or a publication.
• Monitor and evaluate the data collection process: After the data collection process is complete, monitor and evaluate the process to identify areas for improvement in future data collection efforts.
• Ensure data quality: Ensure that the collected data is of high quality and free from errors. This can be achieved by validating the data for accuracy, completeness, and consistency.
• Maintain data security: Ensure that the collected data is secure and protected from unauthorized access or disclosure. This can be achieved by implementing data security protocols and using secure storage and transmission methods.
• Follow ethical considerations: Follow ethical considerations when collecting data, such as obtaining informed consent from participants, protecting their privacy and confidentiality, and ensuring that the research does not cause harm to participants.
• Use appropriate data analysis methods : Use appropriate data analysis methods based on the type of data collected and the research objectives. This could include statistical analysis, qualitative analysis, or a combination of both.
• Record and store data properly: Record and store the collected data properly, in a structured and organized format. This will make it easier to retrieve and use the data in future research or analysis.
• Collaborate with other stakeholders : Collaborate with other stakeholders, such as colleagues, experts, or community members, to ensure that the data collected is relevant and useful for the intended purpose.

Applications of Data Collection

Data collection methods are widely used in different fields, including social sciences, healthcare, business, education, and more. Here are some examples of how data collection methods are used in different fields:

• Social sciences : Social scientists often use surveys, questionnaires, and interviews to collect data from individuals or groups. They may also use observation to collect data on social behaviors and interactions. This data is often used to study topics such as human behavior, attitudes, and beliefs.
• Healthcare : Data collection methods are used in healthcare to monitor patient health and track treatment outcomes. Electronic health records and medical charts are commonly used to collect data on patients’ medical history, diagnoses, and treatments. Researchers may also use clinical trials and surveys to collect data on the effectiveness of different treatments.
• Business : Businesses use data collection methods to gather information on consumer behavior, market trends, and competitor activity. They may collect data through customer surveys, sales reports, and market research studies. This data is used to inform business decisions, develop marketing strategies, and improve products and services.
• Education : In education, data collection methods are used to assess student performance and measure the effectiveness of teaching methods. Standardized tests, quizzes, and exams are commonly used to collect data on student learning outcomes. Teachers may also use classroom observation and student feedback to gather data on teaching effectiveness.
• Agriculture : Farmers use data collection methods to monitor crop growth and health. Sensors and remote sensing technology can be used to collect data on soil moisture, temperature, and nutrient levels. This data is used to optimize crop yields and minimize waste.
• Environmental sciences : Environmental scientists use data collection methods to monitor air and water quality, track climate patterns, and measure the impact of human activity on the environment. They may use sensors, satellite imagery, and laboratory analysis to collect data on environmental factors.
• Transportation : Transportation companies use data collection methods to track vehicle performance, optimize routes, and improve safety. GPS systems, on-board sensors, and other tracking technologies are used to collect data on vehicle speed, fuel consumption, and driver behavior.

Examples of Data Collection

Examples of Data Collection are as follows:

• Traffic Monitoring: Cities collect real-time data on traffic patterns and congestion through sensors on roads and cameras at intersections. This information can be used to optimize traffic flow and improve safety.
• Social Media Monitoring : Companies can collect real-time data on social media platforms such as Twitter and Facebook to monitor their brand reputation, track customer sentiment, and respond to customer inquiries and complaints in real-time.
• Weather Monitoring: Weather agencies collect real-time data on temperature, humidity, air pressure, and precipitation through weather stations and satellites. This information is used to provide accurate weather forecasts and warnings.
• Stock Market Monitoring : Financial institutions collect real-time data on stock prices, trading volumes, and other market indicators to make informed investment decisions and respond to market fluctuations in real-time.
• Health Monitoring : Medical devices such as wearable fitness trackers and smartwatches can collect real-time data on a person’s heart rate, blood pressure, and other vital signs. This information can be used to monitor health conditions and detect early warning signs of health issues.

Purpose of Data Collection

The purpose of data collection can vary depending on the context and goals of the study, but generally, it serves to:

• Provide information: Data collection provides information about a particular phenomenon or behavior that can be used to better understand it.
• Measure progress : Data collection can be used to measure the effectiveness of interventions or programs designed to address a particular issue or problem.
• Support decision-making : Data collection provides decision-makers with evidence-based information that can be used to inform policies, strategies, and actions.
• Identify trends : Data collection can help identify trends and patterns over time that may indicate changes in behaviors or outcomes.
• Monitor and evaluate : Data collection can be used to monitor and evaluate the implementation and impact of policies, programs, and initiatives.

When to use Data Collection

Data collection is used when there is a need to gather information or data on a specific topic or phenomenon. It is typically used in research, evaluation, and monitoring and is important for making informed decisions and improving outcomes.

Data collection is particularly useful in the following scenarios:

• Research : When conducting research, data collection is used to gather information on variables of interest to answer research questions and test hypotheses.
• Evaluation : Data collection is used in program evaluation to assess the effectiveness of programs or interventions, and to identify areas for improvement.
• Monitoring : Data collection is used in monitoring to track progress towards achieving goals or targets, and to identify any areas that require attention.
• Decision-making: Data collection is used to provide decision-makers with information that can be used to inform policies, strategies, and actions.
• Quality improvement : Data collection is used in quality improvement efforts to identify areas where improvements can be made and to measure progress towards achieving goals.

Characteristics of Data Collection

Data collection can be characterized by several important characteristics that help to ensure the quality and accuracy of the data gathered. These characteristics include:

• Validity : Validity refers to the accuracy and relevance of the data collected in relation to the research question or objective.
• Reliability : Reliability refers to the consistency and stability of the data collection process, ensuring that the results obtained are consistent over time and across different contexts.
• Objectivity : Objectivity refers to the impartiality of the data collection process, ensuring that the data collected is not influenced by the biases or personal opinions of the data collector.
• Precision : Precision refers to the degree of accuracy and detail in the data collected, ensuring that the data is specific and accurate enough to answer the research question or objective.
• Timeliness : Timeliness refers to the efficiency and speed with which the data is collected, ensuring that the data is collected in a timely manner to meet the needs of the research or evaluation.
• Ethical considerations : Ethical considerations refer to the ethical principles that must be followed when collecting data, such as ensuring confidentiality and obtaining informed consent from participants.

Advantages of Data Collection

There are several advantages of data collection that make it an important process in research, evaluation, and monitoring. These advantages include:

• Better decision-making : Data collection provides decision-makers with evidence-based information that can be used to inform policies, strategies, and actions, leading to better decision-making.
• Improved understanding: Data collection helps to improve our understanding of a particular phenomenon or behavior by providing empirical evidence that can be analyzed and interpreted.
• Evaluation of interventions: Data collection is essential in evaluating the effectiveness of interventions or programs designed to address a particular issue or problem.
• Identifying trends and patterns: Data collection can help identify trends and patterns over time that may indicate changes in behaviors or outcomes.
• Increased accountability: Data collection increases accountability by providing evidence that can be used to monitor and evaluate the implementation and impact of policies, programs, and initiatives.
• Validation of theories: Data collection can be used to test hypotheses and validate theories, leading to a better understanding of the phenomenon being studied.
• Improved quality: Data collection is used in quality improvement efforts to identify areas where improvements can be made and to measure progress towards achieving goals.

Limitations of Data Collection

While data collection has several advantages, it also has some limitations that must be considered. These limitations include:

• Bias : Data collection can be influenced by the biases and personal opinions of the data collector, which can lead to inaccurate or misleading results.
• Sampling bias : Data collection may not be representative of the entire population, resulting in sampling bias and inaccurate results.
• Cost : Data collection can be expensive and time-consuming, particularly for large-scale studies.
• Limited scope: Data collection is limited to the variables being measured, which may not capture the entire picture or context of the phenomenon being studied.
• Ethical considerations : Data collection must follow ethical principles to protect the rights and confidentiality of the participants, which can limit the type of data that can be collected.
• Data quality issues: Data collection may result in data quality issues such as missing or incomplete data, measurement errors, and inconsistencies.
• Limited generalizability : Data collection may not be generalizable to other contexts or populations, limiting the generalizability of the findings.

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What the data says about abortion in the u.s..

Pew Research Center has conducted many surveys about abortion over the years, providing a lens into Americans’ views on whether the procedure should be legal, among a host of other questions.

In a  Center survey  conducted nearly a year after the Supreme Court’s June 2022 decision that  ended the constitutional right to abortion , 62% of U.S. adults said the practice should be legal in all or most cases, while 36% said it should be illegal in all or most cases. Another survey conducted a few months before the decision showed that relatively few Americans take an absolutist view on the issue .

Find answers to common questions about abortion in America, based on data from the Centers for Disease Control and Prevention (CDC) and the Guttmacher Institute, which have tracked these patterns for several decades:

How many abortions are there in the U.S. each year?

How has the number of abortions in the u.s. changed over time, what is the abortion rate among women in the u.s. how has it changed over time, what are the most common types of abortion, how many abortion providers are there in the u.s., and how has that number changed, what percentage of abortions are for women who live in a different state from the abortion provider, what are the demographics of women who have had abortions, when during pregnancy do most abortions occur, how often are there medical complications from abortion.

