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What is UX Research: The Ultimate Guide for UX Researchers

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Quantitative vs. qualitative UX research: An overview of UX research methods

UX research is a multi-dimensional process that includes different user research methods and techniques. In this chapter, we provide an overview of the quantitative and qualitative research methods and explain why the best solution uses a mix of both methods.

What are quantitative UX research methods?

Quantitative research is used to collect and analyze numerical data, identify patterns, make predictions, and generalize findings about a target audience or topic. The data is collected indirectly, either through a UX research tool that automatically records it, such as Google Analytics or Maze, or manually by measuring and analyzing UX metrics.

Qualitative UX research made easy

Explore the powers of both quantitative and qualitative research to discover new insights and test final solutions.

Here are some of the most popular quantitative research methods you can use to collect valuable quantitative data:

• Quantitative usability testing collects usability metrics like time on task, error rate, or success rate. You can use this information to keep an eye on your product's UX and make sure it improves over time.
• Web analytics (or app analytics) provides insights into what people actually do in your product. Analytics data can help you monitor your product's performance and identify problems.
• Card sorting is used to discover how people understand and categorize information. Analyzing the percentage of participants who grouped cards in a similar way can help you determine which categories would be understandable to most users.
• Surveys are a great way to gather information about your users' attitudes and behaviors. You can get qualitative data through open-ended feedback or quantitative data by tapping into a larger volume of responses.

Importance of quantitative research methods

Quantitative data provides a foundation for benchmarking and ROI calculations and can help you decide the best performing version of a design or product.

Quantitative UX researchers collect information by measuring actions, thoughts, or attitudes in different ways, such as conducting voluntary surveys and online polls or analyzing log data.

Duyen Mary Nguyen , Quantitative UX Researcher

Quantitative data aims to answer research questions such as ‘what,’ ‘where,’ or ‘when.’ For example, when collecting usability metrics such as task success rates, time on task, completion rates, clicks, conversion rates, and heatmaps, you can measure how well a design performs and spot issues on a page or in the user flow.

One of the advantages of quantitative research is the ability to run studies with large sample sizes and collect statistically relevant data. As opposed to qualitative feedback, which is interpretable by the researcher and subjective, quantitative research is more objective and representative of a broader audience.

I choose quantitative methods if I need to prioritize one solution over the possible alternatives or to validate an idea, wireframe, prototype or even MVP.

Yuliya Martinavichene , User Experience Researcher at Zinio

What are qualitative UX research methods?

Qualitative user research includes research methods like user interviews and field studies and helps you collect qualitative data through the direct observation and study of participants. Qualitative data yields an understanding of the motivations, thoughts, and attitudes of people. This type of research is key to uncovering the ‘why’ behind actions and develop a deep understanding of a topic or problem.

Yuliya Martinavichene , User Experience Researcher at Zinio, highlights: “Since researchers are curious folks, we prefer not only to observe what people are doing by looking at analytics but also to understand the “why” behind the user behavior.”

She compares the process of running a qualitative study to casting a wide lens to identify user behavioral patterns:

Qualitative research methods come into play when you need to discover, understand and empathize with users, and are not conducted only in the exploratory research phase, but iteratively, throughout the whole development process.

There are different qualitative research methods you can employ for your studies, such as user interviews, diary studies , focus groups, card sorting , usability testing , and more. We explore the most common UX research methods in the next chapter.

Choosing the right user research techniques depends on the project and your research goals. Yuliya explains:

In real-life, there is no “Oscar-winning” scenario and the best answer for the eternal question “What user experience research method should you use? is simply an unsatisfactory “It depends!” Different research pain points call for specific methods and approaches.

Yuliya collects qualitative feedback through different methods depending on the goals of the projects. For example, she might conduct walk-throughs with users and asks them to show her around the software she is researching to understand how they currently use the product. Or she may ask research participants to perform everyday tasks to observe their behavior in real-time, such as logging in or out of the platform.

To gather more qualitative insights, Yuliya also checks social media mentions, analyzes blog posts, and reads app store reviews to collect information about the experience users have with the product.

Qualitative research gives you rich insights about the people, product, and the problem you’re researching, and helps you inform decision-making throughout the design and product development process.

Quantitative vs. qualitative research methods

The key differences between quantitative and qualitative research are in the data they deal with and the questions they answer–where quantitative research focuses on numbers and statistics to answer ‘what’, ‘where’ and ‘when’, qualitative research broadly looks to words and meaning for the ‘why’.

Both methods have their merits, and likewise their drawbacks. As we go on to explore, for the most robust and meaningful research, it’s best to use a combination of quantitative and qualitative, but in certain situations, such as challenges due to time or resource constraints, you may decide to use one or the other.

Quantitative research:

• Answers the questions ‘what’, ‘where’ and ‘when’
• Provides a foundation for benchmarking and ROI calculations
• Allows for large sample sizes
• Analyzes numerical data, identifies patterns, makes predictions
• Collected indirectly through UX research tools or metrics

Qualitative research:

• Answers the question ‘why’
• Provides rich insights about the people, the product and the problem
• Allows tight focus on small sample sizes
• Develops a deep understanding of the topic or problem
• Collected through direct observation or study

Balancing qualitative and quantitative UX research

Employ qualitative research to explore ideas and discover new insights, and then tap into quantitative research methods to test a hypothesis or final solution.

While qualitative and quantitative research yields different data types, they are both essential for conducting effective research and getting actionable insights. Not one method can give you a complete picture, so using both in combination is often the best way to ensure you’re making the right product decisions that fit with your business goals.

Qualitative and quantitative research reinforce each other and help to triangulate the research results. You can be surer of the validity of your findings if both qualitative and quantitative approaches produce convergent results.

Usually, the best solution is built using a combination of insight sources. For example, you can kick-off the discovery phase of a project with qualitative research, and run user interviews to understand people’s needs, preferences, and opinions.

After this initial batch of research studies, the product and design team can start building an incipient solution, usually in the form of a low-fidelity prototype or mockups. The initial solution is then tested through interviews and surveys, and the feedback gathered can help you iterate on the solution until final.

Sometimes you want to start with a round of qualitative methods such as interviews, fly-on-the-wall observations, and diary studies to explore the field and follow up with a quantitative study on a larger sample to generalize the results.

Lastly, when you’ve arrived at a final product, doing user testing quantitatively will help you ensure your solution is easy to use, usable, and intuitive for the end-users—and there are no significant issues with the design before going into the development phase. This mix and match of methods is the best way to research and test during the entire design process until arriving at a solution.

Very often, the solution is built on mixed methods–less quantitative versus qualitative–and more somewhere in-between the two.

In the next chapter, we will dive deeper into common types of research you can use such as tree testing, card sorting, and usability studies, and help you choose the right one for you.

Frequently asked questions

What is quantitative UX research?

Quantitative research is a research methodology used to collect and analyze numerical data, identify patterns, make predictions, and generalize findings about a target audience.

What is qualitative UX research?

Qualitative UX research is a research methodology used to answer questions and understand the motivations, thoughts, and attitudes of a target audience.

What are examples of quantitative research methods?

Quantitative user research methods include usability testing, web analytics (or app analytics), card sorting, and surveys.

What are examples of qualitative research methods?

Qualitative user research methods include user interviews, diary studies, focus groups, card sorting, and usability testing.

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Quantitavive UX Research vs. Qualitative — a Comprehensive Guide (2023)

In the ever-evolving realm of user experience (UX) design, research acts as the compass that guides designers towards creating delightful and intuitive digital experiences.

As UX designers, we understand the vital role research plays in uncovering user insights, informing design decisions, and ultimately delivering exceptional products. However, within the expansive field of UX research, two dominant methodologies reign supreme: qualitative and quantitative research.

Qualitative and quantitative approaches each offer distinct lenses through which we can view user behavior, preferences, and needs. Yet, the question often arises: which research methodology should UX designers embrace to extract meaningful insights and optimize their design process?

In this article, we embark on a journey to demystify the complexities of qualitative and quantitative UX research specifically tailored to the discerning minds of UX designers.

What Is Quantitative UX Research

Quantitative UX research is a systematic approach to gathering and analyzing numerical data to gain insights into user behavior and preferences. It involves collecting data on a large scale, often through surveys, experiments, and analytics, with the goal of obtaining statistically significant results.

In quantitative UX research, designers use metrics, measurements, and statistical analysis to quantify user behaviors, attitudes, and opinions. The focus is on generating objective and measurable data that can be analyzed to identify patterns, trends, and correlations.

This data-driven approach provides designers with quantitative evidence to support decision-making throughout the design process.

Quantitative research in UX provides designers with valuable insights into user behavior at scale, helping them make data-informed decisions, identify usability issues, validate design hypotheses, and track the impact of design changes over time.

It complements qualitative research by providing a broader understanding of user preferences and behaviors, allowing designers to make informed decisions based on statistically significant data. Let’s review the various quantitative ux research methods.

Quantitative UX Research Methods

There are several quantitative UX research methods that designers can employ to gather data and insights. Here are some commonly used quantitative methods in the field of UX:

• Surveys: Surveys are one of the several quantitative research methods. It involves collecting data from a large number of participants using structured questionnaires. They can be administered online or in person and are useful for gathering information on user preferences, satisfaction, demographics, and more.
• A/B Testing: A/B testing -one of the most common quantitative user research methods- compares two or more variations of a design element or feature to determine which performs better based on predefined metrics. It allows designers to test hypotheses, evaluate design choices, and optimize user experiences.
• Analytics and User Tracking: Utilizing web analytics tools or tracking software, designers can gather quantitative data on user behavior within a digital product. Metrics such as click-through rates, page views, time spent on pages, or conversion rates provide insights into user engagement and interactions.
• Behavioral Analysis: Behavioral analysis involves studying large-scale user behavior data to identify patterns and trends. This can include analyzing user flows, funnels, drop-off points, or frequency of interactions to gain insights into user journeys and optimize the user experience.
• Task Performance Metrics: Task performance metrics measure specific aspects of user performance, such as task completion time, error rates, or efficiency. These metrics provide quantitative data on the usability and effectiveness of a design and can help identify areas for improvement.
• Eye Tracking: Eye tracking technology is used to measure and analyze where users look on a screen or interface. It provides quantitative data on visual attention, gaze patterns, and heat maps, which can inform design decisions related to visual hierarchy, information placement, and visual cues.
• Clickstream Analysis: Clickstream analysis involves analyzing the sequence of user actions and interactions within a digital product. It helps identify navigation patterns, user flows, and areas of interest or concern.
• Quantitative Interviews: In quantitative interviews, researchers use a structured interview format to ask predefined questions to participants. The responses are quantified and analyzed for statistical trends and patterns.

These are just a few examples of quantitative UX research methods. Each method has its strengths and limitations, and the choice of methods depends on the research objectives, the target audience, and the available resources.

Often, a combination of qualitative and quantitative research methods can provide a more comprehensive understanding of the user experience.

Expert Considerations to Effectively Do Quantitative UX Research

Quantitative UX reasearch and successfuly interpreting quantitative metrics requires certain aspects that every UX researcher must keep in mind.

1. Plan for high-quality and relevant quantitative UX data

Proper interpretation of quantitative UX metrics starts before gathering any data. There are overarching questions that practitioners need to ask to keep on track and make sound interpretations. 

Some questions to consider are: What are the goals and objectives of the quantitative research you are gathering? What research questions are attempting to be answered with quantitative UX metrics? What methods will be used to interpret data? Who are the stakeholders who will use the data? 

Investing the time to define and answer these questions allow UX researchers to focus on highly relevant metrics to goals and objectives. 

2. Focus on UX-related metrics and not business metrics

There can be an overwhelming amount of metrics for business analytics. So the first step is to narrow it down so that time isn’t wasted focusing on irrelevant data to UX. 

Pro tips: understand UX Metrics versus KPIs. 

UX Metrics are quantitative data used to measure, compare, and track users’ experience interacting with a digital product over time. These are associated with user behaviors and attitudes. KPIs (key performance indicators) are quantitative data used to measure, compare, and track the overall goals. These goals typically are tied to revenue, growth, retention, and user counts. 

It is essential to focus on UX data that aligns with your goals and objectives for research.

3. Have a streamlined data wrangling process in place

A critical part of the quantitative data interpretative process is ensuring data is reliable before analyzing and leveraging it for insights. At this junction is where data wrangling (the process of discovering, structuring, cleaning, enriching, validating, and publishing the data) comes in. This process can be very lengthy and time-consuming. 

Data professionals spend as much as 80% of their time preparing data for analysi s. UX professionals cannot afford this much of their time to be sucked up in cleaning and organizing data. But suppose your research operations have streamlined processes for how to wrangle data. In that case, this saves a lot of time and removes the risk of gleaning insights and making interpretations from incomplete, unreliable, or inconsistent data.

4. Use storytelling to communicate findings

Data visualization is an art. And explaining data visuals is a craft. Not many can do these two things well. This is why storytelling is such a powerful skill. Graphs and charts are great, but if a researcher cannot tell a story to explain the data, the findings have minimal impact on business decisions. Additionally, people, including business leaders, are moved by stories.

It is essential to know how to choose the right data visualization type. Generally, there are four goals for data visualization types: 1. showing relationships, 2. showing distribution, 3. showing the composition, or 4. making comparisons. 

Asking the following questions will help you define the best visualization type for the right audience: 

• What is the story you want to tell?
• Who is the audience you want to tell the story to?
• Do we want to analyze trends?
• Do we want to demonstrate composition?
• Do we want to compare two or more sets of values?
• Do we want to show changes over time?
• How will we show UX Metrics?

Once these questions are answered, it becomes easier to decide if a pie chart, a line chart, a spider chart, a bar chart, or a scatter plot is the best visualization type to tell the user experience story.

5. Synthesize your insights and draw valuable conclusions

Now comes the moment where the synthesis of quantitative UX metrics data serves as a change agent for the user experience. Extract facts from the data. Remain objective by being aware of the pitfalls previously discussed. And make interpretations of the data. The goal is to generate valuable recommendations. 

Good recommendations are:

• Constructive. They offer a solution rather than focusing on the problem revealed by the data.
• Specific. They identify wherein the user experience recommendations are most applicable.
• Actionable. Suggestions should be active. Use language that is active rather than passive to inspire change. 
• Concise. Plenty of recommendations can be generated from any given set of UX data, but not all of them will significantly impact the user experience. Prioritize the most important ones. 
• Measurable. Good recommendations can be measured so that there can be evidence a change has occurred and an impact has been made.
• Balanced. Identify both the strengths and weaknesses.

What is Qualitative UX Research

Qualitative UX research is an investigative approach that focuses on gathering rich, descriptive insights and understanding the subjective experiences, attitudes, and motivations of users.

Unlike quantitative research, qualitative research aims to uncover the “why” behind user behavior rather than focusing solely on numerical data.

Qualitative UX research methods involve observing and engaging with users in a more open-ended and exploratory manner, allowing for in-depth exploration of user perspectives.

This type of research provides designers with a deep understanding of user needs, pain points, and aspirations, which can inform design decisions and drive empathy-driven solutions.

Qualitative research allows designers to gain a deeper understanding of user needs, motivations, and emotions. It helps uncover nuances, user pain points, and opportunities for improvement that quantitative data alone may not reveal.

By leveraging qualitative insights, designers can generate empathy, enhance user engagement, and create user-centered experiences that address real user challenges.

It’s worth noting that qualitative and quantitative research are often used together in a complementary manner, with qualitative research providing a foundation for hypothesis generation and quantitative research validating and measuring the impact of design decisions.

Qualitative research methods in UX

Qualitative research methods focus on gathering rich, in-depth insights into user experiences, attitudes, and motivations.

These qualitative user research methods allow designers to understand the “why” behind user behavior and provide valuable context for design decisions. Here are some commonly used qualitative research methods in UX:

• User Interviews: These qualitative methods require one-on-one or group interviews with participants to gather detailed information about their experiences, behaviors, needs, and goals. These interviews can be structured or semi-structured, allowing for open-ended discussions.
• Contextual Inquiry: Observe users in their natural environment while they engage with a product or service. This method provides insights into how users interact with a design in real-life situations, uncovers pain points, and identifies opportunities for improvement.
• Diary Studies: Ask participants to keep a diary or journal to record their experiences, thoughts, and behaviors over a specific period. Diary studies provide longitudinal insights into users’ lives, allowing designers to understand their daily routines, challenges, and emotional responses.
• Usability Testing with Think Aloud: A solid approach is to observe users as they perform tasks while verbalizing their thoughts and impressions. This method provides real-time insights into users’ decision-making processes, frustrations, and successes during the interaction with a design.
• Focus Groups: Facilitate group discussions with participants to explore shared experiences, opinions, and perceptions. Focus groups encourage participants to build upon each other’s ideas, generate insights, and identify common themes or patterns.
• Card Sorting: Engage users in organizing and categorizing information by asking them to sort and group items into meaningful categories. This method helps designers understand users’ mental models and how they perceive and organize information.
• Cognitive Walkthroughs: Walk through a design or prototype with participants while they share their thoughts and decision-making process. Cognitive walkthroughs help identify potential usability issues and gaps in user understanding.
• Ethnographic Research: Conduct in-depth, immersive studies in users’ natural environments over an extended period. Ethnographic research allows designers to deeply understand users’ cultural context, behaviors, and needs.
• Emotional Mapping: Use techniques such as user diaries, interviews, or visual exercises to explore users’ emotional responses and associations with a product or service. Emotional mapping helps designers create emotionally resonant experiences.
• Prototype Testing and Iteration: One of the several qualitative methods is tp share low-fidelity or high-fidelity prototypes with users and gather their feedback through observations, interviews, or usability testing. Prototyping allows designers to validate ideas, refine designs, and iterate based on user insights.

