quantitative ux research methods

Quantitative UX Research: Overview

• First Online: 01 June 2023

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• Chris Chapman 3 &
• Kerry Rodden 4  

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What is Quant UX research? And, just as importantly, what is not Quant UX research? If you are wondering whether it might be a good fit for you, this chapter will help you answer those questions.

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Chapman, C., Rodden, K. (2023). Quantitative UX Research: Overview. In: Quantitative User Experience Research. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-9268-6_3

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• User Research Designers
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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.

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Miklos Philips

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0.1 - Welcome and Introduction

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4.2 - Early-Design Testing

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UX Research Simplified: Explaining The Key Methods

Unravel the complexities of UX research with straightforward methods, empowering teams to create user-centric products with confidence.

14 min read

UX Research

Ux research definition.

Product design is an essential part of any production process. UX research enables data to be compiled, analyzed, and understood to inform the decisions made during the design phase. UX research consists of, but is not limited to, observation, inquisition, and in-depth research of the nature of how users will interact with the product or service in question. As feedback is provided, it serves to refine designs to be more intuitive to better serve the needs of the product or service’s users.

Importance of UX Research

Performing UX research is imperative during product design and development because it informs the performing party about various aspects of how users interact with their product. This serves to drive the nature of user interaction with the product, any refinements that would bolster usefulness, and how to make the product more interesting and engaging to improve the level at which users enjoy interacting with it.

Source: NN Group

By conducting UX research, product designers get crucial insights into what users need, prefer, like, dislike, and other motivating factors that make the product more palatable to their satisfaction. By allowing data to drive development, businesses can figure out what aspects of their product need to be improved, as well as how to allocate resources to prioritize those improvements with the most significant impact.

The true winner in any market is adopting new ideas while sticking to contemporary trends. User research allows for a more robust competitive edge in product design by identifying those trends and investigating products offered by competitors. Additional insight is also gained from user interviews, surveys, and other testing methods, as it permits direct feedback about the target audience’s interaction with the product.

The feedback is invaluable in that the business understands what a customer is looking for from the product. Even more pivotal is the fact that it points out shortcomings or things that the users would like improved, which can then be applied to a future iteration of the design through careful study of data points with analytic tools like Hotjar and Google Analytics. Systemic monitoring of user interaction with the product yields valuable insights into any adjustments that would benefit the product’s design, as well as how any such changes impact user engagement.

By and large, UX research points out areas where the product can be improved as well as where opportunities for enhancement exist. Through UX research, companies understand what is working and not working, working well, or could work better about their products. Leveraging this knowledge allows them to improve in those areas of design, satisfy users more, and increase their revenue from successfully implementing pertinent changes.

Source: LinkedIn

UX Research’s Role In Helping Businesses

Improvements to products yielded by UX research bring several key benefits to the table for a business, including the attention of prospective customers (through sign-ups), conversions (increased sales), and a boost in customer satisfaction. The latter leads to positive feedback, yielding better reviews and higher NPS ( net promoter scores ). Satisfied customers will become repeat customers, as their loyalty will secure future earnings. On the expense end, better user interaction with products leads to less need for customer service interactions, which reduces costs on that end.

In other words, UX research leads not just to an overall boost in user experience , but its integration into the design and development process also pays off financially by saving businesses money and time, all while getting to know and understand their audience better, including in-depth insight into user goals, mental models, and pain points.

UX Research Method Types

Understanding how and why issues are solved drives effective qualitative UX research methods, while quantitative measures can produce actual metrics (how many, how much, etc.) that help businesses allocate resources appropriately and resolve potentially significant issues with the design and the methodology behind it.

Source: Maze

Qualitative UX Research Methods

Understanding opinions, motivations, and experiences, or in other terms, why users behave in particular ways when interacting with products, is at the heart of qualitative UX research methodology. When a company has a better understanding of user behaviors, it can work out more finely-tuned solutions for those things the users are not fully satisfied with. Such methods include conducting user interviews, studying diaries and ethnography as well as utilizing focus groups.

Explorations of user attitudes, experiences, preferences, and behaviors are best relayed from the users themselves, making user interviews a significantly effective method of qualitative research. By conducting structured, targeted conversations with users wishing to participate, researchers can understand users on a pragmatic and psychological level. Such interviews can be done either remotely via phone or video, as well as via in-person sessions.

The data that is derived from user interviews can then help inform and guide the business’s future decisions in terms of design and development. After sufficient interview sessions in Q&A format, a UX researcher will better understand how users interact with the business’s service or product. In these interviews, users may also bring up formerly unconsidered aspects of a product that are problematic, invaluable information for design improvements that many quantitative methods are unlikely to yield.

UX researchers conducting effective user interviews ensure that the interviews consist of carefully crafted questions that are not leading or suggestive. Instead, the questions are open-ended, and as answers are offered by the user in the interview, researchers should attentively consider the answers and ask follow-up questions. These questions should include what type of solutions users are currently using to attend to the problems they face with the product. That way, the design can be refined to help the target audience meet their needs and have potential leads on solutions that will allow it.

Source: Christina @ wocintechchat.com on Unsplash

For optimal results and compelling interviews, interviewers gain the most out of this qualitative method by being equipped with superb listening skills, which allow them to read the interviewee’s cues and ask timely, pertinent questions. Conducted in such a manner, research stands to gain great insight that will assist in driving future design and development decisions to suit user satisfaction better.

Studying Diaries

One of the most important things in any field of research that involves users is to understand, on a broader scale, their attitudes, experiences, and behaviors toward situations in their daily lives. A potent tool that UX researchers can leverage for this purpose is ESM , or experience sampling method (sometimes known as diary studies). Those participating in an ESM study are tasked with keeping a journal of thoughts and/or feelings they have throughout their day. The results yield insights into daily activities, habits, considerations, etc. that more traditional research methods may not expose.

Whereas a user in an interview can relay a lot of information about how they interact with a product at one point in time, keeping a diary allows research to measure the experiences of long-term product interaction. Many issues surface over repeated exposures or uses that may not be at all evident from a single interaction. The data is then used as a comparative variable against other types of qualitative studies, including focus groups and user interviews.

A significant advantage of such studies is that they are immersive, so researchers can get a deeper sense of user-to-product interaction. Lab-based experiments, as well as many other types of research methods, will simply not be able to yield information about these long-term behaviors. Additionally, diary studies help to contextualize users’ motivations and drivers of users.