This compilation of data on abortion in the United States draws mainly from two sources: the Centers for Disease Control and Prevention (CDC) and the Guttmacher Institute, both of which have regularly compiled national abortion data for approximately half a century, and which collect their data in different ways.

The CDC data that is highlighted in this post comes from the agency’s “abortion surveillance” reports, which have been published annually since 1974 (and which have included data from 1969). Its figures from 1973 through 1996 include data from all 50 states, the District of Columbia and New York City – 52 “reporting areas” in all. Since 1997, the CDC’s totals have lacked data from some states (most notably California) for the years that those states did not report data to the agency. The four reporting areas that did not submit data to the CDC in 2021 – California, Maryland, New Hampshire and New Jersey – accounted for approximately 25% of all legal induced abortions in the U.S. in 2020, according to Guttmacher’s data. Most states, though,  do  have data in the reports, and the figures for the vast majority of them came from each state’s central health agency, while for some states, the figures came from hospitals and other medical facilities.

Discussion of CDC abortion data involving women’s state of residence, marital status, race, ethnicity, age, abortion history and the number of previous live births excludes the low share of abortions where that information was not supplied. Read the methodology for the CDC’s latest abortion surveillance report , which includes data from 2021, for more details. Previous reports can be found at  stacks.cdc.gov  by entering “abortion surveillance” into the search box.

For the numbers of deaths caused by induced abortions in 1963 and 1965, this analysis looks at reports by the then-U.S. Department of Health, Education and Welfare, a precursor to the Department of Health and Human Services. In computing those figures, we excluded abortions listed in the report under the categories “spontaneous or unspecified” or as “other.” (“Spontaneous abortion” is another way of referring to miscarriages.)

Guttmacher data in this post comes from national surveys of abortion providers that Guttmacher has conducted 19 times since 1973. Guttmacher compiles its figures after contacting every known provider of abortions – clinics, hospitals and physicians’ offices – in the country. It uses questionnaires and health department data, and it provides estimates for abortion providers that don’t respond to its inquiries. (In 2020, the last year for which it has released data on the number of abortions in the U.S., it used estimates for 12% of abortions.) For most of the 2000s, Guttmacher has conducted these national surveys every three years, each time getting abortion data for the prior two years. For each interim year, Guttmacher has calculated estimates based on trends from its own figures and from other data.

The latest full summary of Guttmacher data came in the institute’s report titled “Abortion Incidence and Service Availability in the United States, 2020.” It includes figures for 2020 and 2019 and estimates for 2018. The report includes a methods section.

In addition, this post uses data from StatPearls, an online health care resource, on complications from abortion.

An exact answer is hard to come by. The CDC and the Guttmacher Institute have each tried to measure this for around half a century, but they use different methods and publish different figures.

The last year for which the CDC reported a yearly national total for abortions is 2021. It found there were 625,978 abortions in the District of Columbia and the 46 states with available data that year, up from 597,355 in those states and D.C. in 2020. The corresponding figure for 2019 was 607,720.

The last year for which Guttmacher reported a yearly national total was 2020. It said there were 930,160 abortions that year in all 50 states and the District of Columbia, compared with 916,460 in 2019.

• How the CDC gets its data: It compiles figures that are voluntarily reported by states’ central health agencies, including separate figures for New York City and the District of Columbia. Its latest totals do not include figures from California, Maryland, New Hampshire or New Jersey, which did not report data to the CDC. ( Read the methodology from the latest CDC report .)
• How Guttmacher gets its data: It compiles its figures after contacting every known abortion provider – clinics, hospitals and physicians’ offices – in the country. It uses questionnaires and health department data, then provides estimates for abortion providers that don’t respond. Guttmacher’s figures are higher than the CDC’s in part because they include data (and in some instances, estimates) from all 50 states. ( Read the institute’s latest full report and methodology .)

While the Guttmacher Institute supports abortion rights, its empirical data on abortions in the U.S. has been widely cited by  groups  and  publications  across the political spectrum, including by a  number of those  that  disagree with its positions .

These estimates from Guttmacher and the CDC are results of multiyear efforts to collect data on abortion across the U.S. Last year, Guttmacher also began publishing less precise estimates every few months , based on a much smaller sample of providers.

The figures reported by these organizations include only legal induced abortions conducted by clinics, hospitals or physicians’ offices, or those that make use of abortion pills dispensed from certified facilities such as clinics or physicians’ offices. They do not account for the use of abortion pills that were obtained  outside of clinical settings .

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The annual number of U.S. abortions rose for years after Roe v. Wade legalized the procedure in 1973, reaching its highest levels around the late 1980s and early 1990s, according to both the CDC and Guttmacher. Since then, abortions have generally decreased at what a CDC analysis called  “a slow yet steady pace.”

Guttmacher says the number of abortions occurring in the U.S. in 2020 was 40% lower than it was in 1991. According to the CDC, the number was 36% lower in 2021 than in 1991, looking just at the District of Columbia and the 46 states that reported both of those years.

(The corresponding line graph shows the long-term trend in the number of legal abortions reported by both organizations. To allow for consistent comparisons over time, the CDC figures in the chart have been adjusted to ensure that the same states are counted from one year to the next. Using that approach, the CDC figure for 2021 is 622,108 legal abortions.)

There have been occasional breaks in this long-term pattern of decline – during the middle of the first decade of the 2000s, and then again in the late 2010s. The CDC reported modest 1% and 2% increases in abortions in 2018 and 2019, and then, after a 2% decrease in 2020, a 5% increase in 2021. Guttmacher reported an 8% increase over the three-year period from 2017 to 2020.

As noted above, these figures do not include abortions that use pills obtained outside of clinical settings.

Guttmacher says that in 2020 there were 14.4 abortions in the U.S. per 1,000 women ages 15 to 44. Its data shows that the rate of abortions among women has generally been declining in the U.S. since 1981, when it reported there were 29.3 abortions per 1,000 women in that age range.

The CDC says that in 2021, there were 11.6 abortions in the U.S. per 1,000 women ages 15 to 44. (That figure excludes data from California, the District of Columbia, Maryland, New Hampshire and New Jersey.) Like Guttmacher’s data, the CDC’s figures also suggest a general decline in the abortion rate over time. In 1980, when the CDC reported on all 50 states and D.C., it said there were 25 abortions per 1,000 women ages 15 to 44.

That said, both Guttmacher and the CDC say there were slight increases in the rate of abortions during the late 2010s and early 2020s. Guttmacher says the abortion rate per 1,000 women ages 15 to 44 rose from 13.5 in 2017 to 14.4 in 2020. The CDC says it rose from 11.2 per 1,000 in 2017 to 11.4 in 2019, before falling back to 11.1 in 2020 and then rising again to 11.6 in 2021. (The CDC’s figures for those years exclude data from California, D.C., Maryland, New Hampshire and New Jersey.)

The CDC broadly divides abortions into two categories: surgical abortions and medication abortions, which involve pills. Since the Food and Drug Administration first approved abortion pills in 2000, their use has increased over time as a share of abortions nationally, according to both the CDC and Guttmacher.

The majority of abortions in the U.S. now involve pills, according to both the CDC and Guttmacher. The CDC says 56% of U.S. abortions in 2021 involved pills, up from 53% in 2020 and 44% in 2019. Its figures for 2021 include the District of Columbia and 44 states that provided this data; its figures for 2020 include D.C. and 44 states (though not all of the same states as in 2021), and its figures for 2019 include D.C. and 45 states.

Guttmacher, which measures this every three years, says 53% of U.S. abortions involved pills in 2020, up from 39% in 2017.

Two pills commonly used together for medication abortions are mifepristone, which, taken first, blocks hormones that support a pregnancy, and misoprostol, which then causes the uterus to empty. According to the FDA, medication abortions are safe  until 10 weeks into pregnancy.

Surgical abortions conducted  during the first trimester  of pregnancy typically use a suction process, while the relatively few surgical abortions that occur  during the second trimester  of a pregnancy typically use a process called dilation and evacuation, according to the UCLA School of Medicine.

In 2020, there were 1,603 facilities in the U.S. that provided abortions,  according to Guttmacher . This included 807 clinics, 530 hospitals and 266 physicians’ offices.

While clinics make up half of the facilities that provide abortions, they are the sites where the vast majority (96%) of abortions are administered, either through procedures or the distribution of pills, according to Guttmacher’s 2020 data. (This includes 54% of abortions that are administered at specialized abortion clinics and 43% at nonspecialized clinics.) Hospitals made up 33% of the facilities that provided abortions in 2020 but accounted for only 3% of abortions that year, while just 1% of abortions were conducted by physicians’ offices.

Looking just at clinics – that is, the total number of specialized abortion clinics and nonspecialized clinics in the U.S. – Guttmacher found the total virtually unchanged between 2017 (808 clinics) and 2020 (807 clinics). However, there were regional differences. In the Midwest, the number of clinics that provide abortions increased by 11% during those years, and in the West by 6%. The number of clinics  decreased  during those years by 9% in the Northeast and 3% in the South.

The total number of abortion providers has declined dramatically since the 1980s. In 1982, according to Guttmacher, there were 2,908 facilities providing abortions in the U.S., including 789 clinics, 1,405 hospitals and 714 physicians’ offices.

The CDC does not track the number of abortion providers.