These qualitative research methods provide rich data and insights that go beyond numbers and metrics, helping designers gain a deep understanding of users’ experiences, perceptions, and needs. Combining different methods can offer a comprehensive view of user perspectives and inform user-centered design decisions.

When conducting quantitative UX research, there are several expert considerations to keep in mind to ensure the effectiveness of your study. Here are some key considerations.

1. Clearly define research objectives

Begin by defining clear and specific research objectives. Clearly articulate what you aim to achieve through your quantitative research and what specific questions you want to answer. This will guide your study design and data analysis.

2. Use validated measurement instruments

When selecting or creating measurement instruments such as surveys or questionnaires, use established and validated tools whenever possible. Validated instruments have been rigorously tested for reliability and validity, ensuring the accuracy and consistency of the data collected.

3. Pay attention to sampling and avoid bias in data collection

Ensure that your sample is representative of your target population or user group. Consider factors such as demographics, user characteristics, or usage patterns when selecting participants. A well-designed sampling strategy is crucial for the generalizability and validity of your findings.

Also, take steps to minimize bias in data collection. Provide clear instructions to participants, use neutral language, and avoid leading questions that may influence their responses. Additionally, consider factors such as the order of questions or the presentation of stimuli to mitigate potential biases.

4. Collect sufficient data

Ensure that your sample size is adequate to achieve statistical significance. Power analysis can help determine the appropriate sample size based on the effect size you expect to detect, the desired level of confidence, and statistical power.

5. Use appropriate statistical analysis and consider mixed methods

Choose appropriate statistical methods to analyze your quantitative data. Descriptive statistics, inferential statistics (e.g., t-tests, ANOVA, regression), and correlation analysis are common techniques used in quantitative UX research. Consult with a statistician if needed to ensure the accuracy and validity of your analysis.

Also, consider combining quantitative data with qualitative insights to gain a more comprehensive understanding. Integrating qualitative data can provide valuable context and shed light on the “why” behind quantitative findings, enriching the interpretation of your results.

6. Interpret results within context and communicate findings effectively

Interpret your quantitative findings in the context of your research objectives, user behavior, and broader UX considerations. Avoid drawing overly simplistic or misleading conclusions and consider alternative explanations or factors that may influence the results.

Also, present your quantitative findings in a clear and concise manner, using visualizations and data summaries that are easily understandable to both technical and non-technical stakeholders. Clearly communicate limitations and uncertainties associated with the research findings.

7. Iterate and refine

Remember that quantitative UX research is an iterative process. Continuously refine your research methods based on feedback, learnings, and new insights gained. Use findings to inform design iterations and further research efforts.

For UX practitioners, the volume of quantitative data available in today’s digital world is vast. And correctly interpreting quantitative UX metrics can be a daunting task. While it’s worth investing in highly technical skills, often, it’s more about processes that enable sound interpretations of UX metrics. The key is to remain objective, focus on relevant data, have simplified procedures for data cleaning and analysis, tell a good story with said data, and draw valuable conclusions to improve the user experience. Interpreting quantitative UX metrics is more about the process than sophistication in statistical knowledge (some tools take care of this). The goal is to have simplified, focused, and repeatable processes.

Interested in UX Testing?

Data visualizations, about the author: huyen hoang.

Huyen Hoang is a User Experience Researcher at Codelitt . Codelitt helps companies create better product experiences for their users by designing and building people-driven solutions with the speed, technology, and innovation of a startup.

About the Author: Collaborations

As collaborators, they contribute thoughtful and inspiring content that covers various aspects of the UX space, including emerging trends, best practices, and practical tips. Their articles are designed to help readers stay up-to-date with the latest developments in UX, as well as improve their own skills and knowledge in the field.

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Table of Contents

A complete guide to qualitative vs quantitative ux research methods.

How can we build this product?

What can we do to improve this product?

Why are the conversion rates so low?

These are some of the burning questions that every organization faces. In today’s competitive world, understanding consumer behaviour is the quintessential ingredient for the recipe of success.

After all, users are at the heart of any experience of a product, and up to 90% of users are reported to leave using an application due to bad performance. Billions of dollars can be lost when businesses do not prioritize UX Research and turn to the guesswork game.

What is UX Research?

Also known as user experience research, it involves the study of user needs and preferences. While developing any product, platform, or service, it is imperative to understand the user's behaviour. With the help of UX Research, businesses can understand the different aspects of product development and customize it in a way that aligns with the user's needs. This process also helps in improving the product.

With the growing complexities of consumer demand and the rising need for customized products, understanding these changing trends is the need of the hour. One of the ways is to research and analyse consumer behaviour that can help in boosting experience, thus driving conversion.

Studies have proved that a good user experience can be rewarding to companies . Hence, companies are now actively investing in harnessing the power of UX Research. Moreover, with this surge of new technologies like ML and AI, it has become easier to understand the nuances of consumer preferences, thus ensuring better products and services.

  UX research has two subsets:

• Qualitative Research
• Quantitative Research

Qualitative and quantitative research methods are both crucial in understanding user experience (UX) that translates into informed design decisions. Each method offers unique insights and benefits, and often, they are used together to provide a comprehensive understanding of user needs and behaviours. 

This blog takes you through both these concepts and will unfold its key features and applications.

What is Quantitative Research in UX?

‍ Source: Image of Quantitative Research in UX

As the name highlights, this method of UX research focuses on tangible parameters to understand human behavior and assess the usability of a product. The focus of quantitative research in UX is to collect quantifiable data from a large sample and use it to analyze the trends in the market.

To measure user behaviour, preferences, choices, and experiences by analyzing numerical data.

It gives answers to questions such as "what" and "how much." For example:

What percentage of users were able to complete the task in under 2 minutes?

How many errors did the users face while completing this task?

Key Features of Quantitative Research in UX

Data collection.

Collecting data is a critical aspect of quantitative research. Hence, the researchers deploy different methods like surveys, A/B testing, and others to collect the data. This data is usually in the form of clicks or time spent on a webpage or product or satisfaction rates.

Focus on Measurable Data

The focus of this method is on collecting quantifiable data from a large set, such that this information can be analyzed and help in deriving accurate results.

Since quantitative research depends on measurable data, the results are more authentic and give substantial support for a change or improvement.

Large sample sizes

The method focuses on a larger sample size, which ensures that the results are statistically significant. Hence, we can generalize the results to the whole population.

‍Limitations of Quantitative Research in UX

Although quantitative research in UX can help in giving measurable outcomes, it cannot provide support for why the consumer is behaving in a particular way. To get a more sustainable proof, it is important to follow a combined strategy of using qualitative research methods.

It lacks the depth and context that the insights generated from the qualitative UX research bring to the table.Overall, quantitative research is a powerful tool for UX professionals.

By using data to measure user behaviour, you can create products that are not only useful but also enjoyable to use.

Some of the Common Quantitative UX Research Methods

Here's a breakdown of some popular quantitative UX research methods, including their descriptions, features, and examples:

This helps in gathering feedback through structured questions to quantify the preferences, opinions, or experiences of users with a product. However, it is important to mention that this method can also be used in qualitative testing based on the kind of questions it asks. For example, close-ended questions can be a part of the quantitative research method. Conversely, open-ended surveys allow users to provide detailed, narrative responses to gather their feedback and understand their sentiments, thus falling in the category of qualitative research.

• It focuses on a large audience
• The data points are measurable and hence is easy to analyze
• It helps in measuring user satisfaction with a new product, service, or website design
• Understand the interests of the consumer
• Tracking the consumer behaviour pertaining to a particular design

2. A/B testing

This compares two or more design variations to determine which performs better (leading to higher user engagement or conversion rates).

• It highlights the impact of specific design changes.
• Optimize user experience based on real user behaviour.
• Quantify the improvement in conversion rates or other metrics.
• Test two different headlines on a landing page to see which one drives more clicks.
• Compare two checkout form designs to see which one reduces cart abandonment rates.
• Experiment with different button colours to see which one gets more users to sign up.

3. Website Analytics

Understanding website analytics can unfold several patterns, like user behaviour on the website, engagement rate, clicks, and conversion rates. All these insights can help highlight trends and patterns.

• Get a detailed insight into the website traffic.
• Identify user engagement
• Highlights the popular trend on the website
• Assess the effectiveness of marketing campaigns.
• Find out the bounce rate of different web pages
• Highlight the popular content amongst the user

These are some of the common quantitative research methods. Using them, the researcher can gain valuable insights into consumer behavior that can help in improving the overall experience.‍

What is Qualitative Research in UX?

Source: Image of Qualitative Research in UX

Unlike quantitative research, qualitative research in UX design focuses on understanding the reason behind the consumer's behaviour or preference.

It focuses on collecting descriptive and non-numerical data points such as the motivation behind the purchase decision, the need, and the thought process of the consumers. Analogous to quantitative research, the qualitative methods force the subjective experience of the user.

To find out the underlying motivations, emotions, and perceptions of users.

It gives answers to questions such as "why" and "how." For example:

What challenges did the user face while signing up?

(This answers the question: Why the user took a longer time to sign up/ couldn't sign up)

What improvements could improve your experience of the app?

(This answers the question: How can we improve the user experience of the app)

Key Features of Qualitative Research in UX:

Focus on the "why".

As mentioned above, quantitative research deals with numbers, but qualitative research focuses on addressing the why behind the behavior of consumers. It helps the researcher understand the thought processes and emotions that drive the decisions of the consumers.

Uncover User Needs and Experiences

The qualitative research method helps to understand the needs of the consumers. It also sheds light on the challenges and overall experience of the consumers, which eventually helps build a product or service that is in coherence with the demands of the consumers. It relies on various methods like usability testing and interviews to gather this information.

In-depth Exploration

Understanding the nuances of consumer behavior is the foundation of qualitative research in UX. Focusing on smaller and more targeted users helps the researcher unfold the depth of a specific topic and gain detailed insight.

Flexibility

While using the qualitative research methods in UX, the researchers have flexibility in their approach.

Sample Size

The sample size is much smaller, typically till the saturation point, where the responses from the participants get repetitive. According to the NN Group, the recommended sample size so far has been between 5 to 50. The relatively smaller sample size allows for an in-depth exploration of user experiences.

Data Analysis

Thematic analysis, content analysis, or qualitative coding are used to identify the patterns, themes, and insights from the data collected.

Some of the Common Qualitative UX Research Method

Qualitative UX research methods help you understand the "why" behind user behavior. Here's a breakdown of some popular methods, including their descriptions, features, and examples:

1. User Interviews

This involves one-on-one conversations with users to understand their preferences, motivations, and experiences.

• Get in-depth insight into the user needs
• Highlight the reason behind user behavior
• Gain rich, detailed insights into user needs and motivations.
• Uncover unspoken thoughts and feelings that might not appear in surveys.
• Tailor questions to specific user segments.
• Interviewing e-commerce shoppers to understand their purchase decision process.
• Talking to new mobile app users to identify onboarding pain points.
• Discussing users' mental models for a complex software program.

2. Usability Testing

This involves observing the users as they interact with the product to find usability issues and gather feedback.

• Get first-hand information on how the user interacts with the designs
• Find out if the user is facing any confusion while using the website
• Testing the checkout flow of potential customers
• Watch how the user is completing a particular task within the app

3. Focus Group

This brings together a small group of participants to discuss their attitudes and perceptions regarding a product.

• Gain insights from group dynamics and user interactions.
• Identify common themes and concerns among a specific user segment.
• Spark new ideas and areas for exploration based on user feedback.
• Conducting a focus group with new parents to understand their needs for a baby monitoring app.
• Gathering feedback from experienced gamers on a new game concept.
• Discussing user expectations and pain points related to a new financial service platform.

By using these qualitative methods, UX researchers can build a comprehensive understanding of user needs, motivations, and behaviors.

Limitation of Qualitative UX Research Method

Such insights cannot be statistically validated and generalized to the larger population.

Summary of Qualitative Research vs Quantitative Research Methods

Qualitative UX Research

Quantitative UX Research

Type of Data

Focuses on non-numerical data.

Measurable and tangible data.

In-depth understanding

More generalized approach

Method of Data Collection

Interview, Focus Group, Usability Testing.

Surveys, A/B Testing, Website Analytics

Gives the reason behind the consumer behaviour and also highlights the user perception and motivation behind the decision.

Gives statistical validity and tangible reasons to support the decision and highlights the trend and patterns.

Limitations

It gives a more subjective outcome, and the process is time-consuming.

This method lacks depth and is not able to highlight the nuances of consumer behaviour. Also, there is a possibility of data biases.

Final Verdict: Qualitative vs Quantitative Research, Which is Better?

Both quantitative and qualitative research in UX have their pros and cons, offering the researcher different options. The right approach would be following mixed-methods research.

It is necessary for companies to recognize which methodology will be the most beneficial to their product success by asking the right questions. When successful UX research is conducted, it can lead to products and experiences that resonate with the diverse needs and stories of your users and user journey.

Level-up Your UX research with Alien!

At The Alien Design, we take the design experience and virtual presence a notch above. Our team of creative minds is always bubbling with new ideas and follows an innovative approach that converts your vision into reality.

Our approach of blending together innovativeness, creatively, and technical excellence provides outstanding results every time.  Connect with our UX experts today!

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What is the goal of quantitative research in UX?

The goal of quantitative research in UX is to measure user behavior, preferences, choices, and experiences by analyzing numerical data.

What types of questions does quantitative research answer?

Quantitative research provides answers to questions such as "what" and "how much." For example, it can determine the percentage of users able to complete a task in under a certain time frame or the number of errors users face during a task.

What are some common methods used in quantitative UX research?

Common methods include surveys, A/B testing, and behavioral data analysis. Surveys gather feedback through structured questions, A/B testing compares design variations, and behavioral data analysis examines user actions within a digital product.

What is the goal of qualitative research in UX?

The goal of qualitative research in UX is to uncover the underlying motivations, emotions, and perceptions of users.

How does qualitative research differ from quantitative research in terms of sample size and data analysis?

Qualitative research typically involves a smaller sample size compared to quantitative research, allowing for in-depth exploration. Data analysis in qualitative research focuses on identifying patterns, themes, and insights through methods such as thematic analysis or content analysis.

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The Complete Guide to UX Research Methods

UX research provides invaluable insight into product users and what they need and value. Not only will research reduce the risk of a miscalculated guess, it will uncover new opportunities for innovation.

By Miklos Philips

Miklos is a UX designer, product design strategist, author, and speaker with more than 18 years of experience in the design field.

PREVIOUSLY AT

“Empathy is at the heart of design. Without the understanding of what others see, feel, and experience, design is a pointless task.” —Tim Brown, CEO of the innovation and design firm IDEO

User experience (UX) design is the process of designing products that are useful, easy to use, and a pleasure to engage. It’s about enhancing the entire experience people have while interacting with a product and making sure they find value, satisfaction, and delight. If a mountain peak represents that goal, employing various types of UX research is the path UX designers use to get to the top of the mountain.

User experience research is one of the most misunderstood yet critical steps in UX design. Sometimes treated as an afterthought or an unaffordable luxury, UX research, and user testing should inform every design decision.

Every product, service, or user interface designers create in the safety and comfort of their workplaces has to survive and prosper in the real world. Countless people will engage our creations in an unpredictable environment over which designers have no control. UX research is the key to grounding ideas in reality and improving the odds of success, but research can be a scary word. It may sound like money we don’t have, time we can’t spare, and expertise we have to seek.

In order to do UX research effectively—to get a clear picture of what users think and why they do what they do—e.g., to “walk a mile in the user’s shoes” as a favorite UX maxim goes, it is essential that user experience designers and product teams conduct user research often and regularly. Contingent upon time, resources, and budget, the deeper they can dive the better.

What Is UX Research?

There is a long, comprehensive list of UX design research methods employed by user researchers , but at its center is the user and how they think and behave —their needs and motivations. Typically, UX research does this through observation techniques, task analysis, and other feedback methodologies.

There are two main types of user research: quantitative (statistics: can be calculated and computed; focuses on numbers and mathematical calculations) and qualitative (insights: concerned with descriptions, which can be observed but cannot be computed).