Source: Grianghraf on Unsplash

ESM is not only valuable in qualitative terms, such as the gathering of descriptions or comments during a user’s interaction with a product but it can also provide quantitative information, like how often a user interacts with the product and when they do so. This allows for a broader scope of long-term user behaviors, as well as particular repeat tendencies during the usage of a product.

Another benefit of a long-term evaluation is the ability of researchers to note how a user’s behavior changes when interacting with the product over time. This also yields valuable insights about what types of long-term changes might be needed to improve the design process.

Rather than relying on lab-based experimentation, which could yield artificialized results, or just on a handful of interview questions, diary studies allow real-world observation of user behaviors, which are critical for UX researchers to know.

In our collaboration with Slack , we conducted comprehensive UX research, including ethnographic studies, to deeply understand user behaviors and needs. Through UX research, we brought together three very different audiences.

By observing how users interact with Slack in their real environments, we gathered valuable insights into unmet needs and existing challenges. This information was crucial in refining Slack's design, ensuring it effectively addressed user pain points. The research emphasized understanding user motivations, which informed decisions throughout the design process, resulting in a more user-centered product.

Slack Demo by Clay

Ethnography

Studies in ethnography are one of the user experience research methods that include the observation and comprehension of beliefs, behaviors, and attitudes, with a particular focus on people’s interaction with technology, products, and services in seeking solutions to common problems. While this is no simple feat, it is paramount to UX research.

The key to ethnographic studies is to obtain insights into the real-life experiences of people, contextualized by the environments they occur in, as it relate to the product that the study is concerned with. The collected data is then used to optimize the decisions made during the design process. The real key to ethnography is to study motivations, namely, what needs are not being met that the users are trying to satisfy with a particular product. The collected information is then utilized to isolate existing problems, which is a key piece of knowledge on how to address them.

Before an ethnographic study starts, it must be parameterized with finely defined objectives to ensure optimal results, including the compilation of specific research questions relating to the user’s experience, as well as the demographic and geographical setting of the study. Other steps in the preparation also include appropriating a sampling plan, setting up a recruitment process, conducting interviews, facilitating visits, and effectively analyzing qualitative measures.

Source: Christopher Burns on Unsplash

Contemporary ethnographic studies also leverage digital tools like mobile apps and wearables alongside traditional interviews and surveys to gain critical insights into the behaviors of users. Technology makes it easier to collect a far greater sample of accurate and detailed data during the studies, which is far more reliable than counting on the user to self-report the findings retroactively. Combining modern methods with traditional ones allows access to important insights for UX researchers, leading to product innovation and higher user satisfaction levels.

Focus Groups

Perhaps the most commonly recognized user research method is the use of focus groups, an approach that consists of gathering a group of users in a space (physical or virtual) and engaging them to freely discuss a particular topic or a set of issues. These focus groups tend to be of a particular grouping, such as people with similar needs, industry roles, or backgrounds. As the focus group discusses the matter at hand, a facilitator observes and promotes further discussion by asking questions pertaining to the topic at hand and then encouraging additional discussion.

Businesses heavily leverage focus group research when they are seeking to figure out user perceptions, preferences, motivations, and behaviors as they relate to the business’s service or product. In observing interactions between people, a researcher can better understand all of those motivators. The observable factors include facial expressions, body language, and other nonverbal cues which would not be readily observable through surveys or interviews.

For the successful utility of focus groups, the researcher facilitating the focus group must keep the participants’ discussions focused on the topic and ensure that all of the participants have had an opportunity to voice their opinions. The ideal environment for such an exchange is structured but relaxed, allowing participants to not feel influenced or pressured into sharing their thoughts on the focused topic. It is also immensely helpful to have the focus group be facilitated by an experienced moderator.

The data collected from the focus group will then need to be analyzed. However, this should not occur until after the session has been completed, as it could disrupt the potential for certain participants’ insights to be factored into the analysis. The facilitator will need to take careful notes during the focus group session so they can later be analyzed to draw meaningful results.

Source: Andrew Moca on Unsplash

Focus groups are a popular method of UX research because they allow for the collection of many qualitative insights that other methods do not offer. When participants are in an open environment where their thoughts and opinions are welcome, they are more apt to share valuable information to help UX researchers understand their product or service’s users better.

Quantitative UX Research Methods

While qualitative data offers a lot of intangibles, quantitative UX research methods are necessary to put hard numbers on various research points, allowing for a more thorough analysis of user preferences and behavior trends. Quantitative research entails the collection of data sourced from usage logs, surveys, questionnaires, usability tests, and various other means over a lengthy period. This data is then sorted and analyzed to yield ways to optimize product design.

Questionnaires and Surveys

In terms of quantitative data collection, surveys and questionnaires are among some of the most popular methods because they offer a structured manner of compiling data for comparison and analysis. Questionnaires and surveys are a relatively simple way of getting input from various respondents about various topics at considerably minimal expense.

The questions asked through surveys and questionnaires should be comprised of easy-to-understand questions with easily derived points of data. The questions should yield a positive experience for responders and be able to provide valuable results about patterns and trends quickly from the data collected.

An important aspect of surveys and questionnaires is pretesting, or the process of asking the questions that will be in the final survey earlier in the process. This preplanning process assures that the questions asked fully reflect the user's experiences and feelings. Ensuring that any potentially unfamiliar terms are clearly explained to the respondents is also crucial.

Source: Scott Graham on Unsplash

It is also important to consider formatting and question length to minimize omissions or errors in participant reporting. For instance, if a survey takes over 20 minutes, many participants grow weary of continuing and become more disengaged, which in turn hinders the integrity and authenticity of results. In terms of formatting, paper-based surveys may turn out to be too expensive, while web-based ones are more economically sound.

Usability Testing

Since the improvement and optimization of the user experience are at the heart of UX research, methods that will most readily achieve this goal are preferable. To that end, one of the most common methods used in UX research is usability testing, which aids in determining areas of improvement through product interactions by users in real-life usability sessions. During the sessions, usability researchers observe participant interaction with the product. They take detailed notes and ask follow-up questions relating to what issues the users believed to have encountered with the product. The feedback provided is then used during potential changes, enhancements, or improvements made to the products.