In the District of Columbia and the 46 states that provided abortion and residency information to the CDC in 2021, 10.9% of all abortions were performed on women known to live outside the state where the abortion occurred – slightly higher than the percentage in 2020 (9.7%). That year, D.C. and 46 states (though not the same ones as in 2021) reported abortion and residency data. (The total number of abortions used in these calculations included figures for women with both known and unknown residential status.)

The share of reported abortions performed on women outside their state of residence was much higher before the 1973 Roe decision that stopped states from banning abortion. In 1972, 41% of all abortions in D.C. and the 20 states that provided this information to the CDC that year were performed on women outside their state of residence. In 1973, the corresponding figure was 21% in the District of Columbia and the 41 states that provided this information, and in 1974 it was 11% in D.C. and the 43 states that provided data.

In the District of Columbia and the 46 states that reported age data to  the CDC in 2021, the majority of women who had abortions (57%) were in their 20s, while about three-in-ten (31%) were in their 30s. Teens ages 13 to 19 accounted for 8% of those who had abortions, while women ages 40 to 44 accounted for about 4%.

The vast majority of women who had abortions in 2021 were unmarried (87%), while married women accounted for 13%, according to  the CDC , which had data on this from 37 states.

In the District of Columbia, New York City (but not the rest of New York) and the 31 states that reported racial and ethnic data on abortion to  the CDC , 42% of all women who had abortions in 2021 were non-Hispanic Black, while 30% were non-Hispanic White, 22% were Hispanic and 6% were of other races.

Looking at abortion rates among those ages 15 to 44, there were 28.6 abortions per 1,000 non-Hispanic Black women in 2021; 12.3 abortions per 1,000 Hispanic women; 6.4 abortions per 1,000 non-Hispanic White women; and 9.2 abortions per 1,000 women of other races, the  CDC reported  from those same 31 states, D.C. and New York City.

For 57% of U.S. women who had induced abortions in 2021, it was the first time they had ever had one,  according to the CDC.  For nearly a quarter (24%), it was their second abortion. For 11% of women who had an abortion that year, it was their third, and for 8% it was their fourth or more. These CDC figures include data from 41 states and New York City, but not the rest of New York.

Nearly four-in-ten women who had abortions in 2021 (39%) had no previous live births at the time they had an abortion,  according to the CDC . Almost a quarter (24%) of women who had abortions in 2021 had one previous live birth, 20% had two previous live births, 10% had three, and 7% had four or more previous live births. These CDC figures include data from 41 states and New York City, but not the rest of New York.

The vast majority of abortions occur during the first trimester of a pregnancy. In 2021, 93% of abortions occurred during the first trimester – that is, at or before 13 weeks of gestation,  according to the CDC . An additional 6% occurred between 14 and 20 weeks of pregnancy, and about 1% were performed at 21 weeks or more of gestation. These CDC figures include data from 40 states and New York City, but not the rest of New York.

About 2% of all abortions in the U.S. involve some type of complication for the woman , according to an article in StatPearls, an online health care resource. “Most complications are considered minor such as pain, bleeding, infection and post-anesthesia complications,” according to the article.

The CDC calculates  case-fatality rates for women from induced abortions – that is, how many women die from abortion-related complications, for every 100,000 legal abortions that occur in the U.S .  The rate was lowest during the most recent period examined by the agency (2013 to 2020), when there were 0.45 deaths to women per 100,000 legal induced abortions. The case-fatality rate reported by the CDC was highest during the first period examined by the agency (1973 to 1977), when it was 2.09 deaths to women per 100,000 legal induced abortions. During the five-year periods in between, the figure ranged from 0.52 (from 1993 to 1997) to 0.78 (from 1978 to 1982).

The CDC calculates death rates by five-year and seven-year periods because of year-to-year fluctuation in the numbers and due to the relatively low number of women who die from legal induced abortions.

In 2020, the last year for which the CDC has information , six women in the U.S. died due to complications from induced abortions. Four women died in this way in 2019, two in 2018, and three in 2017. (These deaths all followed legal abortions.) Since 1990, the annual number of deaths among women due to legal induced abortion has ranged from two to 12.

The annual number of reported deaths from induced abortions (legal and illegal) tended to be higher in the 1980s, when it ranged from nine to 16, and from 1972 to 1979, when it ranged from 13 to 63. One driver of the decline was the drop in deaths from illegal abortions. There were 39 deaths from illegal abortions in 1972, the last full year before Roe v. Wade. The total fell to 19 in 1973 and to single digits or zero every year after that. (The number of deaths from legal abortions has also declined since then, though with some slight variation over time.)

The number of deaths from induced abortions was considerably higher in the 1960s than afterward. For instance, there were 119 deaths from induced abortions in  1963  and 99 in  1965 , according to reports by the then-U.S. Department of Health, Education and Welfare, a precursor to the Department of Health and Human Services. The CDC is a division of Health and Human Services.

Note: This is an update of a post originally published May 27, 2022, and first updated June 24, 2022.

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Key facts about the abortion debate in America

Public opinion on abortion, three-in-ten or more democrats and republicans don’t agree with their party on abortion, partisanship a bigger factor than geography in views of abortion access locally, do state laws on abortion reflect public opinion, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

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ABA core provider survey cited in Kansas City Fed research brief

The researchers highlight 2022 ABA survey results showing that 46% of community banks that used the “big three” of Fiserv, FIS and Jack Henry were extremely or somewhat dissatisfied with their core provider, compared with about 27% of banks that used a smaller core provider, and they highlighted the contrast in ratings by banks and by the cores themselves, noting that “ABA concludes that this gap in effectiveness assessment between the banks and core providers ‘is the root cause of bank leaders’ dissatisfaction with core providers.’”

The article found that the “big three” not only “dominate the U.S. core services market but also have a large presence in related vertical markets, such as card network services; payment processing services for DIs, merchants, or governments; and BaaS.” The researchers discuss the CFPB’s concerns over market power , although they note that “it is difficult to assess whether the Big Three are leveraging this power.”

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This paper is in the following e-collection/theme issue:

Published on 29.3.2024 in Vol 26 (2024)

Effects of a Digital Mental Health Intervention on Perceived Stress and Rumination in Adolescents Aged 13 to 17 Years: Randomized Controlled Trial

Authors of this article:

Original Paper

• Eliane M Boucher, PhD   ; 
• Haley Ward, BA   ; 
• Cynthia J Miles, BS   ; 
• Robert D Henry, PhD   ; 
• Sarah Elizabeth Stoeckl, BS  

Twill, New York, NY, United States

Corresponding Author:

Eliane M Boucher, PhD

114 Fifth Avenue

New York, NY, 10011

United States

Phone: 1 432 258 5233

Email: [email protected]

Background: Although adolescents report high levels of stress, they report engaging in few stress management techniques. Consequently, developing effective and targeted programs to help address this transdiagnostic risk factor in adolescence is particularly important. Most stress management programs for adolescents are delivered within schools, and the evidence for these programs is mixed, suggesting a need for alternative options for stress management among adolescents.

Objective: The aim of the study is to test the short-term effects of a self-guided digital mental health intervention (DMHI) designed for adolescents on perceived stress and rumination (ie, brooding).

Methods: This was a 12-week, 2-arm decentralized randomized controlled trial of adolescents aged 13 to 17 years who presented with elevated levels of perceived stress and brooding. Participants were randomly assigned to engage with a self-guided DMHI (Happify for Teens) or to a waitlist control. Participants assigned to the intervention group were given access to the program for 12 weeks. Happify for Teens consists of various evidence-based activities drawn from therapeutic modalities such as cognitive behavioral therapy, positive psychology, and mindfulness, which are then organized into several programs targeting specific areas of concern (eg, Stress Buster 101). Participants in the waitlist control received access to this product for 12 weeks upon completing the study. Participants in both groups completed measures of perceived stress, brooding, optimism, sleep disturbance, and loneliness at baseline, 4 weeks, 8 weeks, and 12 weeks. Changes in outcomes between the intervention and waitlist control groups were assessed using repeated-measures multilevel models.

Results: Of the 303 participants included in data analyses, 132 were assigned to the intervention and 171 to the waitlist. There were significantly greater improvements in the intervention condition for perceived stress (intervention: B =–1.50; 95% CI –1.82 to –1.19; P <.001 and control: B =–0.09; 95% CI –0.44 to 0.26; P =.61), brooding (intervention: B =–0.84; 95% CI –1.00 to –0.68; P <.001 and control: B =–0.30; 95% CI –0.47 to –0.12; P =.001), and loneliness (intervention: B =–0.96; 95% CI –1.2 to –0.73; P <.001 and control: B =–0.38; 95% CI: –0.64 to –0.12; P =.005) over the 12-week study period. Changes in optimism and sleep disturbance were not significantly different across groups ( P s≥.096).

Conclusions: Happify for Teens was effective at reducing perceived stress, rumination, and loneliness among adolescents over 12 weeks when compared to a waitlist control group. Our data reveal the potential benefits of DMHIs for adolescents, which may present a more scalable, destigmatized, and cost-effective alternative to school-based programs.