Quantitative research is primarily exploratory research and is used to quantify the problem by way of generating numerical data or data that can be transformed into usable statistics. Some common data collection methods include various forms of surveys – online surveys , paper surveys , mobile surveys and kiosk surveys , longitudinal studies, website interceptors, online polls, and systematic observations.

This user research method may also include analytics, such as Google Analytics .

Google Analytics is part of a suite of interconnected tools that help interpret data on your site’s visitors including Data Studio , a powerful data-visualization tool, and Google Optimize, for running and analyzing dynamic A/B testing.

Quantitative data from analytics platforms should ideally be balanced with qualitative insights gathered from other UX testing methods , such as focus groups or usability testing. The analytical data will show patterns that may be useful for deciding what assumptions to test further.

Qualitative user research is a direct assessment of behavior based on observation. It’s about understanding people’s beliefs and practices on their terms. It can involve several different methods including contextual observation, ethnographic studies, interviews, field studies, and moderated usability tests.

Jakob Nielsen of the Nielsen Norman Group feels that in the case of UX research, it is better to emphasize insights (qualitative research) and that although quant has some advantages, qualitative research breaks down complicated information so it’s easy to understand, and overall delivers better results more cost effectively—in other words, it is much cheaper to find and fix problems during the design phase before you start to build. Often the most important information is not quantifiable, and he goes on to suggest that “quantitative studies are often too narrow to be useful and are sometimes directly misleading.”

Not everything that can be counted counts, and not everything that counts can be counted. William Bruce Cameron

Design research is not typical of traditional science with ethnography being its closest equivalent—effective usability is contextual and depends on a broad understanding of human behavior if it is going to work.

Nevertheless, the types of user research you can or should perform will depend on the type of site, system or app you are developing, your timeline, and your environment.

Top UX Research Methods and When to Use Them

Here are some examples of the types of user research performed at each phase of a project.

Card Sorting : Allows users to group and sort a site’s information into a logical structure that will typically drive navigation and the site’s information architecture. This helps ensure that the site structure matches the way users think.

Contextual Interviews : Enables the observation of users in their natural environment, giving you a better understanding of the way users work.

First Click Testing : A testing method focused on navigation, which can be performed on a functioning website, a prototype, or a wireframe.

Focus Groups : Moderated discussion with a group of users, allowing insight into user attitudes, ideas, and desires.

Heuristic Evaluation/Expert Review : A group of usability experts evaluating a website against a list of established guidelines .

Interviews : One-on-one discussions with users show how a particular user works. They enable you to get detailed information about a user’s attitudes, desires, and experiences.

Parallel Design : A design methodology that involves several designers pursuing the same effort simultaneously but independently, with the intention to combine the best aspects of each for the ultimate solution.

Personas : The creation of a representative user based on available data and user interviews. Though the personal details of the persona may be fictional, the information used to create the user type is not.

Prototyping : Allows the design team to explore ideas before implementing them by creating a mock-up of the site. A prototype can range from a paper mock-up to interactive HTML pages.

Surveys : A series of questions asked to multiple users of your website that help you learn about the people who visit your site.

System Usability Scale (SUS) : SUS is a technology-independent ten-item scale for subjective evaluation of the usability.

Task Analysis : Involves learning about user goals, including what users want to do on your website, and helps you understand the tasks that users will perform on your site.

Usability Testing : Identifies user frustrations and problems with a site through one-on-one sessions where a “real-life” user performs tasks on the site being studied.

Use Cases : Provide a description of how users use a particular feature of your website. They provide a detailed look at how users interact with the site, including the steps users take to accomplish each task.

You can do user research at all stages or whatever stage you are in currently. However, the Nielsen Norman Group advises that most of it be done during the earlier phases when it will have the biggest impact. They also suggest it’s a good idea to save some of your budget for additional research that may become necessary (or helpful) later in the project.

Here is a diagram listing recommended options that can be done as a project moves through the design stages. The process will vary, and may only include a few things on the list during each phase. The most frequently used methods are shown in bold.

Reasons for Doing UX Research

Here are three great reasons for doing user research :

To create a product that is truly relevant to users

• If you don’t have a clear understanding of your users and their mental models, you have no way of knowing whether your design will be relevant. A design that is not relevant to its target audience will never be a success.

To create a product that is easy and pleasurable to use

• A favorite quote from Steve Jobs: “ If the user is having a problem, it’s our problem .” If your user experience is not optimal, chances are that people will move on to another product.

To have the return on investment (ROI) of user experience design validated and be able to show:

• An improvement in performance and credibility
• Increased exposure and sales—growth in customer base
• A reduced burden on resources—more efficient work processes

Aside from the reasons mentioned above, doing user research gives insight into which features to prioritize, and in general, helps develop clarity around a project.

What Results Can I Expect from UX Research?

In the words of Mike Kuniaysky, user research is “ the process of understanding the impact of design on an audience. ”

User research has been essential to the success of behemoths like USAA and Amazon ; Joe Gebbia, CEO of Airbnb is an enthusiastic proponent, testifying that its implementation helped turn things around for the company when it was floundering as an early startup.

Some of the results generated through UX research confirm that improving the usability of a site or app will:

• Increase conversion rates
• Increase sign-ups
• Increase NPS (net promoter score)
• Increase customer satisfaction
• Increase purchase rates
• Boost loyalty to the brand
• Reduce customer service calls

Additionally, and aside from benefiting the overall user experience, the integration of UX research into the development process can:

• Minimize development time
• Reduce production costs
• Uncover valuable insights about your audience
• Give an in-depth view into users’ mental models, pain points, and goals

User research is at the core of every exceptional user experience. As the name suggests, UX is subjective—the experience that a person goes through while using a product. Therefore, it is necessary to understand the needs and goals of potential users, the context, and their tasks which are unique for each product. By selecting appropriate UX research methods and applying them rigorously, designers can shape a product’s design and can come up with products that serve both customers and businesses more effectively.

Further Reading on the Toptal Blog:

• How to Conduct Effective UX Research: A Guide
• The Value of User Research
• UX Research Methods and the Path to User Empathy
• Design Talks: Research in Action with UX Researcher Caitria O'Neill
• Swipe Right: 3 Ways to Boost Safety in Dating App Design
• How to Avoid 5 Types of Cognitive Bias in User Research

Understanding the basics

How do you do user research in ux.

UX research includes two main types: quantitative (statistical data) and qualitative (insights that can be observed but not computed), done through observation techniques, task analysis, and other feedback methodologies. The UX research methods used depend on the type of site, system, or app being developed.

What are UX methods?

There is a long list of methods employed by user research, but at its center is the user and how they think, behave—their needs and motivations. Typically, UX research does this through observation techniques, task analysis, and other UX methodologies.

What is the best research methodology for user experience design?

The type of UX methodology depends on the type of site, system or app being developed, its timeline, and environment. There are 2 main types: quantitative (statistics) and qualitative (insights).

What does a UX researcher do?

A user researcher removes the need for false assumptions and guesswork by using observation techniques, task analysis, and other feedback methodologies to understand a user’s motivation, behavior, and needs.

Why is UX research important?

UX research will help create a product that is relevant to users and is easy and pleasurable to use while boosting a product’s ROI. Aside from these reasons, user research gives insight into which features to prioritize, and in general, helps develop clarity around a project.

• UserResearch

Miklos Philips

London, United Kingdom

Member since May 20, 2016

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Using Quantitative and Qualitative Research in UX Design

UX designers often get stuck focusing on the wrong things.

They focus on details like the latest Figma techniques without understanding the bigger picture.

This poses a challenge to businesses and stakeholders. Because at the end of the day, they have targets to achieve.

They need team members (designers included) who know this and deliver output to make this happen.

And that starts with a UX research strategy.

An important step is uncovering the insights from two types of research: quantitative (which tells us "what" people do) and qualitative (which explains "why" they do it).

This guide will explain each kind of research and how they are used in UX research.

On its own, however, it won't get anywhere. Its value lies in knowing how to apply it in the real world.

In our UX research course , learn the exact processes and tactics that Michael Wong (Mizko) used to help build a UX agency that generated over $6 million in revenue.

What is quantitative research in UX design

Quantitative research focuses on gathering and evaluating numerical data. The goal is to identify trends, calculate averages, or find connections between data points.

For example, Google Analytics uses quantitative research to monitor the total number of site visits, inquiry counts, and bounce rates. With this data, you get insights into how users behave on your site and how it's performing.

Quantitative research in UX: Knowing when and why use it

Quantitative research can be super helpful at different stages, mainly because it gives you solid numbers to work with.

Here's why it's important in your UX research:

1. You'll spot trends or patterns

Before diving into the nitty-gritty details of your design, you might want to get a general sense of user behavior or preferences.

Example: For example, you could use surveys to determine what features users want the most or analyze website traffic to see where users spend their time. ‍

2. Test your concepts and assumptions

Once you have some design ideas or changes in mind, quantitative research can test if those ideas resonate with a wider audience.

Example:  This is where A/B testing comes in handy. You might create two versions of a page and see which one performs better in terms of clicks, engagement, or conversions. ‍

3. Validate or refine your designs

After implementing your designs, you’ll want to know if they match your desired results. It also helps pinpoint usability issues.

Example: Use Google Analytics or other analytics tools to track conversions and engagements to assess if your product meets your objectives.

Types of quantitative research methods in UX design

Let's explore the common quantitative research methods in UX:

1. Usability testing (Benchmarking)

• What is it: This method measures the usability of a product by quantifying user performance on specific tasks. Sample metrics include task success rate, time to complete a task, and error rate.
• Best used for: A starting point for usability and tracking progress over time. It's useful for objectively evaluating how design changes affect usability.
• Tools: Zoom, Maze.co , and Optimal Workshop. ‍

2. Web or app analytics

• What is it: Software that tracks and analyzes how users interact with a website or app. You can see what features people use the most, where they spend their time, and where they drop off.
• Best used for: Understanding user behavior on a large scale. It's great for spotting trends and patterns in how users navigate and interact with your product.
• Tools: Google Analytics, PostHog, MixPanel, Amplitude, FullStory, and HotJar. ‍

3. Visual heatmaps

• What is it: Mouse heatmaps show where users click, move their mouse, or scroll on a page. Radar-like color coding is used to indicate areas of high and low activity.
• Best used for: Visualizing user engagement and interest on specific webpage or app screen sections. It helps identify which areas attract the most attention and which are ignored.
• Tools: FullStory and Hotjar. ‍

4. Funnel analysis

• What is it: This method tracks users' steps towards a specific goal within your app or website. This includes making a purchase or signing up. It shows where users drop off in the process.
• Best used for: Identifying stages in the user journey where people are leaving or getting stuck. This is crucial for optimizing conversion rates.
• Tools: Google Analysis, Mixpanel, and Amplitude. ‍

5. Cohort analysis

• What is it: Cohort analysis involves grouping users based on shared characteristics or behaviors, such as sign-up date and tracking their actions over time.
• Best used for: Understanding how different groups of users engage with your product over their lifecycle. It's useful for spotting long-term trends and the impact of changes or features.
• When to use: Measuring user retention, engagement, and the effectiveness of updates or new features.
• Considerations: You'll need to decide how to segment your users into cohorts and what metrics to track for each group.
• Tools: Google Analytics. ‍

4. A/B testing

• What is it: A type of testing that shows two variants of a web page, app screen, or feature to different segments of users. This is done to determine which one performs better against a predefined goal.
• Best used for: Making data-driven decisions on design changes, new features, or content strategies. It helps determine what works best for your users.
• Tools: Mixpanel and Amplitude. ‍

5. Fixed-question surveys or questionnaires

• What is it: Research methods that collect feedback directly from users through answers to specific questions.
• Best used for: Gathering data that can be analyzed statistically for patterns or trends.  For instance, respondents may be asked to rate satisfaction on a scale of 1 to 5 or gather demographic details to see broader trends.
• Tools: Typeform and Google Forms.

Challenges of quantitative research in UX design

Here are the problems UX designers might face:

• Doesn't dig deep into complicated ideas: Quantitative research may not fully capture feelings and opinions. Numerical data alone can't express these complexities in detail.
• Overlooks the "why": It might overlook important reasons behind what users want and how they decide because it only looks at what they do, not why they do it.
• Limits on what people can say: Quantitative research has predetermined answer choices, so it might not capture every user's viewpoint. This can lead to participants choosing options that don't fully represent their thoughts.

What is qualitative research in UX design

Qualitative research gathers non-numerical data to understand concepts, thoughts, or experiences. It provides depth and context to user behaviors, motivations, and emotions.

Qualitative research in UX: When and why to use it

Qualitative UX research is all about understanding the stories, feelings, and thoughts behind user actions. You talk to users, watch how they interact with your design, or see their reactions to understand their experiences.

Here are the reasons why qualitative research is important in UX design:

1. To get inspired

Before you even start designing, talking to potential users can give you inspiration for what to build by understanding what they need or what problems they have. This can spark ideas for what to build.

Example: Before starting a new app for home gardeners, you talk to potential users and discover common pain points. They struggle with remembering watering schedules and managing pests organically. This feedback inspires the idea of an app that sends watering reminders and offers natural pest control tips. ‍

2. ​It gets to the heart of the problems

Hearing directly from users and understanding their experiences makes creating solutions that appeal to them easier. This includes understanding user needs, behaviors, and the context of their problems.

Example: Imagine you're developing a new fitness app. At this stage, you might interview users to understand their fitness routines, exercise motivations, and frustrations with current fitness apps. This can help you identify features your app should have, like personalized workout plans or motivation tracking. ‍

3. Improve something specific

Even after your design is out in the world, you’ll want to keep improving it. Talking to users can help you understand what’s working, what’s not, and why. It also builds industry insights and bridges knowledge gaps.

Example: When redesigning a public transportation app, holding focus groups could reveal that users want real-time updates about delays. ‍

Types of qualitative research methods in UX

1. user interviews.

• What is it: One-on-one conversations with users to explore their experiences, needs, and challenges. Unlike structured surveys, these interviews allow for open-ended responses and follow-up questions.
• Best used for: Gaining deep insights into user behaviors, motivations, and attitudes. They can help you understand the nuances of user needs and the context of their interactions with a product.
• Tools: Calendly, Zoom, Google Sheets, and ScreenApp. ‍

2. User observations

• What is it: This method involves watching users interact with a product in their natural environment to see how they use it without interference.
• Best used for: Identifying usability issues and understanding user behavior in a real-world context. Observations can reveal how intuitive a product is and how users navigate it.
• Tools: FigJam and Miro. ‍

3. Usability testing

• What is it: A method where users are asked to complete tasks using the product while observers or UX resarchers note where they encounter problems or confusion.
• Best used for: Directly assessing the functionality and user-friendliness of a product. It helps pinpoint specific areas where users struggle, informing targeted improvements.

4. Open-ended surveys

• What is it: Unlike fixed-choice surveys, these surveys primarily use open-ended questions to allow respondents to express their thoughts and feelings in detail.
• Best used for: Gathering qualitative data on user opinions, experiences, and suggestions. They offer rich, narrative data that can uncover new insights or deepen understanding of known issues.
• Tools: Typeform and Google Docs. ‍

5. Focus groups

• What is it: A moderated discussion with users about their experiences, perceptions, and opinions regarding a product or service.
• Best used for: Exploring diverse viewpoints on a topic, generating new ideas, and understanding user attitudes.
• Tools: Calendly, Zoom, and FigJam. ‍

6. Diary studies

• What is it: A research method where users record their experiences, thoughts, and frustrations while using a product.
• Best used for: Understanding long-term user behavior, experiences, and patterns that emerge over time. Diary studies capture how feelings and usage may change in different contexts.
• Tools: Journey, Daylio, and Google Sheets. ‍

7. Card sorting

• What is it: An interactive method where users organize topics into categories that make sense to them.
• Best used for: Structuring or reorganizing content on a website or app. It reveals how users conceptualize different information groups.
• Tools: Dovetail and OptimalSort. ‍

Challenges of qualitative research in UX design

While qualitative research in UX design offers deep insights, it comes with its own set of challenges:

• Limited scope of participants : While qualitative research goes deep, it does so with fewer participants. This means you hear from a relatively small group while you get detailed insights from each person. This limits how much you can extrapolate findings to represent a larger population.
• Requires a lot of time, effort, and resources to analyze: Breaking qualitative data into actionable insights can take much time and effort. Unlike quantitative data, it's not as straightforward to visualize through charts or graphs. This makes it harder to grasp or present findings quickly.
• Risk of bias from researchers : The subjective nature of qualitative research means it's more open to bias from the researcher or participants. Reproducing the exact results can be tricky since every interview or focus group may unfold differently.
• Generalization issues : Because qualitative studies typically include small group participants, applying the findings to larger trends or behaviors among users is hard.
• Privacy concerns: People might not always feel comfortable sharing their thoughts in settings where their identity is known, especially on sensitive topics. This might make people hold back or change their answers, making the data less genuine and helpful.