Among the important aspects that can be uncovered by usability testing are the discovery of unintuitive functions, unclear labels, confusing instructions, navigation issues, problematic performance, and a multitude of others. Usability testing is therefore crucial because observing customers in their natural environment interact with a product can identify many usability uses early in the development process, allowing any design and adjustment changes to take place before the product is distributed more broadly.

However, usability testing is not just about observing users' behavior. Upon or after the users’ interaction with the product, questions related to the usage of the product should be used to gain additional insights into what elements users found confusing or challenging to use and why. This can reveal how a variety of users, such as older versus younger or those with different forms of education, could encounter different intuitive issues with the product. Once design teams understand the issues encountered by these different groups, they can apply solutions specifically tailored to those members of a target audience. This assures that the product receives more user engagement and increased satisfaction.

Source: Jason Coudriet on Unsplash

Surveys and interviews can provide good information, but much of what they supply could be limited, while a study of users with hands-on experience is even more valuable. Beyond that, the usability testing data can be tracked and measured in heatmaps, which illuminate various important metrics such as how long a user took to complete a task with the product and how successful they were.

Therefore, the true value of usability research is that it permits an expedient identification of a product’s shortcomings or problems early in the development process, which gives designers time to make the necessary adjustments, resulting in a final product that is optimized from its pre-user testing models.

A/B Testing Method

A/B testing is built around the idea of comparative research. In other words, with this approach, users are provided with two versions of a particular product, use them both, and compare which had a more successful usability outcome. This allows developers to see which design elements have to be improved upon and which are more effective.

By comparing two versions, A/B testing informs developers with insights into how effective some design choices are against others. If users are, for instance, comparing web page layouts, the checkout process, or various sign-up forms, user interactions with multiple versions can show which were easier for user needs and more readily met their expectations.

The tests conducted here must have a clearly defined objective, as it will be the only way to clearly measure implemented changes. This is also important because to collect meaningful data based on user behaviors during product interaction, valid measurements and usage parameters should be in place. When results are interpreted, both quantitative and qualitative feedback from users should be considered based on the product or aspect of a product undergoing the test.

Source: Wikipedia

The insight offered from comparing how users interact with two versions of a product is invaluable because it allows developers to sift out the features that work best for the final product’s development. Driven by a better understanding of user experience, future iteration of the product can be improved, leading to a more satisfactory final result.

Behavior Data Analysis

The most effective aspect of UX research is its ability to dive into the user experience and collect important insights about it through the data collected. It allows researchers to better understand users’ needs, behaviors, motivations, and preferences with products and services. Once the user-product interaction data is analyzed, patterns and trends emerge, allowing researchers to understand which features are easier to understand, which navigation can be refined, how much time a user spends on a particular aspect of utilizing the product, and other actionable insights that drive a more optimized design and development process for the product.

However, data collection alone is of little use unless it can be visualized in a meaningful way and queried for particularly interesting aspects. For digital products, this can be done through analytics tools like Google Analytics or via A/B testing. After the data is collected and visually rendered , it needs to be used to detect trends of behavior patterns. Let’s consider the example of a website with a page or feature with low engagement. Through UX research, it might be noted that this page will be reached when users navigate to it after a particular action, but the navigational paths to reach it are not easily available or are seldom used.

A deeper dive into the usage trends collected through an extended usage period can illuminate how a product or service is used in the daily lives of those interacting with it. UX researchers are able to collect valuable insights into user behaviors, which will then increase their knowledge about which parts of the process need improvements. Traditional methods of observation do not yield the types of results that researchers need to dive deeply enough into the product, but they are certainly not without merit. The ultimate goal of UX research is to detect problematic features or aspects and then optimize them, increasing the satisfaction of user experiences.

UX Research Best Practices

Here are some best practices for conducting effective UX research:

By following these best practices, companies can conduct effective UX research that leads to the creation of user-centered products and services that drive business success.

UX Research Potential Challenges

The right participants might be hard to reach. Every product has a certain target audience base, but collecting participants who reflect it accurately can prove challenging. Without the right participants, the feedback received on preferences and behaviors is unlikely to be as impactful.

Miscommunication. When team members or participants miscommunicate, errors are introduced into the research, resulting in nominally helpful or faulty results, along with errors in methodology.

Research is time-consuming. Due to the varying aspects involved in the research process, UX research can take a long period. This can be tough in terms of the long-term securing of all adequate tools and resources to keep it moving forward.

Resources are limited. Many companies wish they could devote a lot more resources to full-fledged UX research methods, but most are constrained by resource limitations that include necessary equipment for trials, staff availability and experience, financial expenses, and the time that they have to perform it.

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Final Thoughts

To ensure a successful product's optimal development, companies must conduct UX research during the design process. The more thorough the UX research ahead of development, the less likely that mistakes that incur additional expenses are to hinder the success of the business and the product after its release. By leveraging the right research methodology and utilizing the right tools, businesses can compile vital information about user preferences and behaviors during product interaction. This drives a more optimal design of the product and its features.

Of course, UX research is not without its challenges, so being aware of the potential expenses, length, and shortcomings of various methods is imperative ahead of the research project. Once a business can lay out a solid plan and begin to strategically execute it, the benefits of an optimal UX research strategy cannot be overstated.

Clay is a UI/UX design & branding agency in San Francisco. We team up with startups and leading brands to create transformative digital experience. Clients: Facebook, Slack, Google, Amazon, Credit Karma, Zenefits, etc.

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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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UX Research Methods and Techniques

Explore 16 of the most common quantitative and qualitative methods for making informed decisions and generating actionable human insights

Introduction to UX Research Methods

What are ux research methods.

UX research methods are the family of experimental protocols design teams use to study users and test prototypes. They include everything from simple interviews to specialized scorecards, and can be either moderated (ex. interviews) or unmoderated (ex. surveys).

While conducting UX research should generally be left to experienced designers, every member of a Design Thinking team can benefit from a deeper appreciation of the established techniques and rich insights they provide.

What are the types of UX Research methods?

For the sake of simplicity, this guide categorizes common UX research methods into three types based on the data they commonly provide: Quantitative, Qualitative, or Mixed.

Quantitative UX Research Methods Best for benchmarking, prioritization and forecasting

Qualitative UX Research Methods Best for modelling user experiences and inspiring ideas

Mixed UX Research Methods Can be used to deliver both quantitative and qualitative data

The UX Research Methods Matrix

X-dimension: situation vs solution.