Trial Registration: ClinicalTrials.gov NCT04567888; https://clinicaltrials.gov/ct2/show/NCT04567888

International Registered Report Identifier (IRRID): RR2-10.2196/25545

Introduction

The onset of many mental health disorders occurs in childhood and adolescence, and these disorders often continue into adulthood [ 1 , 2 ]. Already, approximately 20% of adolescents worldwide have at least 1 mental health disorder [ 3 ]; however, rates of mental illness among adolescents are increasing [ 4 ] and at steeper rates than among adults [ 5 ]. Addressing mental health in adolescence is critical to reducing the prevalence and consequences of mental health disorders in adulthood.

Despite public health efforts to increase access to mental health services for youths, the use of these services by adolescents with mental health disorders remains low [ 6 ]. Research suggests that only 50% of US adolescents with mental illness seek treatment [ 7 ], and as few as 25% actually receive treatment [ 8 ]. Paradoxically, national trends indicate that, overall, the use of outpatient mental health services by US adolescents, including both psychotherapy and psychotropic medications, has increased over time [ 9 ]. However, this increase is primarily attributed to adolescents with less severe or no mental health impairment [ 9 ]. This is problematic, given the shortage of mental health service providers for children and adolescents, particularly in rural and low-income areas [ 10 ]. The increased use of these services by adolescents likely places a strain on the available services for youths and, in turn, adolescents, with more serious mental health disorders may have difficulties receiving necessary treatment. Interventions that are focused on promoting flourishing and preventing future dysfunction and impairment may help to reduce the burden on mental health services by offering alternative services to adolescents with little or no mental health impairment [ 11 ].

Stress as a Risk Factor in Adolescence

Adolescence is a developmental stage where individuals may be particularly sensitive to stress due to shifts in hypothalamic-pituitary-adrenal axis reactivity, leading to more intense hormonal responses to stressors, particularly in older adolescents [ 12 ]. Over the last decade, researchers have become increasingly interested in adolescent stress as an important transdiagnostic risk factor. Although animal models suggest that predictable, chronic mild stress levels in adolescence can actually increase resilience in adulthood [ 13 ], research suggests many adolescents are coping with more severe stress levels. In one study, 22% of adolescents aged 15 to 17 years reported moderate to severe levels of perceived stress [ 14 ]. In addition, national surveys conducted by the American Psychological Association [ 15 , 16 ] have found that adolescents report higher levels of stress than most adults, particularly during the school year.

Such high levels of stress have been linked to lower life satisfaction [ 17 ], poorer academic performance [ 18 , 19 ], cigarette smoking [ 20 ], emotional eating [ 21 ], poorer diet [ 22 ], more frequent subjective health complaints (eg, headaches, fatigue, and sleep difficulties) [ 23 ], as well as internalizing symptoms including depression [ 24 , 25 ] and anxiety [ 25 ]. Interpersonal stress, in particular, predicts the onset of a first major depressive episode among adolescents [ 26 ]. Thus, addressing stress in adolescents is critical to avoiding more long-term problems.

However, 25% of adolescents self-report not doing enough to manage their stress [ 16 ]. Approximately 55% of adolescents report setting aside time for stress management “a few times a month or less,” 13% report never setting aside time for stress management, and just 5% report having seen a mental health professional about their stress [ 15 ]. Based on these data, the American Psychological Association noted the need for opportunities to help adolescents address and cope with their stress in order “to break this unhealthy legacy of stress in America” [ 15 ].

Although there has been an increase in interventions targeting adolescent stress [ 27 ], evidence-based interventions for stress are much less common than those for anxiety and depression [ 28 ]. Furthermore, most interventions for stress are school-based, and the evidence for these interventions is mixed. In one systematic review of stress management interventions, only 58% of the reviewed studies found significant improvements in physiological indicators of stress (eg, blood pressure) or self-reported stress [ 29 ]. More recent meta-analyses of school-based programs further suggest that these programs may only be effective for school rather than social stress [ 27 ]. Given these findings, we need more research exploring the effectiveness of stress management programs with adolescents, particularly those that could be delivered outside schools.

Negative Cognitions and Stress

In addition, given that stress in adolescence stems, at least in part, from feelings of helplessness and negative affect [ 30 ], effective interventions for adolescent stress may need to target underlying negative cognitions as well as perceived stress. However, recommended approaches to addressing stress tend to focus on stress management training, relaxation training, and problem-solving skill or decision-making skill training [ 27 , 28 , 31 ], which may not adequately address the related negative cognitions and cognitive processes.

Indeed, there is evidence that improving the content of adolescents’ cognitions can help attenuate the consequences of stress. For example, interpersonal stress predicts depressive symptoms in adolescents only when coupled with negative cognitions [ 26 ] or persistent low positive affect [ 32 ], whereas self-compassion buffers against the negative consequences of stress on internalizing symptoms [ 25 ]. In other words, addressing both negative cognitions and stress together may be particularly important to mitigate the negative consequences of stress [ 26 ].

Rumination—a pattern of repeatedly thinking about the causes, consequences, and symptoms of one’s negative affect [ 33 ]—is one cognitive process that may be particularly relevant to stress and future risk of mental health concerns. Because rumination can occur in response to stressful events, it also plays a role in the negative consequences of chronic stress. Longitudinal research has shown that more frequent stressful life events predict increased rumination among both adults and adolescents, and that rumination mediates the relationship between stressful life events and anxiety symptoms in adolescents [ 34 ]. Other research has shown that adolescents who ruminate in response to stress are at greater risk of depression and substance misuse [ 35 ].

Rumination may also increase perceived stress. In one study, rumination exacerbated the relationship between life hassles and depression, anxiety, and stress in adolescents [ 36 ]. Other research shows that rumination increases adolescents’ likelihood of experiencing interpersonal stress which, in turn, predicts more internalizing symptoms [ 37 ]. Therefore, applying approaches that are more traditionally applied to addressing negative cognitive processes like rumination, such as cognitive restructuring, self-monitoring, acceptance strategies, and attention control training [ 31 ], may be helpful in reducing stress as well.

These findings suggest there may be a common pathway to reducing both rumination and perceived stress in adolescents. Therefore, identifying interventions that can address both would be beneficial as they would target 2, rather than 1, important transdiagnostic risk factors in the adolescent population.

The aim of this study was to test the impact of a digital mental health intervention (DMHI) designed for adolescents called Happify for Teens (Twill Inc). This program has been adapted for adolescents between 13 and 17 years of age from another DMHI developed for adults (Happify; Twill Inc). Happify for Teens consists of gamified versions of evidence-based activities adapted from various therapeutic approaches including cognitive behavioral therapy (CBT) [ 38 ], mindfulness-based stress reduction [ 39 ], and positive psychology [ 40 , 41 ]. Consequently, these programs integrate a variety of recommended approaches to addressing negative cognitions [ 31 ] that also help manage stress [ 42 - 45 ].

Observational studies of real-world Happify users have shown significant improvements in subjective well-being and anxiety among adults after 6-8 weeks of use, with greater gains among users who completed more activities [ 46 - 48 ]. Randomized controlled trials (RCTs) with adult participants have similarly shown improvements in depressive symptoms, anxiety, and resilience among those who completed at least 2 activities per week relative to a control group [ 49 , 50 ]. However, Happify for Teens has yet to be tested empirically. Therefore, in this study, we recruited adolescents aged 13 to 17 years who reported elevated stress and rumination. Participants were randomly assigned to have access to Happify for Teens for 12 weeks or to a corresponding waitlist control group. Changes in perceived stress after 4, 8, and 12 weeks across the 2 groups were compared. We also examined changes in brooding (the maladaptive component of rumination) as a secondary outcome and in sleep disturbance, loneliness, and optimism as exploratory outcomes.

Study Design

This was a 12-week, 2-arm RCT of adolescents aged 13 to 17 years residing in the United States with elevated levels of perceived stress and brooding ( Multimedia Appendix 1 ).

Ethical Considerations

A study protocol was previously published [ 51 ], and the trial was registered with ClinicalTrials.gov (NCT04567888). Study procedures were reviewed and approved by IntegReview (HLS-20), an independent institutional review board, which was acquired by Advarra after the study was launched. Parental consent was obtained electronically as part of the prescreening questionnaire, and participant assent was obtained electronically before participants began the baseline assessment, after qualifying for the study. The use of e-signatures was approved by IntegReview. Participants received US $20 for completing each of the 4-, 8-, and 12-week assessments and a US $20 bonus if they completed all 4 assessments. Participants were not compensated for engaging in the intervention. All data were deidentified for analysis, and responses to the baseline, 4-, 8-, and 12-week assessments were matched using a user-generated ID code, which was entered at the beginning of each assessment.

Participants

The study was advertised to parents or guardians via social media, emails to Happify users, within US schools, and using a snowballing recruitment method. Parents or guardians were directed to complete a prescreening questionnaire to report their child’s age, country of residence, and previous Happify use and to provide electronic consent for each eligible child. Adolescents who were qualified based on the prescreening questionnaire were then invited to complete a screening questionnaire via email; adolescents were eligible to participate if they reported being 13 to 17 years of age, residing in the United States, having never used Happify, and reporting elevated stress (Perceived Stress Scale [ 52 ] scores >14) and brooding (Ruminative Response Scale—Short Form—Brooding Subscale scores [ 53 ] ≥10).