How quantitative and qualitative research work together in UX

Doing both qualitative and quantitative research methods in UX design is like having the best of both worlds.

Qualitative research digs into the "why" behind user actions, while quantitative research offers solid stats to back up your findings and spot trends.

Pairing these two methods gives you a full view of what's happening and why. Start with qualitative methods, like interviews, to get raw, in-depth feedback.

Next, conduct surveys or similar quantitative techniques to determine if those feelings or issues are common among your users.

Both research methods can sometimes uncover deeper insights that using one method alone might miss.

Let's take a look at a real-life case study from Spotify.

Case study: How Spotify used the mixed-method approach

Problem: Qualitative data revealed a discrepancy compared to the quantitative numbers from an A/B test on using a new feature that lets you skip ads.

They noticed users were engaging with the feature in different ways. However, when they talked to users directly, they realized there was confusion about how it worked, which the numbers alone didn't explain.

What Spotify did: Spotify's Product Insights team, which consisted of a mix of User Researchers and Data Scientists, adopted a mixed-methods research strategy known as " simultaneous triangulation ."

This approach involved:

• Clearly defining the research questions to focus the study effectively.
• Combining qualitative methods (user interviews and diary studies) with quantitative methods (A/B tests and data tracking) to gather insights.
• Using these methods together on the same group of users helps get a complete picture of how users behave and what they think.

How it helped: This integrated approach allowed Spotify to understand why there was a difference between user feedback and the data.

For example, they found that users they thought were "power skippers" were just confused about the rules for skipping ads. Only talking to users could reveal this, showing a full view of how people interacted with the feature.

Outcome: Using both user feedback and data, Spotify could fix misunderstandings.

They sent messages to users confused about whether there was a limit to skipping ads. They explained clearly that they could skip as many ads as they wanted. This clear communication messaging greatly improved how well the feature worked and doubled its feature success metrics.

By combining both research methods, Spotify solved the puzzle of mismatched insights and made better decisions for their product.

Boost your skills in 10+ hours and impress your stakeholders

To gain the confidence and trust of stakeholders, designers often focus on making their designs look prettier and on-trend.

That's the old way of thinking. Companies nowadays seek designers who go beyond that and bring more results.

And it starts with understanding their users.

To truly meet their needs and solve their problems, you need to dive deep into their world.

Understanding how your work fits the larger business objectives is crucial to stand out.

Learn how to master UX research in just 10+ hours with Mizko's Practical UX Research & Strategy Course .

This course is your bridge to knowing your users and truly understanding them. By the end of the course, you'll be able to know what type of research methods to use in your projects to uncover crucial insights.

Here’s what makes it stand out:

• Hands-on learning: Apply what you learn through real-world challenges. Knowing UX research is one thing, knowing how to apply it.
• Efficiency: Forget about sifting through countless pages or websites. Get straight to the heart of effective UX research methods.
• Expert guidance: Learn from Mizko, an experienced designer who successfully transitioned to an agency owner and startup advisor. Get exclusive access using the resources and templates that helped him succeed.
• Flexible learning: Study at your own pace without the stress of a fixed schedule.

You’ll also learn how to:

• Draw valuable insights to inform your designs.
• Choose the right participants for meaningful feedback.
• Visualize research findings for easy understanding.
• Prioritize insights into actionable design tasks.
• Clearly communicate your findings and recommendations to stakeholders.

This course has already helped over 6,800 designers from top tech companies like Google, Meta, and Squarespace to integrate UX research into their daily work.

Here's what some of them have to say:

"I'm 100% more confident when talking to stakeholders about User Research & Strategy and the importance of why it needs to be included in the process. I also have gained such a beautiful new understanding of my users that greatly influences my designs. " - UX/UI Designer Alyssa Durante

"The process in this course connects the dots and its easy to lead the clients through this process... + I can adapt the process based on the resources and the needs of the client. Life is now way easier to be honest because I have clear path to show to the clients even before we start the project because I can build expectations from the start." - UX/UI Designer Milosh Jakjimovski

"As I was struggling to find a high-level research framework for my day-to-day design work, I was able to fill many of the knowledge gaps because I took this course. It provides a well-structured research process that cuts out the "guesswork" that I'm adopting in my projects. Mizko covers his reasoning for every decision he took from start to end. Real-life examples and practical solutions throughout the course were incredibly helpful. Right now, I'm more confident than ever with my design decisions, presenting meaningful briefs to stakeholders, and so on." -  UX Designer Al Razi Siam

Go beyond learning Figma skills and deliver designs that drive business results.

Mizko, also known as Michael Wong, brings a 14-year track record as a Founder, Educator, Investor, and Designer. His career evolved from lead designer to freelancer, and ultimately to the owner of a successful agency, generating over $10M in revenue from Product (UX/UI) Design, Web Design, and No-code Development. His leadership at the agency contributed to the strategy and design for over 50 high-growth startups, aiding them in raising a combined total of over $400M+ in venture capital.

Notable projects include: Autotrader (Acquired. by eBay), PhoneWagon (Acquired by CallRails), Spaceship ($1B in managed funds), Archistar ($15M+ raised) and many more.

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A Beginner’s Guide to Quantitative UX Research

UX research is at the cornerstone of UX design as it’s the best way to identify where there’s a problem and to uncover the design opportunities available to remedy them. Through various research methods, designers work to pinpoint the needs of their users and the best ways to meet those needs.

An important subcategory of UX research is quantitative user research . Quantitative user research is what most people imagine when they think of research data—it’s numerical or statistical information obtained through highly controlled testing environments. While its counterpart, qualitative data, gives researchers important subjective information, quantitative data provides crucial objective information that helps designers to evaluate their products and determine when a redesign might be necessary.

We’ve created this comprehensive guide to quantitative user research to help you understand what quantitative data is, how it’s used, and the different types of quantitative research methods employed by UX designers.

Here’s what we’ll cover:

• What is quantitative UX research?

When to use quantitative UX research

• Quantitative UX research methods
• Utilizing mixed methods in UX research
• Key takeaways

Now, let’s get started!

1. What is quantitative UX research?

Quantitative user research is the process of collecting and analyzing objective, numerical data from various types of user testing.

Quantitative research utilizes large sample numbers to produce bias-free, measurable data about a user population. It answers the questions of “how many, how much, and how often?”

The main goal of quantitative user research is to indirectly measure the usability of a completed or final product. However, quantitative research is also used to compare a product to its competitors or calculate a company’s ROI.

2. When to use quantitative UX research

Quantitative user research is best conducted on a product that is already in existence or when you’re completing a final design. This means that quantitative research is utilized at the very beginning or very end of a design cycle. However, to time your quantitative research well, you’ll need to evaluate your research goals and understand the benefits that running quantitative user research will have on your designs.

Here’s a brief overview of some benefits of quantitative research, some potential downsides, and the situations when you should use quantitative methods in your UX research.

Benefits of quantitative research

• Easier to avoid human-bias as it’s difficult to lead participants to certain outcomes in a structured and highly controlled testing environment
• Allows you to assign numbers to the usability of your product, which may be more convincing to some investors and stakeholders
• Results in data that is easily presented in the form of graphs, charts, etc.
• Helps you understand if changes in your designs create different (statistically significant) outcomes
• Warrants less direct contact with users and easy to conduct remotely

Potential downsides to quantitative UX research

• Can only give you an idea of what is happening, but doesn’t answer the question of why certain trends or patterns are present
• Doesn’t result in anecdotal data or direct quotes from users, which can also be impactful with some investors and stakeholders
• In order to obtain any sort of statistical significance, you need to have a lot of respondents/participants (a large sample size), which may be difficult to organize
• Can be costly due to the need for a larger sample size
• Lets you know if a redesign is necessary but doesn’t clue you in on how the product  should be redesigned
• When comparing your product to its competitors
• To determine if a redesign is necessary or worth doing
• When you need to analyze and compare different designs and whether the changes observed are statistically significant
• If you need to evaluate company goals, key performance indicators, or when justifying support for and investment in your UX design team to upper management

3. Quantitative UX research methods

There are many types of tests and research methods that can provide meaningful quantitative data when analyzing your product. Here, we discuss a few of the most common ones: Analytics, heatmaps, funnel analysis, cohort analysis, and A/B testing.

Analytics, and Google Analytics in particular, is one of the most valuable sources of quantitative user data. Through metrics like bounce rates, page views, conversion rates, and click-throughs, analytics helps give you a clear cut idea of the usability of a site and what users are doing when they interact with it. It can quickly give you numerical data that will suggest what parts of a site need work or if a complete redesign is warranted.

Mouse heatmaps

Similar to analytics, mouse heatmaps paint a pretty vivid picture (literally) of what is happening when a user interacts with a site. Mouse heatmaps help you visualize a user’s mouse movement and records when they hover, scroll, click, or pause when moving through a site. With radar-like color coding, mouse heatmaps show where your users’ attention is drawn and what areas can be leveraged for higher conversion rates.

Funnel analysis

Funnel analysis is a method that helps you visualize the steps needed for your users to complete a task and analyze how successful they are at doing so at each step. The map typically takes on the shape of a funnel as you assess what percentage of users are making it all the way to the final step of the task. A funnel analysis helps you visualize where most users are dropping out of the journey and what steps in the funnel need attention in order to maximize conversion rates.

Cohort analysis

Utilizing a cohort analysis helps you look at user engagement over time. The activity of your older users is often masked by the high rates of new users. So instead of lumping all your users into one category, a cohort analysis sorts them into related groups so you can accurately assess if engagement is improving over time or if it just appears that way due to growth. It will also show you where your users are dropping out and what areas need work in order to improve user retention.

A/B Testing

A/B testing allows designers to compare two or more versions of a design on users to see which one is more effective. It’s best that the designs differ by only one or two key features so that you can accurately assess if different outcomes of the test are actually due to differences in specific features. While you can obtain some qualitative data from in-person A/B testing (ie. quotes, facial expressions), A/B testing gives you a percentage of how many users prefer each design, giving you a distinct idea of which version is more effective.

4. Utilizing mixed methods in UX research

Quantitative user research can offer invaluable data when analyzing the usability of a product. However, when used on its own, it’s not enough to portray a complete picture of how successful a product is at fulfilling the user’s needs. This is where mixed methods research comes in.

Mixed methods research simply refers to using both quantitative and qualitative user research to investigate the efficiency of a product. 

As we’ve already said, quantitative data gives you objective, numerical data that answers all your “what, how many, and how much” questions. Qualitative data, on the other hand, provides crucial user feedback and subjective data to answer why certain trends are occurring, and how you might address any problems or pain points.

When used as a pair, quantitative and qualitative data give you a more thorough and detailed view of how users are reacting to a product, what areas have flaws or frictions, and how they might be remedied.

5. Key takeaways

Quantitative data is a crucial part of UX research that gives designers minimally-biased and objective numerical or statistical data about the efficiency of their products. Through various testing methods, UX researchers and designers employ quantitative user research to evaluate the usability of a product or determine if a redesign is necessary. However, quantitative UX research is best used alongside its qualitative UX research counterpart. When used in conjunction, designers can easily identify trends in user behavior, understand why they might be happening, and work towards resolving them.

To learn more about UX research, check out these articles:

• How to conduct UX research like a pro
• Qualitative vs. quantitative UX research—what’s the difference? 
• How to conduct inclusive user research
• 5 Mistakes to avoid in your UX research portfolio

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Quantitative vs. qualitative research

In this post, we’ll delve into the differences between quantitative vs. qualitative research and the benefits and drawbacks of using each one

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UX designers strive to create the most user-friendly products and services possible. But without speaking directly to users about what they want and need, UX designers can only guess what the best user experience will be. This is why UX research is such an essential part of the UX design process. 

UX research involves asking users to identify what problems a product or service can help them solve and provides insights into the best ways to do so. There are a wide variety of methods a UX researcher can use, but in general, each of these UX research methods will fall under the umbrella of either quantitative research or qualitative research. 

In this post, we’ll delve into the differences between quantitative vs. qualitative research and the benefits and drawbacks of using each one by discussing the following topics:

What is quantitative research?

What is qualitative research, examples of quantitative research, examples of qualitative research, which method should you choose, presenting quantitative versus qualitative research.

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Quantitative research answers questions about quantity such as:

For example, you might want to conduct a quantitative study to find out how often people use a product, how much time they spend with the product, and how many features of the product they use. 

Quantitative methods involve collecting numerical data that can be analyzed using statistics. This means quantitative studies are often straightforward to implement and can be easily automated and conducted remotely, however they also require enough participants to ensure they yield statistically significant results.

• Studies are quick to implement and cost effective
• Analysis is fast
• Results are statistically significant and considered objective
• Numeric results are often easy to understand and use to improve a product’s UX

Disadvantages

• A large number of participants ( at least 20 ) are required to ensure statistical significance
• Someone of the team must have expertise in statistical analysis
• Results lack context, so they can reveal what people did but not their reasoning

Qualitative research answers questions about quality such as how users feel about an experience, why they like or dislike a feature, and why they make certain decisions when completing tasks. Ultimately the goal of qualitative research is to delve into users’ thinking to find out “why.”

Qualitative methods involve collecting data in the form of written or spoken words that are then analyzed for prominent themes and patterns. As a result, both the data collection and analysis of qualitative studies can be time-consuming and labor-intensive. On the other hand, only a few participants are required to arrive at valuable results that can provide nuanced insights into users’ thoughts and feelings about a product.

• Only a small number of participants (usually around 5) are required
• Provides detailed, first-hand insight into UX issues 
• Allows for flexibility during data collection
• Results in compelling stories that help stakeholders foster empathy for users 
• May identify unexpected information about the user’s experience with the product 
• Time consuming to plan, run, and analyze
• Tends to cost more than quantitative studies due to the time commitment required
• Analysis is subjective and therefore results may be influenced by researcher bias

[GET CERTIFIED IN UX]

Quantitative research includes any studies and tests that yield numerical data, such as: 

• First-click tests
• Surveys with yes/no and multiple choice questions

Many of these methods can be implemented remotely with a growing group of UX research tools . For example, first-click tests and surveys can be run through Optimal Workshop , Google Analytics can provide any required analytics data, and Hotjar can record user interactions with your product in order to generate heatmaps of how users navigate through it. You’ll also use software, such as SPSS (or plug formulas into a Google or Excel spreadsheet) to statistically analyse quantitative results.

Qualitative research is often carried out in person either in a lab where users come to participate in the study or in the field where researchers go to where users are. It can include the following methods:

• User interviews
• Focus groups
• Ethnographic studies
• Shadow sessions
• Surveys with open-ended questions

Qualitative studies usually require at least one researcher to be there to perform tasks such as asking users questions during user interviews or observing users during ethnographic studies. However, there are some tools that enable researchers to run qualitative studies remotely. For example, video research platform Lookback enables researchers to run either moderated or unmoderated remote interviews. 

Furthermore, while analysing qualitative data is a very hands-on process, researchers can use platforms like Rev to transcribe things like interview recordings and programs like Dedoose , NVivo , and Reframer to organize, synthesize, and analyze the large amount of text data qualitative studies inevitably yield.

Qualitative and quantitative research can be used at pretty much any point in the design process but each method is most useful at different times.

Quantitative research tends to be most valuable during the design phase of the UX process when it can quickly uncover if the UX solutions being designed are working the way the UX team intends. Quantitative studies are also helpful to validate the final design of a product before it goes live. At this point, quantitative research can confirm the design is ready to go to clients and stakeholders or point to the tweaks that need to be made to ensure the product is the best it can be.

Quantitative research, often with Google Analytics, is also utilized once a product goes live to evaluate the product’s ongoing usability, compare it to competitors, and track its return on investment. 

On the other hand, qualitative research is most valuable during the discovery phase of the UX process when it can provide extensive insight into users’ thoughts and feelings about the product the UX team is getting ready to design or redesign. Qualitative studies can also be valuable during the design phase when the UX team wants to understand how users feel about key user experience features, especially if they’re unique or unusual. Findings from such studies can help the UX team determine if it’s pursuing the best possible solutions.

Combining quantitative and qualitative research

While it can make sense to focus on either quantitative or qualitative research in some circumstances, more often than not, it can be incredibly valuable to combine them to conduct a mixed methods study. That’s because quantitative and qualitative methods are complementary approaches. For example, a survey can include a series of quantitative multiple choice questions that help point to how much users like a product’s different features, as well as several qualitative questions that enable participants to explain the reasons for their answers to the multiple choice questions. 

Mixed methods research is the best of both worlds, ensuring you can answer not only the questions of how much and how many but also why. This provides results that have both statistical weight and depth of insight, with the findings of each method strengthening the other. 

Some examples of mixed method research include:

• Card sorting where users explain their reasoning as they organize the cards
• Tree testing where users describe their decisions out loud
• Surveys that include multiple choice and open-ended questions

Whether you performed quantitative, qualitative, or mixed method research, each UX research report should follow the same basic outline: 

• An introduction
• Research goals
• Business value
• Methodology
• Key learnings
• Recommendations

Most of these sections involve explaining what you did and why you did it, but in the key learnings section, where you’ll present the findings from your research, the data and artefacts you present will depend on the research methods you used. 