The X-dimension separates methods based on what they are typically used to study: Either the situation as a whole (like a literature review or diary study), or the solution being created (like concept testing or an intercept survey). UX research methods are leveraged throughout the complete project cycle — they don’t end when the interviews are over.

Y-Dimension: Qualitative vs Quantitative

The Y-dimension separates methods based on the type of data they typically output: Either more qualitative (like focus groups or concept testing), or more quantitative (like user surveys or A/B testing). Relying on only one type of data can be dangerous: Robust research projects should include a mix of both, as they provide different perspectives on the experience.

Which UX Research Methods should I use?

Typically, UX research methods are stacked together to create an overall UX research plan . That means that the selection of your methods is based on what stage of the plan you are in, and what questions you need to answer. Keep the following factors in mind as you browse the guide:

Three factors to consider when selecting a research method

• Questions: What do we need to find out specifically?
• Resources: How much time/talent/budget do we have?
• Risk tolerance: What are the risks of incorrect assumptions?

If it doesn’t agree with experiment, it’s wrong.

Qualitative UX Research Methods

Qualitative UX Research Methods are powerful sources of inspiration. They bring the voice of the customer directly into the design process, and answer critical questions about the goals and behaviors that solutions can support.

UX research methods in this section:

• User interviews
• Focus groups
• Diary studies
• Literature review
• Participatory design
• Remote walkthrough

User Interviews

User Interviews are the bread and butter of qualitative UX research methods. When designing user-centered solutions, there is no substitute for speaking with real users. While user interviews can take many forms and can integrate multiple methods (such as card sorting and concept testing), the quality of any interview is determined by the quality of its questions.

When planning user interviews, extreme care must be taken to develop questions that are most likely to make interviewees comfortable and actively engaged. If you have ever conducted user interviews before, you will appreciate how difficult this can be in formal settings.

User interviews help to answer

• Who are our primary and secondary personas?
• What do they think and do? Say and feel?
• What are their major pains and gains?
• Who else should we be talking to?

Focus Groups

Focus groups are like user interviews conducted with a group of 5-10 people at once. While they can help expedite the research process , they require significant planning and expert moderation to conduct effectively. Because of this, focus groups are typically conducted by research firms experienced at building group discussion guides that balance personalities and ensure all participants are able to share their feelings openly and evenly.

Focus groups help to answer

• What do teams think about a topic/solution?
• What information gaps exist in the field?
• Which disciplines should we be talking to?
• Does our messaging spark controversy? Conversation?

Diary Studies

Diary studies are an ethnographic UX research method that provide rich qualitative insights. The basic premise of a diary study is to ask potential users to record their experiences in a diary, which is then collected by researchers upon completion.

Diary studies can be recorded as guided journal entries or photo essays, and typically aim to describe a “ day in the life ” of a particular person. Diary studies add a level of realism that can’t be achieved in controlled settings, and are a great way to gain the type of detailed insights that inspire genuine innovations. Note that due to their revealing nature, protecting user privacy is especially important to consider with this method.

Diary studies help to answer

• What does a typical day look like?
• Who do our users rely on and when?
• When/where do our users engage with us?
• What other factors influence the experience?

Literature Review

Also called secondary or desk research, Literature Reviews are a method for exploring available information to gain context about a specific domain. While the rigor required varies with every solution, every design project is likely to benefit from at least a cursory review of existing research. When conducting literature reviews, it is critical to consider the credibility and bias of the source. Government statistics and peer-reviewed publications are typically the most robust sources, with surveys, articles and other sources requiring additional caution.

Literature reviews help to answer

• What cultural trends are influencing our users?
• How has our demographic evolved over time?
• What does science say about the unmet need?
• How are other related solutions experienced?
• What else do we know about our users?

Participatory Design

Participatory design is when teams integrate one or more users directly into their design process. This can be particularly helpful when designing enterprise solutions for specific roles, where deep domain knowledge is needed to appreciate the complexities of required tasks. It also helps to create external “champions” of the solution, who will then help train users and improve adoption.

While the benefit of having instant access to real user feedback can help remove bias and align teams, it is not without risks. The power of user personas is that they represent the collective goals and behaviors of target groups. Relying on n=1 comes with risks.

Participatory design helps to answer

• What would the user do/think?
• What challenges a decision cause?
• Which feature is most important?
• How do these experiences compare?

Remote Walkthrough

A remote walkthrough, also called a Touchstone Tour or simply “shadowing”, puts users in the driver seat as they walk design teams through their environment. For example, if you were designing a new video editing application, you may recruit current video editors to walk you through their daily tasks within the software. Thanks to modern video conferencing tools like Slack or Zoom, it’s easy to conduct and record remote walkthroughs alongside other ux research methods.

Remote walkthroughs help to answer

• What tasks are required to complete their goals?
• How do users complete these tasks?
• What UX challenges do they face along the way?
• Do they use any shortcuts? Customizations?
• How comfortable are users in their environment?

Quantitative UX Research Methods

Today, digital “desire lines” are everywhere — but only if you know where to look. Whether you are improving an app used by millions, or building a service for select specialists, being able to parse big data into actionable insights is a mandatory skill for all UX researchers.

• Behavioral analytics
• User surveys
• Intercept surveys
• Click tracking
• Eye tracking
• A/B testing

Behavioral Analytics

Behavioral analytics help model how users are engaging with an existing system or solution. The process of determining which metrics are the best proxy for the experience, and what the current data says about the solution, is where this UX research method shines.

Typically, the analysis is completed by a core research team and shared with the broader cross functional team during design thinking workshops to inform and inspire ideas. Common behavioral metrics include bounce rate, conversion rate, time to completion, time on task, or other digital/physical desire lines.

Behavioral analytics help to answer

• Where are our users coming from?
• Are they finding what they want?
• How long are they spending with us?
• What do they search for most?
• How often do they engage with us?

User Surveys

Surveys are an established research method adopted by myriad disciplines to collect hard data from groups of people. Data are then analyzed by statistical methods to generate “significant” insights that are unlikely to be due to chance. The power to discern signal from noise is the product of the size of the survey sample: The more people you ask, the more confident the statistics will be.

Like user interviews, the quality of a user survey relies on recruiting the right people and asking the right questions. But unlike interviews, these questions need to be formatted in a way that can be answered using a sliding scale or multiple choice — at least until natural language processing simplifies the analysis of free-text responses.