Eligible participants were directed to complete the baseline assessment and provide electronic assent to participate in the study. To enroll in the study, participants had to provide electronic assent, complete the baseline assessment, and pass at least 1 attention check.

Once enrolled, participants were randomized to condition; randomization was completed automatically by Qualtrics (Qualtrics) using block randomization upon completing the baseline assessment and meeting final eligibility criteria. Those assigned to the intervention condition received instructions to download the Happify mobile app and were directed to the Happify for Teens platform after creating an account. Like the original Happify program, Happify for Teens consists of digital versions of evidence-based activities, which are categorized into 6 different skills: Savor (activities focused on developing mindfulness), thank (activities focused on gratitude), Aspire (activities focused on optimism, goal-setting, and finding meaning and purpose), Give (activities focused on acts of kindness, forgiveness, or promoting prosocial behavior), Empathize (activities fostering self-compassion and perspective-taking), and Revive (activities focused on physical health). In Happify for Teens, these activities were modified and then reviewed by a panel of adolescents to ensure the language and content were both appropriate and relevant. As in the original Happify program, activities are organized into “tracks,” 4-week programs intended to address a specific area of concern, like increasing one’s confidence or reducing stress. Users are able to switch tracks at any time and can also access activities outside these tracks, on demand, through the Instant Play feature. More information on the Happify for Teens program, including screenshots, can be found elsewhere [ 51 ].

Participants were given access to all Happify for Teens tracks; however, the same track ( Stop the Worry Cycle ) was shown as the featured track for all participants and recommended upon signing up for the program. Participants received no instructions on how much to engage with the intervention but received push notifications and weekly engagement emails as part of the intervention. We also contacted participants who completed no activities over 7 days via email or SMS text message (based on participant preference). Participants had access to the intervention for the full study period but stopped receiving push notifications or emails regarding use after 8 weeks; this was done to provide a period of time where engagement with the program may be more naturalistic, given that RCT procedures tend to be associated with inflated engagement with DMHIs [ 54 ]. Participants in both conditions also received regular emails or SMS text messages (depending on participant preference) about their progress to boost retention. These emails were identical regardless of condition and reminded participants of an upcoming assessment (when appropriate) or asked if the participant had any concerns. In total, 5 such emails were sent throughout the 12-week study period. Waitlist participants received access to the intervention after 12 weeks.

Every 4 weeks, participants were prompted to complete outcome measures via Qualtrics. Participants were contacted via email or SMS text message (based on participant preference) if an assessment was not completed within 7 days of its scheduled date.

Measurements and Outcomes

Primary outcome: perceived stress.

The Perceived Stress Scale [ 52 ] consists of 10 items asking participants how often they felt each feeling or thought in the previous month (eg, “How often have you felt nervous and ‘stressed’?”). Items are rated on a scale from 0 (never) to 4 (very often), and ratings are summed, so higher scores indicate greater perceived stress. Across the 4 time points, internal reliabilities ranged from acceptable to good (αs=.77 to .88).

Secondary Outcome: Brooding

The Brooding Subscale of the Ruminative Response Scale [ 53 ] asks respondents to indicate how often they engage in 5 behaviors (eg, “Think ‘Why can’t I handle things better’?”) on a scale from 1 (almost never) to 4 (almost always). Participants in this study were asked to reflect on the previous month. Ratings are summed, so higher scores indicate more brooding. Internal reliability values were fair to acceptable (αs=.61 to .78).

Exploratory Outcomes

Sleep disturbance.

The PROMIS (Patient-Reported Outcomes Measurement Information System) Pediatric Sleep Disturbance Scale—Short Form 4a [ 55 ] measures the extent to which participants experienced sleep disturbances over the previous 7 days (eg, “In the past 7 days, I had trouble sleeping”). Items are rated on a scale from 1 (never) to 5 (always), and ratings are summed, so higher scores indicate more sleep disturbance. Internal consistency ranged from good to excellent (αs=.89 to .91).

The Roberts UCLA Loneliness Scale [ 56 ] consists of 8 items (eg, “I lack companionship”). Respondents rate each statement on a 4-point scale from 0 (never) to 3 (often), and ratings are summed, so higher scores indicate greater loneliness. Internal reliability values ranged were all good (αs=.82 to .85).

The Life Orientation Test—Revised [ 57 ] consists of 10 items (eg, “I’m always optimistic about my future”). Respondents indicate their level of agreement with each statement on a 5-point scale from 0 (strongly disagree) to 4 (strongly agree). After dropping 4 filler items, ratings are summed, so higher scores indicate more optimism. Internal reliabilities were acceptable (αs=.72 to .77).

Statistical Analysis

To assess whether changes in outcomes differed across groups, we created repeated-measures multilevel models (MLMs) for each outcome. MLMs were computed in R software (R Foundation for Statistical Computing) using the lme4 package [ 58 ] and restricted maximum likelihood estimation. All models included a random slope for time (Δ χ 2 2 s≥10.3; P s≤.01) and cross-level interactions for condition (waitlist and intervention)×time (baseline, 4 weeks, 8 weeks, and 12 weeks). We examined regression assumptions (eg, residual normality and influential observations), and final models were run with the small number of influential outliers removed (2-4 observations, depending on the outcome). Note that these analyses differ from those in the published protocol [ 51 ] because data violated the sphericity assumption for repeated-measures ANOVAs. Additionally, MLMs can manage missing outcome data without imputation, allowing us to retain more participants. Due to power constraints, we focus only on analyses testing changes in primary, secondary, and exploratory outcomes across conditions.

In addition, because careless responding is problematic with web-based surveys and may artificially increase relationships between variables, we used two a priori mechanisms for identifying low-quality data: (1) failing 3 or more attention checks in any given assessment and (2) completing an assessment at a rate faster than 1 second per item [ 59 ]. Specific assessments that met either of these criteria were dropped rather than dropping the participant altogether, and analyses were rerun without these assessments as a sensitivity analysis.

Study enrollment began on June 3, 2021, and continued until December 18, 2021. Overall, 2332 parents or guardians completed the screening questionnaire, of which 1604 met initial inclusion criteria and provided consent. In total, 631 adolescents proceeded to complete the screener, of which 353 met inclusion criteria, completed the baseline assessment, and were enrolled into the study and assigned to condition (Happify for Teens: n=178 and waitlist: n=175). However, 22 participants in the intervention condition did not create a Happify for Teens account and were withdrawn from the study.

Note that this sample is smaller than the target sample size reported in the published protocol [ 51 ]. As described in that protocol, however, power analyses indicated that 200 participants would be sufficient for 80% power to detect a small effect for our primary outcome. Due to the high levels of dropout observed with digital interventions [ 60 ], including with adolescents, we assumed a 75% attrition rate and set a target sample size of 800 participants. Because attrition rates were much lower than expected (assessment completion rates ranged from 78.95% to 87.13%), we decided to stop enrollment once 100 participants per condition completed the 12-week assessment to avoid oversampling, resulting in a smaller sample.

Data Exclusion

Of the 331 participants who completed the study, 28 were excluded from data analyses ( Figure 1 ). Of note, 22 participants in the intervention condition failed to complete any activities throughout the study period (and thus were not exposed to the intervention). In total, 5 participants were excluded for providing odd or missing birth years on the baseline assessment, and 1 additional participant was excluded for having duplicate responses to assessments. This resulted in a total of 303 participants included in our analyses (Happify for Teens: n=132 and waitlist n=171). Because the failure to engage with the intervention is subject to self-selection bias, and thus excluding these participants from the analysis means the sample is not fully randomized, we also conducted sensitivity analyses including participants who signed up for the program but completed no activities (n=22) as well as those participants randomized to the Happify for Teens condition who never created an account on the platform (n=22).

Sample Demographics

Sample demographics are presented in detail in Table 1 . The majority of the sample identified as female (n=202, 66.7%) and as White (n=262, 86.5%). Fewer participants reported being 13 years of age relative to other age groups, but all qualifying age groups were represented in our sample. When starting the study, the majority of participants (n=226, 74.6%) were enrolled in school full-time, in person.

a Gender was assessed using an open-ended question (What is your gender?); responses clearly identifying male or female were coded as such, and other responses were combined into the “neither” category.

b Age was estimated using participants’ reported birth year at baseline. Adolescents reported their age during screening, and those reporting ages 13 years and younger or 17 years and older were disqualified. Nevertheless, some participants may have turned 18 years before the baseline assessment or during the study period.

c Race was a multioption question, consequently percentages across categories sum to more than 100%.

Most participants were not currently using any self-care or wellness apps (n=268, 88.4%). Among those currently using these programs, there was a great deal of variability in programs, but I am Sober (n=4) and Calm (n=3) were reported most frequently. Additionally, although we used current Happify members as one recruitment mechanism, few participants reported their parents used Happify (n=25, 8.3%).

Happify for Teens Use

Of the participants assigned to the Happify for Teens condition who signed up for the program, 85.7% (132/154) completed at least 1 activity over the 12-week study period. The mean number of activities completed among these participants was 46.24 (SD 53.02), ranging from 1 to 235 activities.