For instance, if you performed a quantitative study, this is where you’ll present any relevant statistics you found, such as the percentage of participants who preferred one UX design solution over another. If you performed a qualitative study, there are more ways to present your findings and you’ll have to decide which ones best represent your results. Options can include sharing the main themes or patterns you found in the qualitative data, illustrative quotes from participants, or artefacts like personas, journey maps, affinity diagrams, or storyboards. 

To present the best key learnings section, it helps to combine qualitative and quantitative results whenever possible. This provides an opportunity for you to back up the statistical results uncovered by your quantitative research with quotes, personas, affinity maps, or other findings from your qualitative research. Not only does this create a convincing demonstration of the value of your research, it makes a stronger case for your findings and fosters greater empathy for your products’ users.

Both quantitative and qualitative UX research has strengths and weaknesses. As a result, UX researchers must think carefully about the goals of the research studies they’re conducting before deciding which method to utilize. No matter which one you choose, however, the results of UX research can make an invaluable contribution to the success of the user experience of any product. 

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UX design research methods

Effective user experience design is intuitive, accessible, and engaging. But how do you design a delightful experience that meets your target audience’s needs? Conducting user experience research gives you a glimpse inside your users’ heads, so you can understand what they care about and the challenges they face.

In this article, Figma Designer Advocate Ana Boyer weighs in on:

• What user experience research is, and why your team needs it
• Different types of UX research that support product development
• UX design research methods made easier with Figma

What is user experience research?

User experience research helps design teams identify areas of opportunity to improve user interfaces and enhance the overall user experience. According to Ana, UX research can reveal insights about target users across all phases of product development—from strategy and planning to product launch and post-launch improvements. A robust UX research framework includes both quantitative and qualitative research.

Quantitative research

Using information gathered from larger sample sizes, quantitative research yields concrete numerical data that reveals what users are doing. Researchers run statistical analyses and review analytics to gain insights into user behavior. For example, Ana says, “you might try tracking the number of times users clicked a CTA button on a newly designed web page, compared to an old version."

Qualitative research

For qualitative research, researchers collect subjective and descriptive feedback directly from users, tapping into users’ personal feelings and experiences with a product or design.  "Qualitative research gives you a more thorough explanation of why someone is doing something in the context of a flow,” Ana says.

User-centered design research often covers two types of qualitative research: attitudinal and behavioral. Attitudinal research examines users’ self-reported beliefs and perceptions related to a user experience, while behavioral research focuses on observing first-hand what users do with a product.

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3 benefits of user experience research

According to Ana, with UX research you can:

• Validate your design. "You can learn whether or not your design is hitting project goals and your users are able to accomplish a task—for example, ordering an item from your platform.”
• Put your users front and center. UX research uncovers what users want and need, so you can deliver a product that delights customers.
• Save time and resources. Doing user research and testing early and often allows you to make smaller adjustments quickly and easily. That way, Ana says, “you can take a more iterative approach to design—without having to backtrack and redo your entire UX design.”

How to conduct  UX research

Most common UX research methodologies break down into these essential activities:

• Observe how users act and react . This not only includes clicks and scrolling onscreen, but also their body language and facial expressions. Careful observation helps you understand how users normally perform a task, what interactions users pick up easily or enjoy, where they get stuck in a flow, and more.
• Empathize with your users . To create a useful and usable product, you need to consider how users' context influences them as they interact with your design.
• Analyze information to surface common themes. “Tagging key user responses helps you pinpoint what needs the most work and refinement to improve the user experience," Ana advises

When to use key UX research methods—at a glance

Given all the UX research methods you can use for  product development, when is each most useful? Ana offers these pro tips.

• User personas help you understand your core users in the early stages of development. “If you don’t know who you’re building for, then the time you invest in building and creating something will be wasted,” Ana explains. FigJam’s user persona template will help you get the ball rolling.
• Interviews gather in-depth information directly from users to test your ideas, so you can lower the risk of building a product that misses the target. FigJam’s user interview template will help you lay the groundwork.
• Card sorting invites users to show you what they think is the most intuitive way to organize high-level information in your design. Try FigJam’s card-sorting tool to shape your product’s information architecture.
• Task analysis studies users as they use your site or app to complete tasks, or jobs to be done. Use it to validate your design, and ensure users can quickly and easily accomplish their goals. Get started with FigJam’s jobs to be done template .
• Eye tracking analyzes where users look, when, and how long as they interact with your product.
• Surveys indicate how useful and usable your design is. Surveys  can provide useful insights at any phase of product development, pinpointing where users are struggling with an interface, and revealing user sentiment about a product’s colors, fonts, and overall design.

Launch & post-launch

• A/B testing shows which version or iteration of a webpage, app screen, or CTA button performs better with your users.
• Analytics track KPIs like time spent on page, bounce rate, number of clicks on key CTAs, and more to see what’s working—and what isn’t. Analytics may also reveal useful insights about your users, including location, device usage, age, and gender.
• Usability bug testing identifies and helps fix usability issues that affect your product’s quality and ease of use. “Teams struggle to invest the time and process in doing this, but it can have a huge impact on quality,” Ana says.
• Diaries captured in writing or on video track users’ thoughts and impressions over a certain time period. This self-reporting approach reveals how a product fits into and enhances users’ daily lives.

Kick off user experience research with Figma

No matter where you are in the product development process, FigJam’s research plan template can help you define your research goals. Figma’s research and design templates help you conduct research with user interviews , user personas , card sorting , and Sprig study integration .

With the insights gained from your research, you're ready to design, develop, and prototype engaging user experiences. Use Figma’s UX design tool to:

• Give and receive instant feedback on designs or prototypes—and enjoy real-time collaboration with your team. Figma's Maze integration makes testing prototypes easy.
• Set up design libraries to quickly launch user research projects and improve UX design.
• Easily share assets between Figma and FigJam to help keep your projects moving forward.

To jumpstart your UX research, browse inspiring UX research resources shared by the Figma community .

Now you're ready to roll with UX research!

Go to next section

[1] https://www.nngroup.com/articles/which-ux-research-methods/

[2] https://www.uxbooth.com/articles/complete-beginners-guide-to-design-research/

Guides » UX Research Basics » Quantitative vs. Qualitative Research

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Quantitative vs. Qualitative UX Research

There are several ways of conducting ux research, however, all of them can be divided into either qualitative and quantitative research depending on the type of data obtained. in this guide we are going to walk you through the main differences between them and show you when to use which method in order to get the data you need..

Last update 05.11.2023

In UX design, it is important to keep the user and their needs in mind at all stages of the design process. But still, how can you know what your users’ needs are? The best way to find out is to conduct thorough user research and collect enough data. Today we are going to give you the quantitative vs. qualitative research comparison and show when to use which method.

While there isn’t one that is better or more valuable than the other, there are some key differences that make qualitative data at times more useful than quantitative data—and vice versa.

What is qualitative research?

Qualitative UX research focuses on a smaller number of users to understand their needs in greater detail . The goal of qualitative research is to discover any problems in UX, investigate why something is happening, or find ways to solve a particular issue. This type of research answers questions like: “Why?” or “How?”

When you want to know why users are having a bad experience with your product, listen to their opinions and find out more about the reasons behind their behavior – qualitative research methods are the ones to help you!  Qualitative research is often formative, meaning that it helps you get the understanding you need to make the right creative decisions.

What is quantitative research?

Quantitative research focuses on large groups of people to collect data that can be counted or measured with numerical responses. Quantitative research is used to determine the scale of a problem, evaluate design possibilities, or track a product’s user experience over time. This type of research frequently provides answers to such questions as “How many?” and “How much?” and provides you with statistical data.

When you want to discover how many users feel a certain way about a product or its specific features, conduct quantitative research.

Qualitative UX research pros and cons

• It’s a  flexible  research method since you can change your questions, refocus the discussion based on the user’s responses, or add additional depth to the questions you’re asking.
• Because of the nature of the questions posed in qualitative research, you can get  more detailed feedback  and thus a better understanding of what a user thinks and why they think that way.
• Users can provide you with nonverbal clues that can help you further your research. Qualitative research methods allow researchers to delve into the emotional data that influences decision-making.
• The study’s findings may challenge your assumptions about the product by revealing an entirely different outcome than you may have anticipated. Participants tend to offer more information than you expect.
• There is no “right” or “wrong” answer because it is an open-ended process,  which makes   data collection much easier .

Disadvantages

• Varying user feedback might make it harder to reach a conclusion. Because individuals have different perspectives, the reaction to qualitative research findings can often be at two extremes. That means two very different outcomes can be achieved, making the data difficult to analyze and present to generalized audiences.
• The qualitative research method does not allow for statistical analysis. It will only present the study’s findings from a variety of perspectives. Responses to this type of research can be challenging to represent statistically.

Quantitative UX research

• Quantitative research uses a larger sample size, allowing you to learn more about your users and  enhance the research’s credibility . When you have the option of researching a larger sample size for any hypothesis, it is easier to acquire an accurate generalized conclusion.
• It is a straightforward process to implement, thereby  allowing researchers to collect information quickly from a large number of participants .
• The type of findings you get when collecting quantitative data will help you decide on the type of statistical analysis you should do. As a result, evaluation of your data and presenting your conclusions becomes simple and free of subjectivity and errors.
• Quantitative research often does not allow for in-depth feedback; most questions will have responses drawn from a set of multiple-choice answers. If the questions are not well-formulated, then you might miss out on critical insights.
• There’s a chance that the responses or characteristics provided aren’t representative of the entire population. Because of the assumptions and generalizations that are required for this activity, it is relatively easy to arrive at incorrect conclusions.
• While quantitative research can tell you how many people did a specific action, or which features they favor, it can’t tell you the reasons for their actions or choices.

Qualitative vs quantitative UX research: Which one is better?

A Mixed Method approach provides deep, rich research insights, which are needed as more businesses turn to a product-led-growth strategy.

Overall, no single research method will be able to provide you with answers to all of your questions. Using a range of methodologies in your research is the greatest plan. Both qualitative and quantitative research play an important role in the design process and also provide us with different kinds of information from users. By combining the two, you’ll get the best of both worlds and obtain the most accurate assessment from your research.

Below, we list some typical qualitative and quantitative UX research methods. We say  typical  since a  specific research method isn’t strictly bound to one type . Rather, the type is just one of several aspects of the research method. Some methods are more likely to be one type rather than the other. Sometimes, a research method even combines aspects of multiple types, making it a hybrid.

For example, usability testing may collect qualitative insights about why participants fail to complete a key goal in a web application. But an unmoderated usability testing study conducted online with enough respondents to be statistically significant can also help you tell how much of a problem this actually is.

Typical qualitative UX research methods:

• User interviews

Focus groups

Usability testing.

• Five second testing

Session recording

Field studies, diary studies.

This method is used to collect in-depth information on people’s opinions, beliefs, experiences, and feelings. Interviews can be conducted one-on-one or in a group context, such as a focus group, and can be done in person or remotely via  video call .

Involves a discussion in a small group (usually 5-10 participants) with a moderator guiding the discussion. The aim is to learn more about users’ beliefs, thoughts, impressions, desires and reactions to certain concepts.

A process of evaluating a product or service by putting it to the test with real users and giving them tasks to complete. Usability testing can be moderated or unmoderated, and it can be done in person (e.g., in a lab) or remotely (e.g., through video call). Check out this article on  how to run usability tests .

Five-second testing is a quick usability testing method that involves showing participants a design or interface for just five seconds and then asking them questions about their initial impressions.

A full recording of a user’s session – of interacting with a product. Allows researchers to observe every scroll, click and other interaction with a digital product and gain insights about user behavior.

A field study in UX means observing and gathering qualitative data from real users in their natural environment, such as their homes or workplaces. The goal is to understand their behaviors, needs, and challenges in order to inform and improve digital product design.

Diary studies involve collecting data from users over an extended period of time, typically through entries in a diary or journal.  These studies provide rich, in-context information.

Typical quantitative UX research methods:

• Card sorting
• Tree testing
• A/B testing
• First click testing
• Website analytics
• Eye-tracking studies
• Card Sorting

Card sorting is a UX research method in which study participants organize topics into categories that make sense to them. This method serves to create an information architecture that matches users’ expectations. Check out this article on  how to conduct a card sort .

Tree testing is a technique that involves removing the user interface and requiring users to navigate the site and perform tasks solely through links. This allows you to determine whether a problem is caused by the user interface or the information architecture.

A/B testing involves putting two or more versions of your design to the test on users to see which one is the most effective. Each variation differs only in one aspect, which may or may not influence how users react. A/B testing is particularly useful for confirming assumptions derived from qualitative research.

Involves observing where participants would click first on a user interface when asked to accomplish a certain task. This method helps identify potential usability issues and provides insights into users’ expectations and mental models of the interface.

Website Analytics

Using analytical tools like Google Analytics and  UXtweak  to measure metrics, such as page views and click-through rates, gives you a better understanding of your user’s behavior. Check out this list of the best tools you can use for  website analytics .

A popular approach for gathering quantitative data is by having users fill out a series of questionnaires. Surveys are typically used for quantitative research, but they can also be used for qualitative research when structured properly. Here you can find additional information on what  surveys are and how to conduct them effectively .

Eye tracking

Uses specialized technology to track and record users’ eye movements as they interact with digital interfaces, providing insights into visual attention and helping designers optimize the design and placement of elements within the interface.

How to perform data analysis

Both qualitative and quantitative research approaches supply researchers with a wealth of information. Once the study is over, it’s time to analyze the information gathered to gain relevant insights from it. Here’s how you can analyze UX research data.

1. Organize and collect your research data logically

This comprises the information from all sources and formats, including text, handwritten notes, audio recordings, and video clips. To effectively analyze your audio and video clips, make sure to transcribe them.

2. Tag and code your data

Review the notes, transcripts, and data for any relevant phrases, statements, and concepts that correspond to the research goals and questions. Review the tag and code any remaining data that represents key activities, actions, concepts, statements, ideas, and needs or desires from the customers who participated in the research.

3. Identify common themes

Examine the tags and codes to see if any connections can be used to determine themes. Pay particular attention to tags that include notes with several other tags as a helpful tip. This frequently suggests a connection between subjects. You may also use  Affinity Diagrams  to visualize your data and uncover meaningful patterns. Here you can find more information on  using thematic analysis to analyze qualitative data .

4. Synthesize data by turning your themes into meaningful insights

Depending on your study goals, you’ll work your way through each theme, starting with the ones you think are most important. This can be done on a whiteboard with sticky notes with each theme linked to a study discovery and the final insight gained. Once you’ve finished, make a list of all of the most important insights.

5. Present your findings

Sharing your findings with your team is the final stage in the analytical phase. Create a  UX Research report  on your findings and recommendations. The insights you uncover through user research and subsequent analysis will guide the next steps in your design process, indicating what you should focus on and why.

People also ask (FAQ)

UX research can include both qualitative and quantitative research methods. The best result and insight into user experience and user behavior will be obtained by combining the two approaches and including multiple UX research methods in your UX research plan .

Qualitative research in UX aims to provide in-depth understanding through methods like interviews and observations and typically involves a smaller amount of subjects. Quantitative UX research, on the other hand, involves collecting numerical data and conducting statistical analysis to measure user preferences and UX performance metrics . It aims to provide objective, measurable insights and typically involves a larger number of participants.

Quantitative UX research includes methods such as:

It is however important to note some methods may have both quantitative and qualitative aspects to them, depending on the use.

UX Research Methods

Ux research process, topics: ux research basics.

• 01. UX Research Basics
• 02. Remote User Research
• 03. UX Research Plan
• 04. UX Research Questions
• 05. UX Research Methods
• 06. Quantitative vs. Qualitative Research
• 07. UX Research Process
• 08. UX Research Report
• 09. UX Research Framework
• 10. UX Research Presentation
• 11. UX Research Bootcamp

UX Research Basics

Remote user research, ux research plan, ux research questions, quantitative vs. qualitative research, ux research report, ux research framework, ux research presentation, ux research bootcamp.

• Tree Testing
• Preference Test
• Five Second Test
• Session Recording
• Mobile Testing
• First Click Test
• Prototype Testing
• Website Testing
• Onsite Recruiting
• Own Database
• Documentation
• Product features
• UX Glossary
• Comparisons

Learn / Guides / UX research guide

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How to understand your users and what they want: the complete guide to UX research

Really knowing your users involves taking the initiative to understand their behavior, their preferences, and their desires. This is where UX research comes into play. 

It may seem overwhelming at first and you might not know where to start, but when done right, UX research gives you key insights into what your users want (and don’t), so you can give them the best possible product and experience.

Last updated

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This is your ultimate guide to UX research: learn exactly what it is, why it matters, which research methods to use, and the best practices to follow, so you can start understanding your users better and create the perfect product for them .  