User surveys help to answer

• Who are our users?
• What challenges do they face?
• What goals and behaviors do they share?
• Where should we focus our design efforts?
• What do they think about a situation or solution?

Intercept Surveys

Intercept surveys, also called feedback surveys, are a simplified form of user survey deployed in the wild where interactions occur. Intercept surveys are commonly found on websites and in emails, and can be as simple as asking “Was this information helpful?”. In practice, intercept surveys are best when limited to only a single question that is easy to understand and effortless to answer.

Intercept surveys help to answer

• What are the biggest challenges users face?
• Where does the experience go wrong?
• Why are users dropping off at this point?
• How is our current solution being received?

Click Tracking

Click Tracking is a specialized ux research method that lets designers observe and analyze everywhere users click or tap when visiting a website. While digital marketers have been using scroll depth and CTA conversion rates for years, modern click-tracking tools like HotJar can now passively record real user visits and generate cumulative heat maps for your pages. These heat maps show where users are (and aren’t) clicking. In fact, HotJar will automatically generate three different layers of heat maps to capture all clicks, moves and scrolls. Together, these session-tracking maps help designers present findings to stakeholders and improve on-page conversions.

Click tracking helps to answer

• Is this button/content getting lost?
• Are users trying to click the wrong thing?
• How are users engaging with our pages?
• What effect did this design update have?

Eye Tracking

Eye tracking is a specialized UX research method that records where your test users are looking — not just where they scroll or click to. Unlike click tracking which can be installed on a live website, eye tracking studies require controlled settings with user opt-in. In the past, eye tracking was prohibitively expensive due to the technology required; however, accurate, webcam-based tools like Real Eye have greatly reduced the barrier to entry.

Today, eye tracking studies are frequently used as a form of unmoderated usability testing that participants can complete on their own time. This dramatically simplifies the logistics and reduces the guesswork in major decision decisions.

Eye tracking helps to answer

• Where do users look first?
• What design is more attractive?
• Is our message being missed?
• Are we confusing our users?

A/B Testing

A/B Testing is a data-driven way to determine which of two (or more) options is the most effective at achieving a specific goal. A/B testing is used in a variety of industries, especially in digital marketing, where optimizing conversion rates is of critical importance. In user experience design , A/B testing can be used to optimize specific aspects of an existing solution, or to determine which of two designs to pursue.

A/B testing helps to answer

• What experience converts best?
• How can we optimize the experience?
• What direction should we pursue?
• What do our users prefer?

Mixed UX Research Methods

Mixed UX Research methods can be used to generate human insights and hard data . They allow for both direct observation of user behaviors, while also generating data that can be subject to statistical analysis.

UX research methods described in this section:

• Heuristic evaluation
• Concept testing
• Tree testing
• Card sorting
• Usability testing

Heuristic Evaluation

Heuristic evaluation is effectively a “pragmatic review” of a user experience by design experts. When applied formally, it uses a point-based scoring system akin to those used to judge athletic performances (like gymnastics or diving). Using predefined criteria and scorecards helps to reduce bias and make scalable decisions in situations where direct usability testing is not possible or necessary.

Of course, the quality of a heuristic evaluation is determined by the experience of the reviewers, and their ability to make unbiased judgements from a user’s point of view. Having a validated set of personas helps improve the output of a heuristic evaluation, and the same interfaces can (and should) be reviewed from the perspective of multiple user personas.

Web users ultimately want to get at data quickly and easily.

Heuristic evaluation helps to answer

• Which design is more user friendly?
• How much have we improved our UX?
• Do we need to redesign this solution?
• What quick wins can we start with?

Concept Testing

Concept testing is exactly that: Testing concepts/prototypes with users to see what they say. Concept testing is common when developing marketing campaigns or other mass-market creative ideas where it is difficult or impossible to predict how people will respond. Concept testing and usability testing are quite similar in this sense; however, concept testing is concerned with deciding which concept (or “big idea”) to pursue, while usability testing is conducted with high-fidelity designs to validate decisions or make minor improvements. Concept testing is commonly integrated with other techniques to streamline the research efforts, and can use card sorting and scorecards to support data-informed decisions.

Concept testing helps to answer

• What tasks are required to complete a user’s goal?

Tree Testing

Tree testing is a specialized UX research method for assessing how intuitive an information architecture is. In its simplest form, tree testing involves watching users interact with a prototype menu within a controlled setting (i.e., no content or visuals included, only the menu itself).

By prompting users to complete specific tasks by clicking through the menu (ex: Where would you go to find X or do Y), researchers can see how their architecture relates to their user’s mental models. This allows teams to optimize critical structural elements early in the design process, avoiding more expensive updates downstream.

Tree testing helps to answer

• Is our information architecture intuitive?
• Are we using the right labels?
• Where are users getting lost?
• Which sitemap is more effective?
• How can we optimize click depth?

Card Sorting

Card sorting is a fundamental UX research method applied throughout the design process . In essence, card sorting is exactly that: Sorting a stack of cue cards that have words on them into piles that make sense to the sorter. For example, you may have a stack of 30 cards with the names of different foods on them.

If you asked someone to sort them into piles according to their most vs. least favorite items, you would learn more about their preferences than if you simply asked them their favorite foods. This basic card sorting theory can be applied to any situation, and augmenting the prompts and piles lets UX researchers answer a variety of questions about the opportunity.

Card sorting helps to answer

• How do our users think about this domain?
• What items belong together? Apart?
• What navigation will work best?
• Where will they look for this content?
• Which experiences should we prioritize?

Usability Testing

Usability testing is used to assess how user friendly a higher-fidelity prototype is with your target users. Usability tests are typically used later in the design process, before shifting to the Implementation step of the design thinking process. Usability testing is conducted similar to other ux research methods such as Tree Testing or Card Sorting, where users are asked to complete specific tasks within a controlled environment. Because usability testing is performed with fully functional prototypes (or the minimum viable product), UX researchers are able to benchmark quantitative metrics such as Time to Completion (TTC) in addition to other qualitative metrics. This makes usability testing a powerful tool for demonstrating business impact and deciding what areas to work on in future updates.

Usability testing helps to answer

• How user friendly is our solution?
• How much time/effort does our solution save?
• What impact can we expect our solution to have?
• What should we focus on in the next release?

So what are UX research methods?

UX Research methods describe the established protocols and best practices designed to help teams understand users and improve real experiences . They range from simple surveys to rich ethnographic field studies, and furnish teams with the actionable insights they need throughout the development process.