Consistent with other DMHI research, engagement dropped over the course of the 12-week study period. More specifically, among participants who completed at least 1 activity, 3 (2.3%) completed no activities during the first 4 weeks, whereas 25 (18.9%) completed no activities between week 5 and week 8, and 60 (45.5%) completed no activities between week 9 and week 12. Similarly, mean levels of engagement dropped over time, with an average of 22.49 (SD 22.29) activities completed between week 1 and week 4 compared to an average of 15.25 (SD 21.11) activities completed between week 5 and week 8 and 8.5 (SD 14.49) activities completed between week 9 and week 12.

Although participants were not given explicit instructions on how often to engage with the Happify for Teens platform or how many activities to complete, previous research with adults suggests that completing an average of 2 or more activities is optimal [ 49 , 50 , 61 , 62 ]. Among participants who completed at least 1 activity, 75.8% (n=100) engaged at the optimal level during the first 4 weeks, 50% (n=66) engaged at the optimal level between week 5 and week 8, and 29.5% (n=39) engaged at the optimal level between week 9 and week 12. These levels are consistent or better than what has been observed in previous research using adults [ 49 , 61 , 62 ].

Changes in Outcomes

Descriptive statistics for each outcome by assessment period are presented in Table 2 . All final MLMs reported below included a random slope for time (Δ χ 2 2 s≥10.3; P s≤.01). Only 4 participants were flagged for attention checks (1 on 3 of 4 assessments, 1 on 2 assessments, and 2 on just 1 assessment). No participants were flagged for completion rate. Primary and secondary outcomes did not change meaningfully in these analyses when these assessments were excluded. In addition, outcomes did not change meaningfully in sensitivity analyses including participants who had been randomly assigned to the intervention condition but never engaged with the Happify for Teens program. More specifically, no main effects of time or condition changed for any of the primary, secondary, or exploratory outcomes nor did any of the time×condition interactions. However, some nonsignificant effects for control variables did become significant in the sensitivity analyses. The effect of age became significant for perceived stress ( P =.04), such that stress increased with age. The effect of gender also became significant for both optimism ( P =.03) and loneliness ( P =.02), such that adolescents who identified as male reported higher levels of optimism but also higher levels of loneliness compared to other gender identities.

a Perceived stress was measured with the Perceived Stress Scale [ 52 ].

b Brooding was measured using the Ruminative Response Scale—Brooding Subscale [ 53 ].

c Sleep disturbance was measured using the PROMIS (Patient-Reported Outcomes Measurement Information System) Pediatric Sleep Disturbance Scale—Short Form 4a [ 54 ].

d Loneliness was measured using the Roberts UCLA Loneliness Scale [ 55 ].

e Optimism was measured using the Life Orientation Test—Revised [ 56 ].

We found a significant main effect of time ( P <.001) but no significant effect of condition ( P =.97). These were qualified by the predicted condition×time interaction ( P <.001). To break down this interaction, we calculated simple slopes for each condition, which revealed a significant reduction in perceived stress among participants in the intervention condition ( B =–1.50; 95% CI –1.82 to –1.19; P <.001) but not among those in the waitlist control ( B =–0.09; 95% CI –0.44 to 0.26; P =.61; Figure 2 ). With the exception of a significant effect of gender ( P <.001) suggesting that participants identifying as male had significantly lower PSS scores overall, no other effects were significant ( P s≥.06).

We also found a significant effect of time ( P <.001) but not of condition ( P =.15) for brooding. These effects were qualified by a significant condition×time interaction ( P <.001). There were significant reductions in brooding among participants in the waitlist control ( B =–0.30; 95% CI –0.47 to –0.12; P =.001) as well as those in the Happify for Teens condition ( B =–0.84; 95% CI –1.00 to –0.68; P <.001); however, CIs for the 2 groups did not overlap, suggesting that improvements were relatively greater among those in the intervention condition ( Figure 3 ). Again, with the exception of a significant effect of gender suggesting that participants identifying as male reported significantly lower levels of brooding ( P <.001), no other effects were significant ( P s≥.35).

For sleep disturbance and optimism, we found a significant effect of time ( P s<.001) and no significant effect of condition ( P s≥.28). However, the corresponding condition×time interactions were not significant ( P s≥.10), suggesting that while there were improvements in sleep disturbance and optimism over time, improvements did not differ by condition. We did find a significant effect of age for sleep disturbance ( P =.04), suggesting that sleep disturbance was greater as age increased, but no other effects were significant ( P s≥.11). When assessments failing the attention check criterion were dropped, the condition×time interaction did become significant for sleep disturbance ( P =.04). Because no other outcomes changed substantially in the sensitivity analyses, we did not interpret this interaction to avoid making a type I error.

For loneliness, we also found a significant effect of time ( P <.001) and no significant effect of condition ( P =.79), but the corresponding condition×time interaction was significant ( P <.001). As with perceived stress and brooding, simple slopes for each condition were calculated, which revealed significant reductions in Roberts UCLA Loneliness Scale-8 scores among participants in the waitlist control ( B =–0.38; 95% CI –0.64 to –0.12; P =.005) as well as those in the intervention condition ( B =–0.96; 95% CI –1.2 to –0.73; P <.001). Similar to changes in brooding, however, the CIs for the 2 groups did not overlap, suggesting that improvements in loneliness were greater in the Happify for Teens group than in the waitlist control ( Figure 4 ). No other effects were significant ( P s≥.16).

Principal Findings

The purpose of this study was to test the efficacy of a DMHI designed for adolescents on perceived stress and brooding. Our findings suggest that adolescents who were engaged with the intervention had significant reductions in perceived stress, rumination, and loneliness over 12 weeks relative to those in a waitlist control but not in sleep disturbance or optimism.

Previous DMHI research with adolescents has focused primarily on depression and anxiety. For instance, in a recent review of 18 meta-analyses and systematic reviews of digital health interventions for adolescents [ 63 ], only 3 included stress as an outcome. Consistent with the present findings, these studies found significant improvements in stress among adolescents engaging with a digital intervention, which suggests DMHIs can be effective in improving stress management among adolescents. To our knowledge, however, this study was the first to explore the effects of a digital intervention on rumination among adolescents. Given that rumination predicts future dysfunction including anxiety, depression, and substance use [ 34 , 35 ], intervening early to reduce the frequency of brooding is another important mechanism for prevention.

We also found that the intervention significantly improved participants’ loneliness but not optimism or sleep disturbance. Although these were exploratory outcomes, the effect on loneliness is not unexpected, given that Happify for Teens includes information targeting loneliness. Research conducted on the adult version of Happify also suggests that users perceive several activities that appear in the adolescent version as helpful for addressing their feelings of loneliness [ 64 ]. In contrast, sleep is not a focus within the program; and, consequently, to impact sleep outcomes, a more targeted intervention may be necessary.

The reasons why we did not find an effect on optimism are less clear. One potential explanation is that the Life Orientation Test—Revised is a measure of dispositional optimism and thus may be less sensitive to changes in optimism over time. Indeed, a recent study suggested that a state measure of optimism may be more suitable for assessing within-person changes [ 65 ]. Another possibility is that the study was conducted during the COVID-19 pandemic, which may have impacted participants’ levels of optimism and the ability of the intervention to impact optimism. Consequently, additional research is needed to better understand whether this particular intervention can also improve optimism as well as perceived stress, brooding, and loneliness.

Leveraging DMHIs for Mental Health Support in Adolescence

Given that rates of mental illness among adolescents are increasing [ 4 ], and at a steeper rate than among adults [ 5 ], identifying opportunities to increase access to mental health care in this population is critical. Currently, most stress management programs for adolescents continue to be delivered within schools [ 27 - 29 ]. Although school-based prevention programs can be effective [ 28 , 29 ], there are numerous barriers to implementing evidence-based interventions within schools, including lack of time and resources and financial constraints [ 66 ]. Costs associated with implementing such interventions may be particularly prohibitive in socially and economically disadvantaged areas [ 28 ], where students may need these interventions most [ 27 ]. Even when such programs can be implemented, student participation may be negatively impacted by fears of stigmatization [ 67 ]. Given that 95% of US adolescents own, or have access to, a cellular phone, and 88% have daily access to a computer [ 68 ], digital interventions may offer a better, and arguably more cost-effective, opportunity to reach more adolescents while potentially reducing concerns with stigma by increasing privacy and confidentiality.

DMHIs have become increasingly popular [ 69 ], and although interventions developed specifically for youths are still relatively scarce [ 70 ], interest in developing digital tools specifically for adolescents is also increasing. For example, Woebot Health has developed an intervention for adolescents with mild to moderate depression and anxiety that uses a relational agent to deliver CBT, interpersonal psychotherapy for adolescents, and elements of dialectical behavior therapy. Although results are not yet published, they recently completed an RCT testing this DMHI (ClinicalTrials.gov NCT05486611). Similarly, Limbix developed SparkRx, a DMHI drawing on behavioral activation and CBT designed for adolescents with depression, which has been shown to significantly improve symptoms of depression among adolescents who were engaged consistently with the intervention [ 71 ]. However, both interventions have been developed for adolescents with clinical levels of depression, which offer important support to adolescents struggling with mental illness but do not address the increased burden on mental health services coming from adolescents with less severe or no mental health impairment.