Make user-driven product improvements with UX research

Use Hotjar's tools to help you understand your customers and enhance the user experience.

What is UX research?

User experience (UX) research is the study of all your user groups and how they interact with your product or service . It helps you create a product your users love and validate decisions, like trying to figure out if your users will like your new feature or if a design change will positively impact their experience.

UX research vs. UX design

To be clear, UX research and UX design are not the same thing . The UX research process centers on carrying out qualitative and quantitative analysis to gain key insights about your users and the way they interact with your product. Meanwhile, UX design is about implementing those findings to create a valuable experience for your users, whether on your website or app. 

While some companies have designated UX or product researcher roles, UX designers often carry out UX research to inform their design decisions. And sometimes, marketing and customer success teams conduct UX research to learn more about their customers and how to better speak to and serve them.

The UX research process, which is typically an initial phase of the greater UX design process, is ultimately a problem-solving framework. And to determine which research method is the best fit for your needs, you have to begin by asking the question, ‘What are my goals?’

The 2 main methods of UX research

While UX research is an overarching term that describes the process of getting to know your users, there are various methods you can use to carry out your analysis. And, as with any research process, the goal of your research will determine the methods you use .

The first step to decide which method you will be using is defining the research question. And remember: research sometimes requires a creative effort—don't be afraid to think outside the box and be innovative with the methodology to get your insights!

Use both qualitative and quantitative methods when conducting UX analysis . Quantitative research gives you an overview of the hard data, while qualitative research helps explain the ‘why’ behind your results.

Let's take a look at these two methods:

5 quantitative UX research methods

Quantitative research helps you use numerical data to inform your design and product decisions. Quantitative UX research methods include: 

Surveys : glean important insights into the user experience from surveys. Use Net Promoter Score ® (NPS) and customer satisfaction (CSAT) score surveys for a quick, quantitative look at how your users feel about your product and brand, asking them to score their experience on a scale of 1–5.

A/B testing : this helps you compare and evaluate multiple versions of your product or design. For example, if you’re testing out different designs for your check-out cart, use A/B testing to determine which version results in more sales. You can use a tool like Optimizely to test different versions of your product. 

Eye tracking : you can use eye tracking for both quantitative and qualitative research. Special tools, like Lumen and Tobii , let you observe which parts of your design draw users in and which they ignore. You can use these findings to influence your UX design and overall product strategy. 

Product analytics : as well as eye tracking, you can use product analytics tools like heatmaps to gain key insights into how your users interact with your website. You can also use Google Analytics to learn more about user demographics and behavior. 

Benchmarking : this lets you track your product’s usability over time to determine whether it’s making progress—for example, becoming increasingly more valuable and easy to use. To do so, use a relatively large sample size of users (40 or more) and measure their time to complete certain tasks, as well as the outcome of their actions.

5 qualitative UX research methods

It’s also important to understand the reasons behind your quantitative research findings, which is where qualitative analysis can help. Qualitative UX research methods include: 

Surveys : as well as measuring hard data, you can use surveys to ask your users key UX research questions and learn about their product and post-purchase experiences. For example, send out exit-intent surveys to get a better understanding of why your users leave, so you can prevent it from happening in the future. 

Feedback : include a Hotjar Feedback widget on your website to hear what users have to say about your brand and product while it’s fresh in their minds. This allows you to capture opinions from users in the wild and better understand their frustrations and desires. 

Usability testing : this observational research method helps you identify drawbacks and opportunities in your product. Some examples of usability testing include performance testing, card sorting, and tree testing, which can give you key insights into the way your users understand and experience your product.  

User observation : you can also use heatmaps to gain qualitative insights about how your users navigate your website. Hotjar lets you create an unlimited number of heatmaps with a freemium account. Also, watch recordings to see how your users really engage with your product and find out where they get stuck on your site so you can improve the design (and their experience).

Interviews : what better way to get to know your users than by speaking with them? Conduct interviews with distinct user profiles to learn about their jobs to be done , their frustrations with your product, and which features provide them with the most value. 

5 best practices for UX research

When done right, UX research is a powerful tool that helps you get to know your users and give them the product experience they desire. Take a look at these six UX research best practices to conduct effective research and make decisions that'll have the greatest impact on all your users. 

1. Identify your users and their goals

Empathy is the key to successful design. To create something your users will love, you first have to know and understand them . Establish unique user personas —you can’t fit all your different types of users in one box—so you can design a product that delights every type of buyer that comes into contact with it. 

Remember, a big part of UX research is understanding your various user personas and their motivations, which is why you should analyze all of your user groups. Be sure to both track their behavior and seek their opinions— user feedback will often help explain the ‘why’ behind the actions you observe.

Pro tip: use a Hotjar user persona survey to segment your customers into different groups based on their goals, barriers, and use cases.

Collect survey data from your users to help you get to know them better.

2. Use a variety of tools

You should have a variety of UX research tools at your disposal to conduct both quantitative and qualitative research. Hotjar, for example, lets you observe what users do on your product or site with Heatmaps and Recordings , as well as collect user opinions with Surveys and Feedback. And for A/B testing, Hotjar offers integrations with tools like Google Optimize and Optimizely , so you can compare different versions of your design.

For the full list of tools to conduct UX research and optimize the process: check out this article .

3. Make data-driven decisions

Once you’ve conducted your UX research, put it to good use and make informed product changes that provide value to your users. Now’s the time to put your users’ goals and desires at the center of your product and design decisions, and find ways to alleviate their frustrations to get happier users that stick around for the long haul. 

4. Keep all relevant stakeholders in the loop

While you may be in charge of the UX research on your team, you may not be calling the shots when it comes to product design changes or new feature roll-outs. That’s why it’s important to keep everyone, from project and product managers and marketers to C-level decision-makers, in the loop. Also, be sure to present your UX research findings in a clear, understandable manner. 

Pro tip: if you're collecting insights with Hotjar, use the Highlights feature to save and organize valuable snippets of heatmaps and recordings and share them with stakeholders to keep everyone on the same page.

5. Improve and repeat your UX research cycle

UX research is not simply a box to check—it should be an ongoing process that you constantly refine and carry out to optimize your product and the user experience. Continue updating your UX research process to gain even better insights into the customer experience and give your users a product that exceeds expectations . 

Conduct UX research to optimize your product and create happier users

UX research saves you from making uninformed assumptions about what your users want. A strong UX research process helps you understand their habits and desires to make smart design decisions. 

Use our methods and best practices to really get to know your customers, nail your UX design, and turn curious visitors into delighted, loyal users.

Use UX research to make user-driven product improvements

Use Hotjar tools to help you understand your customers and enhance the user experience

FAQs about UX research

What are the benefits of ux research.

The primary benefit of conducting UX research is that it helps you provide your users with an optimal product experience. UX research gives you the data you need to make informed product decisions and delight your users at every step of their journey.

Who should conduct UX research?

Sometimes, teams will have designated UX or product researchers. However, people in many different roles can carry out UX research, including members of a marketing team, as well as product designers and developers.

What is the difference between UX research and UX design?

You can think of UX design as the implementation of UX research findings. While UX research is centered around gaining insights into user behavior and preferences, UX design is all about putting these insights into practice and designing a product that provides the best possible user experience. 

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Data-Driven Design: Quantitative Research for UX

How this course will help your career, what you will learn.

What quantitative research is and how it differs from qualitative

Why quantitative research is important

Alternatives to quantitative methods

Simple statistical analysis

Quantitative methods in detail: surveys, early-design testing, web/app analytics and A/B testing

Participant recruitment and screening

Quantitative research is about understanding user behavior at scale. In most cases the methods we’ll discuss are complementary to the qualitative approaches more commonly employed in user experience. In this course you’ll learn what quantitative methods have to offer and how they can help paint a broader picture of your users’ experience of the solutions you provide—typically websites and apps.

Since quantitative methods are focused on numerical results, we’ll also be covering statistical analysis at a basic level. You don’t need any prior knowledge or experience of statistics, and we won’t be threatening you with mathematical formulas. The approach here is very practical, and we’ll be relying instead on the numerous free tools available for analysis using some of the most common statistical methods.

In the “Build Your Portfolio: Research Data Project” , you’ll find a series of practical exercises that will give you first-hand experience of the methods we’ll cover. If you want to complete these optional exercises, you’ll create a series of case studies for your portfolio which you can show your future employer or freelance customers.

Your instructor is William Hudson . He’s been active in interactive software development for around 50 years and HCI/User Experience for 30. He has been primarily a freelance consultant but also an author, reviewer and instructor in software development and user-centered design.

You earn a verifiable and industry-trusted Course Certificate once you’ve completed the course. You can highlight it on your resume , your LinkedIn profile or your website .

Gain an Industry-Recognized UX Course Certificate

Use your industry-recognized Course Certificate on your resume , CV , LinkedIn profile or your website.

Our courses and Course Certificates are trusted by these industry leaders:

Is this course right for you?

This is a beginner-level course for anyone who wants to understand and apply quantitative research in user experience settings. This course is particularly valuable for:

• User researchers and UX practitioners interested in gaining insight into user behavior at scale.
• Project managers and stakeholders who want to help their team to understand the full range of research tools available to them.
• Stakeholders who are keen to get involved in and manage the creative process of developing a new product or service.
• Entrepreneurs looking to use quantitative insights to develop products that fit the market and users’ lives.
• Anyone who is interested finding out more about how users and interactive systems behave in actual use.

Learn and work with a global community of designers

When you take part in this course, you’ll join a global community and work together to improve your skills and career opportunities. Connect with helpful peers and make friends with like-minded individuals as you push deeper into the exciting and booming industry of creativity and design. You will have the opportunity to share ideas, learn from your fellow course participants and enjoy the social aspects afforded by our open and friendly forum.

Lessons in This Course

• Each week, one lesson becomes available.
• There’s no time limit to finish a course. Lessons have no deadlines .
• Estimated learning time: 28 hours 1 min spread over 8 weeks .

Lesson 0: Welcome and Introduction

• 0.1: Welcome and Introduction (39 mins) Preview Preview Start course now
• 0.2: Let Our Community Help You (1 min) Start course now
• 0.3: How to Earn Your Course Certificate (16 mins) Start course now
• 0.4: Expand Your Network and Grow Your Skills in Our Online Forums (5 mins) Start course now
• 0.5: Meet and learn from design professionals in your area (1 min) Start course now
• 0.6: Gain Timeless Knowledge Through Courses From the Interaction Design Foundation (21 mins) Start course now
• 0.7: Mandatory vs. Optional Lesson Items (7 mins) Start course now
• 0.8: A Mix Between Video-Based and Text-Based Lesson Content (6 mins) Start course now
• 0.9: Build Your Portfolio: Design Data Project (7 mins) Start course now
• See all lesson items See less lesson items

Lesson 1: Why Design with Data?

• 1.1: Welcome and Introduction (6 mins) Start course now
• 1.2: Introducing Quantitative Research Methods (17 mins) Start course now
• 1.3: How to Fit Quantitative Research into the Project Lifecycle (16 mins) Start course now
• 1.4: Qualitative and Quantitative Research – What’s the Difference? (15 mins) Start course now
• 1.5: Why Do Triangulation in User Research? (10 mins) Start course now
• 1.6: Why Care about Statistical Significance? (17 mins) Start course now
• 1.7: Pitfalls in Recruiting Participants for User Research (24 mins) Start course now
• 1.8: How to Screen Research Participants (11 mins) Start course now
• 1.9: Discussion Forum (6 mins) Start course now
• 1.10: Congratulations and Recap (10 mins) Start course now

Lesson 2: Statistics

• 2.1: Welcome and Introduction (5 mins) Start course now
• 2.2: Basic Statistics (33 mins) Start course now
• 2.3: Does Usability Follow a Normal Distribution? (21 mins) Start course now
• 2.4: Parametric vs Non-Parametric Statistics (27 mins) Start course now
• 2.5: Data Types (23 mins) Start course now
• 2.6: Hypothesis Testing (22 mins) Start course now
• 2.7: How to Choose a Statistical Test (24 mins) Start course now
• 2.8: How to Use Statistical Tests (17 mins) Start course now
• 2.9: How to Use Tests for Categorical Data (18 mins) Start course now
• 2.10: Using Percentages in Categorical Tests (12 mins) Start course now
• 2.11: Likert Scale Case Study (26 mins) Start course now
• 2.12: What Is Sampling in Data Analytics? (37 mins) Start course now
• 2.13: Correlation in User Experience (18 mins) Start course now
• 2.14: Effect Size and Power in Statistics (11 mins) Start course now
• 2.15: Confidence Intervals (12 mins) Start course now
• 2.16: Discussion Forum (6 mins) Start course now
• 2.17: Congratulations and Recap (31 mins) Start course now

Lesson 3: Surveys

• 3.1: Welcome and Introduction (18 mins) Start course now
• 3.2: Why and When to Use Surveys (17 mins) Start course now
• 3.3: How to Get Started with Surveys (31 mins) Start course now
• 3.4: Writing Good Questions for Surveys (28 mins) Start course now
• 3.5: Survey Bias (17 mins) Start course now
• 3.6: General Tips on Surveys (20 mins) Start course now
• 3.7: Ensuring Quality (30 mins) Start course now
• 3.8: Standardized Usability Questionnaires (21 mins) Start course now
• 3.9: Data Analysis and Significance in Surveys (29 mins) Start course now
• 3.10: Build your Portfolio Project: User Survey (7 mins) Start course now
• 3.11: Congratulations and Recap (31 mins) Start course now

Lesson 4: Early-Design Testing

• 4.1: Welcome and Introduction (5 mins) Start course now
• 4.2: Early-Design Testing (21 mins) Preview Preview Start course now
• 4.3: Getting Started with Early-Design Tests (35 mins) Start course now
• 4.4: Tree Testing (15 mins) Start course now
• 4.5: First-Click Testing (17 mins) Start course now
• 4.6: Ensuring Quality in Early-Design Tests (25 mins) Start course now
• 4.7: Data Analysis and Significance in Early-Design Tests (30 mins) Start course now
• 4.8: Tree-Testing Research Example (27 mins) Start course now
• 4.9: Build your Portfolio Project: Early-Design Testing (15 mins) Start course now
• 4.10: Discussion Forum (6 mins) Start course now
• 4.11: Congratulations and Recap (31 mins) Start course now

Lesson 5: Web and App Analytics

• 5.1: Welcome and Introduction (5 mins) Start course now
• 5.2: Analytics Data Types (16 mins) Start course now
• 5.3: When and Why to Use Analytics (23 mins) Start course now
• 5.4: Analytics and User Experience (13 mins) Start course now
• 5.5: The Mechanics of Analytics (39 mins) Start course now
• 5.6: Metric Categories in Analytics (22 mins) Start course now
• 5.7: Web Analytics Process (9 mins) Start course now
• 5.8: Identifying Key Stakeholders (18 mins) Start course now
• 5.9: Defining Primary Goals (35 mins) Start course now
• 5.10: Identifying the Most Important Site Visitors (38 mins) Start course now
• 5.11: Paths Through a Site (25 mins) Start course now
• 5.12: Determine KPIs (13 mins) Start course now
• 5.13: Ad Hoc Analyses (42 mins) Start course now
• 5.14: Analytics in the organization (19 mins) Start course now
• 5.15: Advanced Analytics (25 mins) Start course now
• 5.16: Data analysis case study: IxDF (40 mins) Start course now
• 5.17: Congratulations and Recap (36 mins) Start course now

Lesson 6: A/B and Multivariate Testing

• 6.1: Welcome and Introduction (5 mins) Start course now
• 6.2: Getting Started (39 mins) Start course now
• 6.3: What to Test (26 mins) Start course now
• 6.4: What’s Involved (35 mins) Start course now
• 6.5: An A/B Test Example (25 mins) Start course now
• 6.6: Redirect and Multivariate Test Examples (31 mins) Start course now
• 6.7: A/B and Multivariate Case Studies (41 mins) Start course now
• 6.8: Build your Portfolio Project: A/B and Multivariate Testing (15 mins) Start course now
• 6.9: Congratulations and Recap (31 mins) Start course now

Lesson 7: Course Certificate, Final Networking, and Course Wrap-up

• 7.1: Get Your Course Certificate (1 min) Start course now
• 7.2: Course Evaluation (1 min) Start course now
• 7.3: Continue Your Professional Growth (1 min) Start course now

Learning Paths

This course is part of 3 learning paths:

How Others Have Benefited

Louiselle Morand Salvo, Switzerland

“Very well structured (overall syllabus + individual lessons), useful tools, and very precise information. The feedback on the questions is detailed; I'm impressed by the work done by the teacher!”

Andrea Wilkins, United Kingdom

“The instructor is an incredible teacher. He was so engaging and felt so relaxed throughout. You can tell he's done this before. I could listen to him teach all day.”

Norman Laborde, Puerto Rico

“William explained complex concepts in a way that was approachable. The resources he offered were valuable and I have a good list of new books and bookmarks that resulted from the course.”