While UX research methods were once confined to specialized labs, the rise of cloud-based solutions has dramatically simplified the methodologies and reduced the overhead. Today, teams of all sizes can leverage UX Research methods to improve their solutions

UX Research Methods

• Describes set of research protocols and best practices
• Used to study both users, situations and solutions
• Output quantitative or qualitative data
• Helps develop personas and optimize prototypes
• Support end-to-end Design Thinking process
• Major methods include User Interviews, Usability Testing, Card Sorting, Surveys and Behavioral Analytics

Qualitative vs. Quantitative UX Research—What’s the Difference?

The idea of user-centered products is a focal point across a variety of industries—tech-related or otherwise. Companies are seeing the benefits of placing their users at the forefront of their design decisions. But how do you know what your users’ needs actually are?

The best way to ensure a final product delivers on users’ needs is to conduct lots of user research throughout the design process. There are a variety of ways to conduct user research, but most methods fit into one of two categories: qualitative and quantitative user research.

While one is generally in no way better or more useful than the other, there are key differences that make qualitative data more useful at certain times than others—and vice versa. In this article, we’ll focus on the differences between these research methods as well as when and how to use each type.

We’ve broken down this guide to qualitative versus quantitative user research as follows:

• Quantitative vs. qualitative UX research
• More about quantitative UX research
• More about qualitative UX research
• When to conduct qualitative or quantitative user research
• Examples of qualitative and quantitative research methods
• Making qualitative and quantitative UX research work together
• Key takeaways

Let’s get started!

1. Quantitative vs. qualitative UX research

In short, quantitative user research is research that yields numerical results, while qualitative research results in data that you can’t as easily slot into a calculation. 

The type of research you conduct is very much reliant on what your research objectives are and what kind of data will best help you understand your users’ needs.

Our one, overarching piece of advice: Don’t underestimate either type of research. Both can offer invaluable insights that can guide your design process to incredible outcomes.

2. More about quantitative UX research

Let’s start with the numbers. What is quantitative UX research , what does it look like, and what are the benefits of conducting this type of user research?

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

Quantitative data is almost always numerical and focuses on the statistical, mathematical, and computational analysis of data. As the name suggests, quantitative user research aims to produce results that are quantifiable.

Examples of quantitative data

Quantitative data answers questions of:

In UX design, analytics are a huge source of quantitative data. Page visits, bounce-rates, and conversion rates are all examples of quantitative data that can be gathered using analytics.

User testing sessions can also be great wellsprings for quantitative data. Task completion times, mouse clicks, the number of errors, and success rates are all forms of quantitative data that you can obtain by including some quantitative elements in your user testing.

Benefits of quantitative user research

Due to the objective nature of quantitative user research, the resulting data is less likely to have human bias as it’s harder to lead participants to a certain outcome and has well-defined, strict, and controlled study conditions.

Quantitative data is also often simple to collect, quicker to analyze, and easier to present in the form of pie charts, bar graphs, etc. Furthermore, clients may prefer to see hard statistics and find it easier to link them back to their KPIs as a way to justify investment for future improvements.

3. More about qualitative UX research

This leads us to our second type of research: qualitative user research . What is it exactly, and what are the benefits of incorporating it into your research process?

Qualitative user research is the process of collecting and analyzing non-numerical data in the form of opinions, comments, behaviors, feelings, or motivations. Qualitative data aims to give an in-depth look at human behavioral patterns.

Examples of qualitative data

Qualitative data cannot be as easily counted and funnelled into a calculation as it’s quantitative cousin. Where quantitative research often gives an overarching view, qualitative research takes a deeper dive into the why .

Qualitative research often takes the form of user surveys, interviews, and observations or heuristic analysis and focus groups. Just as with quantitative data, user testing sessions offer tons of opportunities to gather qualitative data.

Benefits of qualitative user research

Qualitative research gives a more in-depth look at your users and will often reveal things that quantitative data can’t. Qualitative testing employs a “think-aloud” approach that allows you to get inside the mind of the person using your product and see how they use it in their own environment and what sort of response they have to it.

Qualitative data helps you make accurate, informed choices for your users instead of guessing about causation. Obtaining this empathetic and emotionally-driven evidence may make it easier for stakeholders to invest in changes to the product.

4. When to conduct qualitative or quantitative user research

While qualitative user research can be conducted at any point in the design process, quantitative user research is best done on a final working product, either at the beginning or end of a design cycle. This is due to a few reasons, which we’ll cover in this section.

The goals of quantitative research are summative and evaluate metrics on an existing product or site. Companies often use quantitative research to evaluate if a redesign of a final product is needed, to track a product’s usability over a period of time, and compare a product with its competitors. It’s also used to calculate ROI (return of investment) in order to understand how efficient a product is at making an appreciable profit.

Conversely, qualitative user research is both formative and summative and is used to inform design decisions at any point in the design cycle, help ensure that you’re on the right track. Qualitative research identifies the main problems in design, pinpoints usability issues, and helps uncover possible solutions for them within the design process.

Furthermore, because quantitative user research usually involves large numbers of users (>30 participants), conducting quantitative usability tests too early or too often in the design process can be costly, whereas the more intimate and smaller qualitative testing (5-8 participants) is often more affordable and easier to justify.

5. Examples of qualitative and quantitative research methods

Here, we’ve listed some examples of qualitative research methods, quantitative research methods, and research methods that fit into both categories.

Qualitative

• User interviews
• Focus groups
• Diary studies
• Shadow sessions

Quantitative

• Funnel analysis
• Mouse or heat maps
• Cohort analysis

Both qualitative and quantitative

• A/B testing
• Card sorting
• Tree testing
• Storyboarding
• Visual affordance usability testing

6. Making qualitative and quantitative UX research work together

As you may have noticed, there are many research methods that render both quantitative and qualitative data. Furthermore, it’s uncommon for designers to run just one form of user research. This is because quantitative and qualitative user research data are best used together in order to obtain a more comprehensive idea of the issues at hand and their possible solutions.

Conducting both quantitative and qualitative research helps you form hypotheses as well as come up with the metrics on how to test it. Using just one type of research often leads you with unanswered questions and vague or false metrics. When used in conjunction, quantitative data will answer your “what, how many, and how much?” questions while qualitative data gives you the answers to “why?”