Limitations and Future Directions

One limitation of this design is the lack of an active control group. Although the inclusion of a waitlist control accounts for some threats to internal validity (eg, regression to the mean and maturation), we cannot rule out placebo effects. In particular, some researchers argue there are unique considerations for placebo effects in the context of digital interventions, including participants’ beliefs about technology and how the mobile app is designed [ 72 ]. Research has shown that the impact of digital interventions is typically weaker when compared to active control, though these interventions still appear to outperform attentional controls in terms of depression and anxiety [ 73 ]. Previous research conducted on the adult version of Happify also showed superior effects on depression, anxiety, and resilience compared to an active control [ 49 , 50 ]. Nevertheless, additional research comparing the effects of Happify for Teens to a digital sham condition will be important to rule out any potential placebo effects.

Another limitation of this study was the relative homogeneity of participants, particularly in terms of race and schooling situation. Specifically, our sample was predominantly White and attended school full-time in person. Moreover, all participants in the study were US residents. Consequently, it is possible that our results may not generalize to adolescents from other countries, or effects may differ based on schooling situation or race. In addition, because we required participants to complete the baseline assessment before qualifying for the study, our sample may have included adolescents who were particularly motivated, conscientious, etc. Although this helped to reduce the risk of attrition, these participants may have engaged with the intervention differently than we would see in another, less motivated, sample of adolescents.

Another important consideration is that because we advertised to caregivers and obtained parental consent, our participants may have also differed from the general population in terms of attachment style, quality of relationship with their caregiver, parenting styles, or even the caregiver’s own mental health; all of which could impact the extent to which the adolescent responds to and benefits from the program [ 74 , 75 ]. Research suggests that caregiver perceptions of an adolescent’s mental health as well as their attitudes toward mental health care are more predictive of treatment-seeking among adolescents than the adolescents’ own attitudes;, consequently, caregivers may act as the “gatekeepers” to mental health services [ 76 ]. Therefore, an important step to improving access to mental health support among adolescents may be to identify opportunities to reach those whose caregivers are less supportive. In future research, obtaining a waiver of parental consent may permit accessing those adolescents who are personally interested in DMHIs, but whose caregivers may be less interested or supportive.

Finally, previous research on DMHIs for adolescents is also criticized for a lack of follow-up assessments [ 77 - 79 ]. However, some interventions, including school-based stress management interventions, may have stronger effects over time than immediately after intervention [ 27 ], emphasizing the importance of tracking effects longitudinally. Although this study followed participants for 12 weeks, providing some insight into the longitudinal effects of the intervention, future research should include longer-term follow-up to better ascertain whether effects diminish or strengthen over time. In particular, because rumination can stem from both perceived stress [ 34 ] and loneliness [ 80 ], it is plausible that there could be continued improvements in rumination resulting from the reductions in perceived stress and loneliness. Similarly, additional research assessing the long-term implications of Happify for Teens on other mental or physical health outcomes that are predicted by stress, rumination, and loneliness is needed.

Conclusions

Research suggests that adolescents are experiencing increasing levels of stress, particularly while in school, but few engage in stress management activities [ 15 , 16 ]. Although several stress management interventions have been developed for adolescents, many of these are school-based interventions, and the evidence supporting their effectiveness is mixed [ 27 - 29 ]. Digital interventions may offer more cost-effective and scalable options for addressing important transdiagnostic risk factors in adolescence to promote positive mental health and prevent future dysfunction; however, DMHIs designed specifically for adolescents are rare, particularly those focused on wellness. This study provides promising evidence for the use of a DMHI for addressing perceived stress, brooding, and loneliness in adolescence.

Acknowledgments

The authors would like to thank Acacia Parks and Julia Stafford for their input in planning this study.

Authors' Contributions

EMB was the principal investigator for this study and led research planning as well as writing the paper. HW assisted in the design and implementation of the study. CJM was responsible for implementing and conducting the study. RDH was responsible for data analysis and supported paper writing. SES supported paper writing.

Conflicts of Interest

EMB is a salaried employee of Twill, Inc (the study sponsor) and holds stock options; all other authors (HW, RDH, CJM, and SES) were employees of Twill, Inc while working on this research. However, all authors received salaries that were not contingent on research outcomes.

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Abbreviations

Edited by G Eysenbach; submitted 03.11.23; peer-reviewed by E Bernstein; comments to author 30.11.23; revised version received 15.12.23; accepted 17.02.24; published 29.03.24.

©Eliane M Boucher, Haley Ward, Cynthia J Miles, Robert D Henry, Sarah Elizabeth Stoeckl. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.03.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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2024 Housing Market Forecast and Predictions: Housing Affordability Finally Begins to Turnaround

As we look ahead to 2024 , we see a mix of continuity and change in both the housing market and economy. Against a backdrop of modest economic growth, slightly higher unemployment, and easing inflation longer term interest rates including mortgage rates begin a slow retreat. The shift from climbing to falling mortgage rates improves housing affordability, but saps some of the urgency home shoppers had previously sensed. Less frenzied housing demand and plenty of rental home options keep home sales relatively stable at low levels in 2024, helping home prices to adjust slightly lower even as the number of for-sale homes continues to dwindle. 

Realtor.com ® 2024 Forecast for Key Housing Indicators

Home Prices Dip, Improving Affordability

Home prices grew at a double-digit annual clip for the better part of two years spanning the second half of 2020 through 2022, a notable burst following a growing streak that spanned back to 2012. As mortgage rates climbed, home price growth flatlined, actually declining on an annual basis in early 2023 before an early-year dip in mortgage rates spurred enough buyer demand to reignite competition for still-limited inventory. Home prices began to climb again, and while they did not reach a new monthly peak, on average for the year we expect that the 2023 median home price will slightly exceed the 2022 annual median.

Nevertheless, even during the brief period when prices eased, using a mortgage to buy a home remained expensive. Since May 2022, purchasing the typical for-sale home listing at the prevailing rate for a 30-year fixed-rate mortgage with a 20% down payment meant forking over a quarter or more of the typical household paycheck. In fact, in October 2023, it required 39% of the typical household income and this share is expected to average 36.7% for the full calendar year in 2023. This figure has typically ranged around 21%, so it is well above historical average. We expect that the return to pricing in line with financing costs will begin in 2024, and home prices, mortgage rates, and income growth will each contribute to the improvement. Home prices are expected to ease slightly, dropping less than 2% for the year on average. Combined with lower mortgage rates and income growth this will improve the home purchase mortgage payment share relative to median income to an average 34.9% in 2024, with the share slipping under 30% by the end of the year.

Home Sales Barely Budge Above 2023’s Likely Record Low

After soaring during the pandemic, existing home sales were weighed down in the latter half of 2022 as mortgage rates took off, climbing from just over 3% at the start of the year to a peak of more than 7% in the fourth quarter. The reprieve in mortgage rates in early 2023, when they dipped to around 6%, brought some life to home sales, but the renewed climb of mortgage rates has again exerted significant pressure on home sales that is exacerbated by the fact that a greater than usual number of households bought homes over the past few years, and despite stories of pandemic purchase regret , for the most part, these homeowners continue to be happy in their homes. 

This is consistent with what visitors to Realtor.com report when asked why they are not planning to sell their homes. The number one reason homeowners aren’t trying to sell is that they just don’t need to; concern about losing an existing low-rate mortgage is the top financial concern cited. Our current projection is for 2023 home sales to tally just over 4 million, a dip of 19% over the 2022 5 million total. 

With many of the same forces at play heading into 2024, the housing chill will continue, with sales expected to remain essentially unchanged at just over 4 million. Although mortgage rates are expected to ease throughout the course of the year, the continuation of high costs will mean that existing homeowners will have a very high threshold for deciding to move, with many likely choosing to stay in place.  Moves of necessity–for job changes, family situation changes, and downsizing to a more affordable market–are likely to drive home sales in 2024. 

Shoppers Find Even Fewer Existing Homes For Sale

Even before the pandemic, housing inventory was on a long, slow downward trajectory. Insufficient building meant that the supply of houses did not keep up with household formation and left little slack in the housing market. Both homeowner and rental vacancy remain below historic averages . In contrast with the existing home market, which remains sluggish, builders have been catching up, with construction remaining near pre-pandemic highs for single-family and hitting record levels for multi-family . 

Despite this, the lack of excess capacity in housing has been painfully obvious in the for-sale home market. The number of existing homes on the market has dwindled. With home sales activity to continue at a relatively low pace, the number of unsold homes on the market is also expected to remain low.  Although mortgage rates are expected to begin to ease, they are expected to exceed 6.5% for the calendar year. This means that the lock-in effect, in which the gap between market mortgage rates and the mortgage rates existing homeowners enjoy on their outstanding mortgage, will remain a factor. Roughly two-thirds of outstanding mortgages have a rate under 4% and more than 90% have a rate less than 6%.

Rental Supply Outpaces Demand to Drive Mild Further Decline in Rents

After almost a full year of double-digit rent growth between mid-2021 and mid-2022, the rental market has finally cooled down, as evidenced by the year-over-year decline that started in May 2023 . In 2024, we expect the rental market will closely resemble the dynamics witnessed in 2023, as the tug of war between supply and demand results in a mild annual decline of -0.2% in the median asking rent.