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• Frequently Asked Questions

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Course certificates will be given to participants when they have scored more than 70% or more of the total course points. For example, if a course contains ten lessons each with ten questions, you will receive a course certificate when the instructor has awarded you at least 70 points (70% of the total course points).

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Qualitative vs. quantitative ux research.

Summary:  Qualitative and quantitative methods both have their place in user research, but they address different issues in the UX design process. Understand the differences to pick the right method to learn what you need.

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Both these complementary types of user research play important roles in an iterative design cycle. Qualitative research informs the design process; quantitative research provides a basis for benchmarking programs and ROI calculations.

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Qualitative Research in UX: 7 Methods & Benefits

• February 22, 2023

Quantitative research gets a lot of hype, often leaving poor old qualitative research looking on from the sidelines. It may be because it’s often easier to conduct quantitative studies. There’s no human connection involved, and there’s usually less complex and nuanced data to sift through afterwards.

But if you’re in the camp that finds the prospect of qualitative research in UX daunting, then you’ve come to the right place. Below, we’ll outline 7 qualitative user research methods that’ll make your life easier, as well as tools that you can use to make it a breeze.

Firstly, let’s clear up the difference between qualitative and quantitative.

What’s the Difference Between Qualitative and Quantitative Research?

To put it simply, you’ll use quantitative research to gather data that’s numerical and measurable. Qualitative research, however, relies on the power of observation and subjective factors such as opinions and motivations.

With qualitative research in UX, results are more open to interpretation. This can make it trickier to interpret as it’s more time-consuming to conduct. Having said that, qualitative research must go hand-in-hand with quantitative research. Relying only on quantitative research methods will fail to uncover the entire story. Mere numbers lack context and, more importantly, emotion.

When to Use One Over the Other

If you’re tracking how many users click on a button, that’s quantitative research. While it might be important for tracking conversions, for example, it doesn’t uncover the whole story. What about all those people that aren’t clicking on the button? You know they’re not doing it, but quantitative research will never reveal why.  For that, you’ll need qualitative research.

You could conduct a survey or ask open-ended questions in a user interview. You can also use usability testing software like Maze to uncover why users do what they do. After all, it’s not always a conscious decision to avoid clicking a button. Some users may not have even seen the button!

Quantitative research can never reveal these kinds of insights, but you still need it to inform your qualitative research focus. Leaving one out over in favor of the other is like trying to bake bread but deciding to skip on the flour. When the two are combined and given equal weight, that’s when the magic happens.

The Evolution of Qualitative Research in UX

For a long period of time, qualitative research was limited to surveys…and more surveys. But surveys aren’t super effective because they’re often limited to a pre-defined set of questions, which may overlook aspects the survey creator hadn’t even thought to ask about. Also, surveys remove the ability to ask follow-up questions if the customer has something interesting to say. With the rise of the user interview tools , and advances in AI, qualitative research is now far more feasible, accurate, and accessible. Collecting emotional insights is easier than ever.

"The worst thing that contemporary qualitative research can imply is that, in this post-modern age, anything goes. The trick is to produce intelligent, disciplined work on the very edge of the abyss." David Silverman, Interpreting Qualitative Data Tweet

While it’s evolved in many incalculable ways, here are four solid improvements that today’s UX qualitative research methods have adopted.

• More user-centered. Over the years, qualitative research in UX has become more user-centered. It holds a greater value in understanding users’ perspectives and experiences. This enhanced focus can be found in qualitative user research methods like user interviews, usability testing, and in focus groups.
• More diverse methods. There are far more methods to conduct quality qualitative research than there were previously. In addition to the traditional methods outlined above (user interviews and focus groups), researchers are now using methods such as diary studies, participatory design, and contextual inquiry to gather data on users’ experiences.
• More empathetic. Empathy is crucial to qualitative research in UX. If you don’t connect with the user, you don’t build for the user. By having a deeper understanding of the users’ needs and wants, techniques like empathy mapping and persona creation have blossomed.
• More collaborative research. Qualitative research in UX has become more collaborative, with a greater emphasis on involving stakeholders in the research process.

Unfortunately, not all stakeholders can easily access specialized user research repositories as the learning curve is too high for what they need it for. If you or your team are facing a similar problem, you might want to try out a free solution: tl;dv.

tl;dv is a remote UX research tool that enables you to record, transcribe, and create timestamps so that you can share the most important parts of your user interviews (or any other call) with ease! Gone are the days of stakeholders struggling to access the voice of the customer . Now they can open a hyperlink in Slack, Notion, or their work chat of choice, and immediately watch the most crucial parts of the recorded user research.

On top of this, if a stakeholder, or anyone else, wants to find a meeting where a specific topic was talked about, they can use the powerful search function by typing in a keyword and it will automatically generate a list of all the videos in which the transcript mentions that keyword.

That’s not all. tl;dv empowers you to take your user research to the next level. Its automated note taking feature encourages you to be fully present in the conversation so that you don’t miss a beat, meanwhile, you’re able to manually add notes where you see fit in a smooth and seamless manner so that you get the best of both worlds. At the end of each meeting, you’ll also receive an AI-generated summary of action points. 

Your qualitative research for UX has never been easier.

7 UX Research Qualitative Methods That’ll Make Your Life Easier

1. usability testing.

While usability testing can be performed one-on-one in a lab, virtual products or online services like websites or apps can be tested effectively and remotely through modern tools and software. 

For usability testing, you essentially observe the user with your product. You’ll watch how they interact with it to help identify pain points, areas for improvement, and potential usability issues.

Some tools and software that product teams can use for usability testing include UserTesting, Maze, Lookback, UserZoom, and Optimal Workshop.

2. User Interviews

User interviews are one of the most reliable ways of arriving at qualitative-derived insights. Essentially, it’s when researchers conduct one-on-one interviews with users to gather data on their goals, behavior, attitudes, and needs. Regardless of whether the interviews take place in person or remotely, this style of research is typically time-consuming, exhausting, complex, and difficult to document.

Until now…

As mentioned above, tl;dv makes the perfect sidekick for user interviews . It’s the best way to accurately capture the users’ needs , wants, and pain points, as well as document them in an effective and easily accessible manner. It’s the quintessential tool for any qualitative user researcher.

It works with both Zoom and Google Meet so you won’t have to switch up your interview style. This actually unbalances the decision making in regards to whether to conduct an interview in person or online. Online meetings can be recorded, transcribed, automatically summarized, and include speaker recognition . The juiciest insights need to be rewatched and shared. It’s impossible to effectively share what a user said and felt in an in-person interview.

3. Heat Mapping

Heat mapping is one of the best UX research qualitative methods because it allows researchers to track and analyze user behavior on a website or app. Heat maps can provide insights into where users are clicking, scrolling, and spending time, which provides a massive boost when it comes to making informed design decisions. 

The most popular heat mapping tool is Hotjar , which offers to let you know everything you ever wanted to know about your website that analytics never told you. Other options for heat mapping tools include Crazy Egg, Mouseflow, and ClickTale.

4. Participatory Design

Participatory design is a qualitative UX research method that involves users in the design process in order to understand their perspectives and ensure that their needs are met.

It can take many forms, such as co-design workshops or user testing with prototypes. At its most basic, users are given creative materials in order to construct their ideal experience. This allows researchers to uncover what matters most to them and why.

Product teams can make use of these excellent tools for participatory design: Miro, Figma, InVision, and Sketch.

5. Focus Groups

Focus groups consist of group discussions about a product or a service to explore new perspectives and identify common themes. It’s a tried and tested method of qualitative user research that can provide insights into user behavior, attitudes, and preferences. 

Often, focus groups are conducted in person, but times are changing. A single Google Meet can hold 100 participants, while a Zoom call can have as many as 300! With tl;dv in the meeting, its powerful AI speaker recognition feature will generate an accurate transcript even with dozens of speakers . Oh, and it’s FREE !

6. Journey Mapping

Journey mapping does exactly what it says on the tin: it maps the customer’s journey and interactions with a product or service. It’s a visual representation which is best used to unearth pain points and opportunities for improvement.

Journey maps are actually a qualitative UX research method that includes some of the others. Interviews, surveys, and user testing all collide to create the customer journey map. This is a way of planning a broader user experience design strategy, which may include plans to redesign specific touchpoints, implement new technologies, or even improve customer support.

Some tools and software that product teams can use for journey mapping include Smaply, Canvanizer, UXPressia, and Lucidchart.

7. Diary Studies

Diary studies are a longitudinal way of measuring the qualitative user experience. Basically, it’s a research method in which data is collected from the same participants over an extended period of time. It typically lasts months.

This research method involves asking participants to record their experiences, behaviors, and thoughts over time, usually in a type of diary, hence the name.

In diary studies, the participants are all recording their personal experiences, but they may use different devices depending on the vision of your research. Whether they write a diary on paper, or keep a digital diary with a camera or smartphone app will depend on your research objectives and how you want to collate the data at the end. 

One of the drawbacks of diary studies is that it can only be done for data that is easily recorded by the participants. This completely rules out any subconscious decisions, which are said to influence 90-95% of human behavior .

If your product team wants to include diary studies into their qualitative user research, then tools like Dscout, Moment Diary, ExperienceFellow, and Qualtrics will be helpful.

Take Your Research Game to the Next Level

With these 7 tips for qualitative research in UX, and a clear understanding of the differences between quantitative and qualitative research, your research game is ready to rocket to the next level. 

Don’t forget to invite tl;dv to your user interviews and focus groups. Your future you will thank you for all the time, energy, and effort saved when using this tool to share actionable insights.

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Should You Prioritize Quantitative or Qualitative Data?

Quantitative and qualitative research methods are often treated as opposites. But to make the best possible product, you need both.

User research plays a vital role in the product design process. The more we learn about our users’ needs and wants, the better design we can create for them. And the data we collect plays a crucial part in this process.

We can define two types of data — quantitative and qualitative — and every kind of data has its own attendant type of research. On the surface, quantitative and qualitative research can look similar. After all, they both analyze how users interact with a product. They serve different purposes, however, and you need to understand the distinctions. Once you grasp the differences between quantitative and qualitative data, you can understand when and how best to use each of them.

Guidelines for Collecting Data

No matter what type of data you want to collect, you should always keep the following four things in mind:

• Have a clear goal for your research . Why do you want to collect data in the first place? A clear goal will make your research more focused. For example, you might want to optimize the product checkout experience to reduce the total number of cart abandonments by 50 percent. In this case, you will focus only on checkout user flow and collect key conversion metrics targeted at solving this problem.  
• What do you expect to achieve? What is the product’s expected performance? You need to have a reference point to interpret your data. A reference point might be an expected task-completion time, success rate or some other measurable metric. In our hypothetical situation, you might want the average checkout experience to be less than a minute.  
• Number of test participants . How many people should participate in your research? Although every product is different and suggesting a one-size-fits-all number of test participants is impossible, I can offer a very good starting point. For quantitative research, you need a statistically significant number of people to make a data-informed decision. Quantitative research typically requires dozens of test participants (typically, more than 20 to get meaningful results). Qualitative research, on the other hand, involves a small number of users. According to the NNGroup, it’s possible to uncover 85 percent of potential usability problems with just five users .  
• Relevant demographics. It doesn’t make much sense to collect data from people who won’t use your product. You need to recruit participants who match your target demographics as defined in your user persona .

Quantitative Data

Quantitative data can be measured in numbers. This type of data answers “How?” questions. For example:

• How many people visited this page in the last month?  
• How much time does it take for a user to create an account in our service?

Qualitative data is typically provided in the form of metrics (i.e., conversion rate, average time on task, task competition rate, etc.).

When to Do Quantitative Research

The goal of quantitative research is to see how users interact with a product and identify areas where they might need extra help. Quantitative research can be done at any stage of the product design process, but it ’ s the most effective at the validation stage, either during usability testing or after the product’s release to the market. It helps researchers to gather data about what users do with a product and find patterns in their interactions. This information helps the product team to create a foundation for further benchmarking.

Quantitative research is also very helpful for calculating return on investment. You can employ quantitative methods during redesign iterations to compare the new version ’ s performance with a previous one. These findings are beneficial when you want to convince executives that your design team is moving in the right direction.

Quantitative Research Methods

Here are a few popular quantitative research methods:

• Surveys . A rating survey (“Please rate your experience on a scale from one to five”) and questionnaires with set choices (“Which feature from this list is the most valuable for you?”) are by far the most commonly used quantitative research methods.  
• A/B and multivariate testing . A/B and multivariate testing can help you compare different versions of your design and see which one performs better. A/B testing involves creating two different versions of the same user interface element (for instance, different colors for a call to action button on a landing page) and then shows each version to different users to see which version performs best. Multivariate testing is based on the same idea but involves testing a few UI elements at once (i.e., modifying the color, copy text and position of a call to action button).  
• Web analytics tools . Tools like Google Analytics and Hotjar can help you collect information about what people do in your live product — where they go, what they click and what features they use.  
• Eyetracking studies . Eyetracking is a technique that tracks users’ eyes as they move across an interface. When many participants perform the same task on the same interface, researchers can easily notice any trends.

Practical Tips for Quantitative Research

The goal of quantitative research is to reduce the risk of biased results, which give you incorrect assumptions about user behavior. They can lead the team in the wrong direction and make them invest time and effort in building something that does not bring any value to the users. Biased results can be come from the participants’ side (typically caused by social desirability effect or incorrectly understood assignments) or the researchers’ side (when researchers interpret the data to prove their point of view). Here are a few simple tips that will help you minimize bias:

• Do not vary the study conditions between sessions . Ensure that your study sessions are all run in the same environment. Do not modify the tasks that you want participants to complete along the way. For example, do not make one session in person and another remote because it will be harder to analyze and compare the results.  
• Make the assignments clear . All participants should understand the same thing when they read the task. The instructions should be crystal clear so participants know exactly what they should do. Don’t leave any room for interpretation or you could see too much variance in the results.  
• Invite multiple researchers to analyze data . Collect the feedback from a few researchers to see how they interpret the data.

Qualitative Data

Whereas quantitative research is focused on finding patterns, qualitative research seeks to discover the underlying meanings of those patterns. Qualitative data is generally non-numerical information that helps researchers gain deep contextual understandings of users and explain their behavior. Researchers aim to find answers to “Why?” questions like:

• Why did people visit this particular page?  
• Why are people more interested in this feature rather than other features?

When to Do Qualitative Research

Qualitative research is typically conducted early on in projects because the insights it reveals can dramatically alter product design. It can directly inform the design process. By identifying the core product design problems right at the beginning of the design process, it’s possible to cut both the cost and time of production.

Qualitative research can also be valuable as a follow-up activity for quantitative research. For example, when you know, based on quantitative data, that 60 percent of your users can’t complete a particular task in your product, you probably want to conduct qualitative research to better understand what problems are derailing the users.

Qualitative Research Methods

Researchers typically obtain qualitative data through first-hand observation. Any of the following methods are common:

• In-depth user interviews . This is a process in which a researcher asks one participant questions about a topic of interest (i.e., a particular part of a product) to learn about it from the user’s perspective. For qualitative research, a researcher should ask open-ended questions to generate more behavioral data. For instance, you should ask more questions like “How do you feel about this product?” to give the user as much leeway as possible in their response.  
• Focus groups . A focus group is a small but demographically similar group of people whose reactions to a product are studied by researchers. The group typically consists of six to eight participants. They meet and discuss a product for about two hours. This discussion is moderated by a researcher who asks relevant questions and also maintains the group ’ s focus.  
• Contextual inquiry . Contextual inquiry involves observation of users in a real-world working environment as they interact with a product or service. The information produced by contextual inquiry is highly reliable since researchers see how people interact with a product or service in their natural environment. It’s also highly detailed, meaning that this type of research helps researchers better understand the context of a user’s interaction with a product.

Practical Tips for Qualitative Research

In comparison with its quantitative counterpart, qualitative research offers much more freedom both for researchers and participants. Here are a few things you should consider when running research:

• Use a think-aloud protocol for usability testing . This protocol allows participants to talk about their experiences, thoughts and feelings as they interact with a product so that researchers can gather more valuable insights about real user behavior.  
• Strive for flexibility of research . If you discover that a specific task doesn ’ t give you the insights you need, rework it before running the next session with a new participant.  
• Record videos of user interactions . The videos from qualitative research can be very useful for further analysis. It’s also possible to use videos to convince the team members and stakeholders to invest time in improving user experience since they will see for themselves the problem that participants experience. 

More on the Ins and Outs of Research Make Your Product Research Matter

Quantitative or Qualitative Data? Why Not Both?

Quantitative and qualitative data are not competitors. Rather, they go hand in hand by reinforcing each other. Both qualitative and quantitative data are essential in the product design cycle because they help product teams iterate design and measure the results of a new interaction. Qualitative data can help identify the areas where users face problems and ideate a solution to these problems. Once you introduce changes in your design and release a new version, this version can be evaluated and compared against the initial version using quantitative data.