7. Key takeaways

Quantitative and qualitative user research are both necessary in the process of designing products and experiences that truly meet users’ actual needs and goals.

Quantitative research are larger tests that give a summative evaluation of the overall usability of an existing product and are always reported in numerical form through metrics like satisfaction ratings, task times, number of clicks, and bounce or conversion rates.

Qualitative user research are smaller sessions that give non-numerical, formative information as to what the main issues of usability issues of a product are and are reported as quotes, emotions, or observations.

While quantitative and qualitative user research methods have different goals, they are complementary to each other and give designers a fuller, more comprehensive idea of the success of their product design.

If you’d like to learn more about UX research, check out these articles:

• What is user research and what’s its purpose?
• How to conduct inclusive user research
• Top 5 UX research interview questions to be ready for
• 5 Mistakes to avoid with your UX research portfolio

• Customer Stories
• Designer Stories

UX Research 101: A Complete Guide to User-Centered Design

Turn your design team into a high-performance workforce that puts design at the forefront using a powerful suite of tools.

Top 8 UX Research Methods & When to Use Them

When embarking on the development of a new digital product, it is paramount to keep the user experience (UX) at the top of the mind. However, there needs to be extensive research on what our target audience wants and how their thought process works when it comes to using technology. The idea behind user research is to examine how a system, service, or product is utilized by its users to learn more about their needs, behaviors, and goals. The research is helpful in designing and developing the product to improve its usability and user satisfaction. User research methods let you learn more about users' needs and motivations. Regardless of what type of project you are designing, user research will help make sure you have all the necessary components to facilitate your audience. There are various user research techniques being utilized to pinpoint problems and opportunities and enhance user experience.

Choosing a UX Research Method Based on Your Project Phase

When choosing a UX research method for your project, it's crucial to consider the specific phase you're in. As you move into the different stages, different methods are adopted to effectively optimize the user interface. It is crucial to align your research methods with the project phase, only then can you gather relevant data and make informed decisions.

At the Beginning of the Process

During the Initial phase of any UX research, the focus is on understanding end users, their preferences, and their needs. The research problem is stated and the objectives are set, involving the identification of knowledge gaps and formulating hypotheses to guide the research process. Different methods are utilized at this stage that include conducting interviews to understand user mindset, needs, and challenges.

“When conducted wisely, user interviews can provide a good amount of qualitative data by probing users with the ‘Why’ question.”

Conducting such interviews allow you to gather information through conversations with your users. These direct interactions can help analyze users’ inner behavior, ultimately getting to the problem and its solution. Carrying out surveys and questionnaires helps gather statistical data and feedback. Also, analyzing the user experience of competitors' products can aid in identifying areas for improvement. Giving a contextual perspective also plays a critical role in inspiring design products. Contextual inquiry unravels hidden insights about customers through interpretation and collaboration. In this method users and their behaviors are directly observed. Researchers tend to visit participants in their natural environment, be it home, or workplace, and communicate with them. This is one of the most effective methods to inspire design products.

Once the Design Stage Begins

“People ignore design that ignores people.”

The UX design process is a multi-stage, end-to-end methodology that incorporates design thinking to develop UX projects. User-centered design is all about prioritizing the user. A website, app, or piece of software that doesn't take the needs of the user into account is eventually bound to fail. The whole process involves an iterative method used by UX teams to finish projects. Although the UX process varies depending on the organization and the product, most businesses start following the same design method: 1. Designing Prototype: The design team then begins creating high-fidelity prototypes that resemble the finished product in both appearance and functionality. Designers try to utilize top designer tools to create interactive prototypes if the business has a design system in place. 2. Usability Testing: Usability testing involves observing users as they perform tasks that are given to them by the researcher. They observe the user’s behavior while completing that particular task. This method helps assess the effectiveness of design solutions and gather feedback for any improvements. 3. Diary Studies: User logs (diaries) involve participants recording their experiences, thoughts, and behaviors over a specific period of time. This kind of user research method allows researchers to gain a deeper understanding of user contextual insights and uncover patterns that may not be established in a single-time framework.

After the Release

The work of a user designer is never really completed. Once a product has been created and released, different UX research methods need to be applied to assess its performance and gather feedback for future considerations. 1. A/B Testing These kinds of research techniques involve comparing two or more versions of a design or app to understand which one performs better. This type of testing provides companies to make careful changes and gain insights regarding the user experience. You can use different design tools to increase your core skills in product design. 2. Quantitative Surveys These surveys are similar to those conducted during the initial phase. They are also carried out after the release to collect data on user satisfaction and overall product performance. The questions are about asking respondents to select from a predetermined list of answers (such as ratings, scales, or yes/no answers). These types of questions can provide valuable insights about the product experience. 3. UX Metrics Analysis UX metrics are quantitative datasets that can be analyzed to get insights that aid decision-making. Such metrics analysis determines if your product strategy is performing or not. It involves analyzing data collected from user interactions with a digital product. The analysis is done based on behavioral and attitudinal metrics .

Qualitative vs. Quantitative Research Methods

UX research methods fall under two categories, qualitative and quantitative. Both have different purposes in research design. The main difference between these methods is the type of data collection and its nature. A qualitative user research method is focused on collecting and analyzing subjective information that helps designers in making formative decisions. Qualitative user research data is typically presented in the form of quotes, stories, observations, or narrative descriptions to determine how usable a product is. The quantitative user research method involves gaining information from a larger sample size and providing statistical analysis. This type of UX research involves the collection and analysis of numerical data to measure user behaviors and preferences. Quantitative methods include surveys, co-relation research, and experimental research. It is also important to understand that both these UX research methods are not mutually exclusive. On many occasions, these research techniques can provide a more comprehensive understanding of the user experience.

Qualitative UX Research Methods

Qualitative studies are focused on analyzing user behaviors, attitudes, and motivations in-depth. Qualitative data is considered to be far more challenging to analyze and interpret. These UX research methods are usually presented in the form of structured or semistructured findings. Although qualitative user research can take many different forms, each technique has the potential to reveal priceless information about a product's usability. Qualitative research is highly flexible and less likely to get affected even if your study is not perfect. Secondly, participants are considered to be the key. A good profiled participants will always yield great results

“People are the key, If you are not talking high-quality participants, that's kind of a non-starter. If you are not talking to the right people, it will really get hard to make the right decision.”