New multi-family supply will continue to be a key element shaping the 2024 rental market.  In the third quarter of 2023, the annual pace of newly completed multi-family homes stood at 385,000 units. Although absorption rates remained elevated in the second quarter, especially at lower price points, the rental vacancy rate ticked up to 6.6% in the third quarter. This uptick in rental vacancy suggests the recent supply has outpaced demand, but context is important. After recent gains, the rental vacancy rate is on par with its level right before the onset of the pandemic in early 2020, still below its 7.2% average from the 2013 to 2019 period.  Looking ahead, the strong construction pipeline– which hit a record high for units under construction this summer –is expected to continue fueling rental supply growth in 2024 pushing rental vacancy back toward its long-run average. 

While the surge in new multi-family supply gives renters options, the sheer number of renters will minimize the potential price impact. The median asking rent in 2024 is expected to drop only slightly below its 2023 level. Renting is expected to continue to be a more budget friendly option than buying in the vast majority of markets, even though home prices and mortgage rates are both expected to dip, helping pull the purchase market down slightly from record unaffordability. 

Young adult renters who lack the benefit of historically high home equity to tap into for a home purchase will continue to find the housing market challenging. Specifically, as many Millennials age past first-time home buying age and more Gen Z approach these years, the current housing landscape is likely to keep these households in the rental market for a longer period as they work to save up more money for the growing down payment needed to buy a first home. This trend is expected to sustain robust demand for rental properties. Consequently, we anticipate that rental markets favored by young adults , a list which includes a mix of affordable areas and tech-heavy job markets in the South, Midwest, and West, will be rental markets to watch in 2024.

Key Wildcards:

• Wildcard 1: Mortgage Rates With both mortgage rates and home prices expected to turn the corner in 2024, record high unaffordability will become a thing of the past, though as noted above, the return to normal won’t be accomplished within the year. This prediction hinges on the expectation that inflation will continue to subside, enabling the recent declines in longer-term interest rates to continue. If inflation were to instead see a surprise resurgence, this aspect of the forecast would change, and home sales could slip lower instead of steadying.
• Wildcard 2: Geopolitics In our forecast for 2023 , we cited the risk of geopolitical instability on trade and energy costs as something to watch. In addition to Russia’s ongoing war in Ukraine, instability in the Middle East has not only had a catastrophic human toll, both conflicts have the potential to impact the economic outlook in ways that cannot be fully anticipated. 
• Wildcard 3: Domestic Politics: 2024 Elections In 2020, amid the upheaval of pandemic-era adaptations, many Americans were on the move. We noted that Realtor.com traffic patterns indicated that home shoppers in very traditionally ‘blue’ or Democratic areas were tending to look for homes in markets where voters have more typically voted ‘red’ or Republican. While consumers also reported preferring to live in locations where their political views align with the majority , few actually reported wanting to move for this reason alone. 

Housing Perspectives:

What will the market be like for homebuyers, especially first-time homebuyers.

First-time homebuyers will continue to face a challenging housing market in 2024, but there are some green shoots. The record-high share of income required to purchase the median priced home is expected to begin to decline as mortgage rates ease, home prices soften, and incomes grow. In 2023 we expect that for the year as a whole, the monthly cost of financing the typical for-sale home will average more than $2,240, a nearly 20% increase over the mortgage payment in 2022, and roughly double the typical payment for buyers in 2020. This amounted to a whopping nearly 37% of the typical household income. In 2024 as modest price declines take hold and mortgage rates dip, the typical purchase cost is expected to slip just under $2,200 which would amount to nearly 35% of income. While far higher than historically average, this is a significant first step in a buyer-friendly direction.

How can homebuyers prepare? 

Homebuyers can prepare for this year’s housing market by getting financially ready. Buyers can use a home affordability calculator , like this one at Realtor.com to translate their income and savings into a home price range. And shoppers can pressure test the results by using a mortgage calculator to consider different down payment, price, and loan scenarios to see how their monthly costs would be impacted. Working with a lender can help potential buyers explore different loan products such as FHA or VA loans that may offer lower mortgage interest rates or more flexible credit criteria. 

Although prices are anticipated to fall in 2024, housing costs remain high, and a down payment can be a big obstacle for buyers. Recent research shows that the typical down payment on a home reached a record high of $30,000 .  To make it easier to cobble together a down payment, shoppers can access information about down payment assistance options at Realtor.com/fairhousing and in the monthly payment section of home listing pages. Furthermore, home shoppers can explore loan products geared toward helping families access homeownership by enabling down payments as low as 3.5% in the case of FHA loans and 0% in the case of VA loans .

What will the market be like for home sellers?

Home sellers are likely to face more competition from builders than from other sellers in 2024. Because builders are continuing to maintain supply and increasingly adapting to market conditions, they are increasingly focused on lower-priced homes and willing to make price adjustments when needed. As a result, potential sellers will want to consider the landscape for new construction housing in their markets and any implications for pricing and marketing before listing their home for sale.

What will the market be like for renters?

In 2024, renting is expected to continue to be a more cost-effective option than buying in the short term even though we anticipate the advantage for renting to diminish as home prices and mortgage rates decline. 

However, for those considering the pursuit of long-term equity through homeownership, it’s essential to not only stay alert about market trends but also to carefully consider the intended duration of residence in their next home. When home prices rise rapidly, like they did during the pandemic, the higher cost of purchasing a home may break even with the cost of renting in as little as 3 years. Generally, it takes longer to reach the breakeven point, typically within a 5 to 7-year timeframe. Importantly, when home prices are falling and rents are also declining, as is expected to be the case in 2024, it can take longer to recoup some of the higher costs of buying a home. Individuals using Realtor.com’s Rent vs. Buy Calculator can thoroughly evaluate the costs and benefits associated with renting versus buying over time and how many years current market trends suggest it will take before buying is the better financial decision. This comprehensive tool can provide insights tailored to a household’s specific rent versus buying decision and empowers consumers to consider not only the optimal choice for the current month but also how the trade-offs evolve over several years.

Local Market Predictions:

All real estate is local and while the national trends are instructive, what matters most is what’s expected in your local market. 

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Online Gambling - Worldwide

• Revenue in the Online Gambling market is projected to reach US$100.90bn in 2024.
• Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 6.20%, resulting in a projected market volume of US$136.30bn by 2029.
• In the Online Gambling market, the number of users is expected to amount to 281.3m users by 2029.
• User penetration will be 6.0% in 2024 and is expected to hit 7.6% by 2029.
• The average revenue per user (ARPU) is expected to amount to US$0.47k.
• In global comparison, most revenue will be generated in the United States (US$23,030.00m in 2024).
• With a projected rate of 69.4%, the user penetration in the Online Gambling market is highest in Canada.

Definition:

Additional Information

• Online casinos such as Tipico games
• Online sports betting such as Bet365
• Online poker rooms such as Pokerstars
• Online lottery such as Lottoland

out-of-scope

• Offline gambling activities such as betshops or land-based casinos
• Illegal gambling websites and activities
• Online trading, investing, or other financial activities that involve a risk of loss

Online Gambling

• Online Sports Betting
• Online Casinos
• Online Lottery
• Analyst Opinion

The Online Gambling market Worldwide is experiencing significant growth due to changing customer preferences and favorable market trends. Customer preferences: Customers are increasingly turning to online gambling platforms for convenience and accessibility. The ability to gamble from the comfort of their own homes, at any time of the day, has made online gambling a popular choice. Additionally, the wide variety of games and betting options available online cater to different customer preferences, attracting a diverse range of players. Trends in the market: One of the key trends in the online gambling market is the rise of mobile gambling. With the increasing penetration of smartphones and the availability of high-speed internet, more and more players are using their mobile devices to access online gambling platforms. This trend has opened up new opportunities for operators to reach a larger customer base and offer a seamless gambling experience on the go. Another trend in the market is the integration of social elements into online gambling platforms. Many operators are incorporating social features such as chat rooms and leaderboards to enhance the interactive nature of online gambling. This not only adds a social aspect to the experience but also encourages player engagement and loyalty. Local special circumstances: Different countries and regions have their own unique circumstances that influence the development of the online gambling market. In some countries, online gambling is fully legalized and regulated, creating a safe and secure environment for players. This regulatory framework attracts both operators and players, driving market growth. However, in other countries, online gambling may be restricted or even illegal. This creates a more challenging operating environment for operators, as they must navigate legal and regulatory barriers. In such cases, players may turn to offshore gambling sites that are not subject to local regulations, leading to a loss of revenue for the local market. Underlying macroeconomic factors: The growth of the online gambling market is also influenced by macroeconomic factors. Disposable income and consumer spending play a significant role in determining the demand for online gambling services. In regions with a strong economy and high disposable income, players are more likely to spend money on online gambling. On the other hand, in regions with economic uncertainty or low disposable income, the demand for online gambling may be lower. Furthermore, technological advancements and infrastructure development also impact the growth of the online gambling market. Access to high-speed internet and reliable payment systems are essential for a seamless online gambling experience. Countries with well-developed digital infrastructure are more likely to see higher adoption of online gambling. In conclusion, the Online Gambling market in Worldwide is driven by changing customer preferences, favorable market trends, local special circumstances, and underlying macroeconomic factors. The rise of mobile gambling, integration of social elements, and regulatory frameworks are shaping the market dynamics. Additionally, disposable income, consumer spending, and technological advancements are important factors that influence market growth.

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• Global Comparison
• Key Market Indicators

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