Recent Expert Contributors Articles

A behind-the-scenes blog about research methods at Pew Research Center

For our latest findings, visit pewresearch.org .

How quantitative methods can supplement a qualitative approach when working with focus groups

(Related post:  How focus groups informed our study about nationalism and international engagement in the U.S. and UK )

Pew Research Center often collects data through nationally representative surveys, and we use focus groups to supplement those findings  in interesting ways  and  inform the questionnaire design process  for future work.

When conducting focus groups, we typically use  qualitative  methods to understand what our participants are thinking. For example, we tend to hand-code key themes that come up in discussions. But in our latest focus group project, we wondered if we could use  quantitative  methods, such as topic models, to save time while still gaining valuable insights about questionnaire development.

Some of these methods worked well, others less so. But all of them helped us understand how to approach text-based data in innovative ways. In general, we found that quantitative analysis of focus group transcripts can generate quick, text-based summary findings and help with questionnaire development. But it proved less useful for mimicking traditional focus group analysis and reporting, at least with the specific quantitative techniques we tried.

In the fall of 2019, the Center held  focus groups in the United States and United Kingdom  to talk with people about their  attitudes toward globalization . These discussions focused on three different contexts: participants’ local community, their nation of residence (U.S. or UK) and the international community.

After conducting 26 focus groups across the two nations, we transcribed the discussions into separate files for each group. For our quantitative analysis, we combined all of the files into one .csv document where each participant’s responses — whether one word or a short paragraph — corresponded to one row of the spreadsheet. To prepare the text for analysis, we  tokenized the data , or split each line into individual words, and further cleaned it by removing punctuation and applying  other preprocessing techniques  often used in natural language processing.

Preliminary quantitative findings

As a first step, we conducted a basic exploration of focus group respondents’ vocabulary. Several words frequently emerged among participants in both the U.S. and UK, including “country,” “live” and “feel,” all of which appeared in at least 250 responses across groups in each country. (This analysis excludes pronouns, articles and prepositions that are common in all spoken English, such as “he,” “she,” “they,” “a,” “the,” “of,” “to,” “from,” etc. Names of cities where focus groups took place and text from group moderators are also excluded from analysis.)

We also found that several words and phrases distinguished the U.S. focus groups from those in the UK. Terms like “dollar” and “Republican” were among the most common terms only used by the American groups, while the UK’s national health system (“NHS”) and legislative body (“parliament”) appeared frequently in the British groups but were never used by Americans.

As an exploratory tool, this kind of analysis can point to linguistic distinctions that stray from the predetermined topics included in a focus group guide. For instance, while we asked the groups in oblique ways about what it takes to be American or British, respectively, we never explicitly asked about immigration or minority groups in their country. Nonetheless, “African Americans” and “Native Americans” exclusively arose in the U.S. groups, while “Polish” and “mixed race” people were discussed in the UK. This told us that it might be worthwhile for future survey questionnaires to explore topics related to race and ethnicity. At the same time, it’s possible that our focus groups may have framed the conversation in a unique way, based on the participants’ racial, ethnic or immigration background.

Word correlations

We used another computational tool,  pairwise correlation , for some exploratory text analysis that measures how often words co-occur compared with how often they are used separately. Using three terms related to key themes that the focus groups were designed to study — “global,” “proud” and “immigrant” — we can get a sense of how focus group participants talked about these themes simply by identifying other words that were positively correlated with these topical terms. By further filtering these other terms to those that were mainly used in just one country, we can capture unique aspects of American and British views on global issues, national pride and immigration.

Both British and American participants discussed their nationalities when the conversation turned to pride. For instance, the words that most commonly appeared alongside “proud” in each country were “British” and “American,” respectively. (We considered the words “America” and “American” as separate terms, rather than variants of the same term.) Though “proud” among Britons often involved discussion of the word “flag,” “proud” in the U.S. correlated with “military.” Of course, correlation alone does not reflect whether these discussions had positive, negative or neutral connotations.

Discussions about migration and global issues — including “globalization,” which we shortened to “global” in our text processing — also varied across the two countries. When U.S. respondents used the word “immigrant,” they were also likely to use words like “illegal,” “legal,” “come” and “take.” By comparison, Britons who used the term were liable to do so alongside terms like “doctor” or “population.”

British participants used the word “global” alongside terms related to business (“company,” “industry,” “cheaper”) and global warming (“climate”). In the U.S., on the other hand, the discussion about globalization and immigration often accompanied terms like “hurt,” “China,” “benefit” and “take.”

Pew Research Center has conducted several surveys on the topics of  migration ,  climate change  and  views of China , among others. Our focus groups confirmed that these issues play a part in how individuals see their country’s place in the world, though they also highlight that, in different nations, people approach these topics in distinct ways that may not be immediately evident in traditional survey questions.

Topic models

In recent years, the Center has explored the use of  topic models  for text-based data analysis. This method finds groups of words that appear alongside one another in a large number of documents (here, focus group responses), and in the process finds topics or themes that appear across multiple documents. In our attempt to quantitatively analyze this set of focus group transcripts, we had somewhat limited success with this approach.

On first pass, we used a probabilistic topic model called  latent Dirichlet allocation , or LDA. But LDA often created topics that lacked coherence or split the same concept among multiple topics.

Next we turned to  structural topic models  (STM), a method that groups words from documents into topics but also incorporates metadata about documents into its classification process. Here, we included a country variable as one such “structural” variable. STM allowed us to set the number of topics in advance but otherwise created the topics without our input. (Models like these are often called “unsupervised machine learning.”) We ran several iterations of the model with varying numbers of potential topics before settling on the final number.

( For more on the Center’s use of topic modeling, see:  Making sense of topic models )

Our research team started at 15 topics and then increased the number in increments of five, up to 50 topics. With fewer than 35 topics, many word groupings seemed to encompass more than one topic. With more than 35 topics, several topics that appeared distinct began to split apart across topics. There was no magic number, and researchers with the same data could reasonably come to different conclusions. Ultimately, we settled on a model with 35 topics.

Some of these topics clearly coalesced around a certain concept. For instance, we decided to call Topic 11 “Brexit” because its most common terms included “vote,” “leave,” “Brexit,” “party” and “referendum.” But while this topic and others appeared quite clear conceptually, that was not uniformly the case. For example, one topic looked as though it could relate to crime, but some terms in that topic (e.g., “eat” and “Christian”) did not fit that concept as neatly.

We named some of the topics based on the themes we saw — “Legal immigration,” for example, and “European trade.” But as other researchers have noted, that  does not necessarily mean  the word groupings are  definitely  about that theme. In this case, we used topic models as an exploratory analysis tool, and further research would be needed to validate each one with a higher degree of certainty and  remove conceptually spurious words .

Another important consideration is that topic models sometimes group topics differently than researchers might be thinking about them. For that reason, topic models shouldn’t be used as a measurement instrument unless researchers take extra care to validate them and confirm their assumptions about what the models are measuring. In this project, the topic models simply served to inform questionnaire development for future multinational surveys. For example, Topic 12 in this experiment touches on issues of how spoken language relates to national identity, and future surveys may include a question that addresses this concept.

One helpful aspect of the topic model approach is that it allowed us to see which topics were more prevalent in the U.S. or UK, or if they appeared in both. American respondents, for example, more frequently discussed topics related to the U.S. and legal immigration, while British respondents more often discussed topics related to Brexit and trade in Europe. Topics that researchers coded as “language” and “housing” appeared with relatively the same prevalence in both countries.

However, characteristics of the data and problems with initially interpreting topics can cause further difficulties in this analysis. For instance, a topic we labeled “protection” was much more prevalent in American focus group discussions. That might have led us to assume that Americans are more concerned than their British counterparts with safety-related issues. But the focus groups we conducted were not nationally representative of the populations of either country, so we couldn’t draw this type of conclusion from the analysis. Additionally, because the topic itself might include words that have no relation to the concept of protection, researchers would likely need to consult the full transcripts that mention these topics — as well as external resources — before using this for questionnaire development.

Text-based classification

Qualitative coding of focus group transcripts is a resource-intensive process. Researchers who carried out the qualitative analysis of these transcripts considered using a  Qualitative Data Analysis Software, or QDAS . These are tools designed for qualitative researchers to analyze all forms of qualitative data, including transcripts, manually assigning text into categories, linking themes and visualizing findings.  Many disciplines  employ these methods for successfully analyzing qualitative data.

We wondered if quantitative methods would let us achieve similar ends, so we explored ways to potentially streamline procedures with quantitative tools to minimize the time and labor needed to classify text into topics of interest. Unlike with topic models, a text-based classification model uses predetermined topics, or variables, for the algorithm to classify. (This falls into a broader category called “ supervised machine learning .”) A successful classification algorithm would mean that we could avoid having to read every transcript to determine what content belonged to certain groups, or having to make the kind of subjective judgments that are necessary with qualitative software.

We used an  extreme gradient boosting model  (XGBoost) to classify focus group responses as relevant or not relevant to three different topics: immigration, the economy and the local community. We chose these topics because each emerged in the course of the focus group discussion — some as overt topics from prompts in the focus group guide (e.g., the local community), others as organic themes when people discussed their neighborhoods, national identity and issues of globalization (e.g., immigration and the economy).

Two of our researchers coded the same set of randomly selected focus group responses, about 6% of approximately 13,000 responses from all groups combined. They used a 1 to indicate the response was about a topic and 0 to show it was not. From the set of coded responses, each of the three topics appeared at least 70 times.

The model’s performance proved lackluster. When we compared the model to our hand coding, the accuracy rate ranged from 85% to 93%. But it also failed to identify the topic in most cases where it occurred, meaning that much of the accuracy was driven by matching on instances coded as 0 (i.e. the response is  not  about that topic) since 0 was much more prevalent across categories. One can liken this to a test for a rare disease. If only 1% of people in a population have a disease and the test returns only negative results to all people tested, the accuracy would be high — 99% of tests would be correct. But the test would have little utility since there would be no positive matches in instances where people were actually infected.

Using a measure similar to accuracy called the  kappa , a statistic that examines agreement while adjusting for chance agreement, we found that the classifier performed poorly with a kappa of no more than .37 for two of our topics. In addition, we looked at the models’  precision and recall , metrics that help evaluate the effectiveness of a model. Precision ranged from 20% to 100%, while recall ranged from 4% to 27% among two of the topics. On the third topic — the local community — the model assigned zero to all cases.

The quantitative techniques that we explored in this post do not completely replace a traditional approach to qualitative research with focus group data. Using a quantitative approach, however, can aid in exploratory analysis and refining questionnaire development without having to attend every group in person or read through hundreds of pages of text. The tools we used are far from exhaustive, and as the Center continues to use focus groups as part of the research process, we are hopeful that we can learn more about how to employ innovative techniques in our analysis.

This post benefited from feedback provided by the following Pew Research Center staff: Dennis Quinn, Patrick van Kessel and Adam Hughes.

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Methods Café: Assistance in Qualitative and Quantitative Methods

Methods Café is an initiative by the Department of Political Science to support MA and BA students with methodological and technical questions they encounter in their ongoing research projects (e.g. MA thesis, BA thesis). Our PhD students from the Doctoral School of Political Science, Public Policy and International Relations, Cagla Ekin Guner and Ildar Daminov are available for your questions every week in person or online.

Assistance in Qualitative Methods

Cagla Ekin Guner   / Room B402/ can assist MA students with methodological and technical questions for projects relying on qualitative research designs, including methods (e.g., case study, process tracing), questions on the collection/generation of qualitative data (e.g., designing and conducting interviews, survey design) and their analysis (e.g., thematic analysis, concept formation, qualitative coding) with qualitative data software(e.g., Nvivo, MaxQda).  Book a consultation with Ekin using this link in  Calendly . 

When filling in the Calendly form, add a short note about what your question is. This helps Ekin to prepare in advance. Please note that Ekin offers both zoom and in-person meetings. You can state your preference in Calendly.

She will not be available on the week of 6-12th of May. On the week of 13-19th of May, she is only available for zoom meetings.

Assistance in Quantitative Methods

Ildar Daminov /Room C401/ is a 2nd year PhD student in Political Science (Political Economy track). He can assist MA students with methodological and technical questions for projects relying on quantitative research designs. You can approach Ildar with any questions on variable measurement (DV, IV, control variables), hypotheses tests, regression models, regression diagnostics, causal inference, and fixing mistakes in your R code. Ildar can also assist you with basic/intermediate questions in the area of machine learning related to quantitative text analysis.  Book a consultation with Ildar using this link in  Calendly . 

When filling in the Calendly form, add a short note about what your question is. This helps Ildar to prepare in advance.

Quantitative, Qualitative, Mixed Methods, and Triangulation Research Simplified

• PMID: 38567919
• DOI: 10.3928/00220124-20240328-03

For the novice nurse researcher, identifying a clinical researchable problem may be simple, but discerning an appropriate research approach may be daunting. What are the differences among quantitative, qualitative, mixed methods, and triangulation research? Which method is applicable for the study one wants to conduct? This article discusses the two main research traditions (quantitative and qualitative) and the differences and similarities in methods for front-line nurses. It simplifies and clarifies how the reader might enhance the rigor of the research study by using mixed methods or triangulation. The four types of research are described, and examples are provided to support readers to plan projects, use the most appropriate method, and effectively communicate findings. [ J Contin Educ Nurs. 202x;5x(x):xx-xx.] .

Mixed Methods Designs: vitenskapsteoretiske posisjoner – muligheter og utfordringer

• Kari Røykenes VID vitenskapelige høgskole https://orcid.org/0000-0001-7641-5737
• Sigrunn Drageset HVL, Høgskulen på Vestlandet https://orcid.org/0000-0003-4481-7656

Emneord (Nøkkelord):

Målet med essayet er å drøfte vitenskapsteoretiske posisjoner og hvilke implikasjoner disse har for å anvende mixed methods design. Det finnes ulike måter å kombinere kvalitative og kvantitative metoder, en av dem kalles sekvensiell design, et design forfatterne av essayet har erfaring med. Essayet vil gi leseren en innføring i mixed methods, før den drøfter muligheter og utfordringer. Til slutt beskrives kort muligheter og utfordringer forfatterne erfarte ved å anvende sekvensielt design i egne studier .

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Brunborg, G. S., Scheffels, J., Tokle, R., Buvik, K., Kvaavik, E., & Andreas, J. B. (2019). Monitoring young lifestyles (MyLife) - a prospective longitudinal quantitative and qualitative study of youth development and substance use in Norway. BMJ Open 9, e031084. https://doi.org/10.1136/ bmjopen-2019-031084

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Creswell, J. W., & Clark, V. L. (2011). Designing and Conducting Mixed Methods Research. (2nd Edition ed.). SAGE.

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Creswell, J. W., & Clark, V. L. P. (2018). Designing and Conducting Mixed Methods Research, (3rd ed. ed.). Thousand Oaks, CA.

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Creswell, J. W., & Guetterman, T. C. (2021). Educational Reseach. Planning, Conducting, and Evalueting Quantitative and Qualitative Reseach (sixed edition ed.). Pearson Education Limited.

Doyle, L., Brady, A.-M., & Byrne, G. (2009). An overview of mixed methods research. Journal of Research in Nursing, 14(2), 175-185. https://doi.org/10.1177/1744987108093962

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Drageset, J., Eide, G. E., & Hauge, S. (2016). Symptoms of depression, sadness and sense of coherence (coping) among cognitively intact older people with cancer living in nursing homes-a mixed-methods study. Peer J, 4 (e2096). https://doi.org/10.7717/peerj.2096

Drageset, S. (2012). Psychological distress, coping and social support in the diagnostic and preoperative phase of breast cancer. [Doktorgradsavhandling] Universitetet i Bergen. https://hdl.handle.net/1956/6139

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Morgan, D. (2007). Paradigms Lost and Pragmatism Regaine. Journal of Mixed Methods Research, 1(1), 48-76.

Morse, J. M., & Niehaus, L. (2009). Principles and procedures of mixed methods design. Walnut Creek, CA.

Polit, D. F., & Beck, C. T. (2017). Nursing Research: generating and assessing evidence for nursing practice (10th ed.). Wolters Kluwer.

Ree, E., Wiig, S., Braithwaite, J., & Aase, I. (2020). To what degree and how do healthcare professionals in nursing homes and homecare practice user involvement? A mixed methods study. Tidsskrift for omsorgsforskning, 6(2), 119-136.

Røykenes, K. (2015). Testangst hos sykepleiestudenter: «Alternativ behandling». [Doktorgradsavhandling] Universitetet i Bergen. https://www.nb.no/items/URN:NBN:no-nb¬_digibok_2020022107503

Sale, J. E., Lohfeld, L. H., & Brazil, K. (2002). Revisiting the quantitative-qualitative debate: Implications for mixed-methods research. Quality and quantity, 36, 43-53. https://doi.org/10.1023/A:1014301607592

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