Let's discuss the types of Qualitative UX research methods

1. Competitive Analysis

Such type of UX research techniques enables you to gain strategic insights into the features, functionality, processes, and overall user experience of the competitors' design solutions for digital products. This analysis involves studying and comparing the user experience of competing products or services. When you identify your main competitors (both existing and potential), opportunities to fill, and threats in the current marketplace, competitive analysis becomes a strategic step.

2. Card Sorting

Card sorting is a type of qualitative UX research technique in which the designer creates a set of cards, each containing a piece of content or an idea. Users are then asked to sort the cards into various categories like open sorting, closed sorting, and more. This UX research method helps to develop an information architecture that adheres to users' expectations by revealing the organizational structure of the target audience's domain knowledge. It can also be used to inform the design of navigation menus, site maps, and content structures. Traditionally this method was used in the preliminary stages of the design process for the assessment of information architecture.

3. Ethnography

This user research technique is qualitative in nature. The researchers in this UX research try to immerse themselves in the culture and behavior of the environment they are examining. Observing users in their natural environments helps in the contextual understanding of their needs. This method also helps to uncover group behaviors, culture, conventions, and social interactions that influence their experiences with a product or service. Direct observation, diary studies, video recordings, photography, and artifact analysis are all examples of ethnographic approaches. Observations can be made anywhere, including the user's home, place of employment, or when they are out and about with friends and family. Depending on the type of research being done, study lengths can change. They can be as short as a few hours of observation or as long as several months' worth of research.

4. Participatory Design

These research techniques include participation with all stakeholders (such as clients, staff members, partners, citizens, and consumers) in order to better understand, cater to, and occasionally anticipate their requirements. A wide range of professions, including architecture, graphic design, software, and product design, use participatory design activities. Through collaborative activities and workshops, users contribute their ideas, feedback, and preferences, which can lead to more user-centered design solutions .

Quantitative UX Research Methods

Clients adore hard facts. Although gathering statistical data to support a strategic research agenda with management is far from the only reason to conduct quantitative UX research, it frequently serves as an inspiration for significant research initiatives. Such research methods are mostly used when attempting to assess the usability of a working product. It can also be highly useful for finding the solutions to large, general questions using statistical analysis to support or refute your theory. Quantitative UX research methods focus on collecting numerical data to measure and quantify user behaviors, preferences, and patterns. Quantitative approaches can be categorized, similar to qualitative research, and the best quantitative approach depends on the nature of the problem you are addressing, the sort of data you need, and the study protocols that will be used. Below are quantitative UX research methods mostly used today!

1. Eye-Tracking Method

A type of quantitative research that detects where and how long people look. It enables researchers to observe people from their point of view and gain knowledge on visual attention. It accomplishes this by casting a reflection in the subject's eyes using a specific light. The position and movement of the eyes are inferred from these reflections by the tracker's cameras. The participant's viewing behavior is visualized using that data after it is projected into the user interface. Since the eye-tracking technology records the route without obstructing users' normal behavior, it can be incredibly helpful for usability evaluations. You can also develop a deep understanding of how users interact with your product design with the help of eye tracking based UX testing tool . This knowledge can be helpful to you at different stages of the design process and, in many circumstances, can improve the information you get from other test methods

2. SUS Scores (System Usability Scale)

This tool is just like a standardized questionnaire used to measure how satisfied a user is with their digital experience. The grading gives your project a useful quantitative measure of experience and is frequently used in conjunction with results for effectiveness and efficiency. The key to using SUS successfully is to determine which projects might benefit from including this measure. SUS can be easily incorporated into any research or test effort, but accumulating data only for the purpose of it is pointless. SUS is a great way to benchmark and improve, so iterative projects greatly benefit by evaluating how well a digital product is evolving through an Agile process, for example. According to studies, a SUS score above 68 would be deemed above average and anything below 68 is below average. However, the simplest way to understand your results includes “normalizing” the scores to produce a percentile ranking.

3. Tree Testing

“Tree testing is a highly valuable exercise to get a clear view of what real users expect as topics in the navigation of a website and how these topics are clustered from primary to secondary. Tree testing should be the starting point for designing better digital applications.”

These types of UX research methods enable you to assess the organization and discoverability of topics on a website or mobile application. It is considered a crucial stage in your research strategy. Participants in a tree test are shown a text-only hierarchy of the website and asked to perform a series of tasks. Ultimately, the question of "Can users find what they are looking for?" must be addressed. The tool is perfect for gaining feedback before you design your ideas.

4. User Analytics

User analytics or analytics data, also known as user behavior analytics, is a post-launch user research method of continuous, quantitative data collection and evaluation. Teams utilize analytics tools to gather information about how people interact with their website, app, or product. After that, they examine this information to learn more about user mood and engagement. This research method offers many benefits. Firstly, it significantly reduces lead time as data is readily available, allowing for quick analysis and insights. Secondly, the large sample sizes in analytics enable statistically significant observations, providing a more accurate understanding of user behavior. Also, Analytics capture people's natural conduct, reflecting their real-world behavior rather than behavior influenced by a research context or test environment.

What Results Can You Expect from Your UX Research?

A UX researcher's job is to identify user demands, behaviors, and motivations in order to improve the usability and appeal of websites, services, and products. The results of carrying out effective user research would be to make the overall design process smoother and more productive. We have to keep in mind that addressing user needs is everything. As Vice President of the Nielsen Norman Group Hoa Loranger puts it:

“UX research without users is not UX.”

So, Let's shed light on some of the potential results you can expect

Deeply understanding user needs

Practicing different user research methods can reveal insightful information about user preferences, behaviors, and motives. The design process can be guided by this deeper understanding, which will result in more user-centered goods and services.

Design solution validation

Design decisions can be validated via UX research methods, also providing supporting data. Results of user testing and user feedback can aid in boosting confidence in the efficiency of design ideas. Researchers gain expertise as they conduct UX research, gather data, identify issues, and create fresh solutions.

Decision-Making Supported by Data:

Quantitative UX research techniques offer statistical information that can aid in the decision-making process. Prioritizing design changes based on quantifiable impact and user preferences, for instance, can be done with the use of A/B testing and analytics research.

Usability Issues Identification

Usability testing and other evaluative user research techniques can be used to identify usability problems and pain spots in a design. Taking care of these problems can increase user engagement.

Key Takeaways

If you are looking to improve your design skills or excel in becoming an effective UX researcher, strive for continuous learning. Prioritizing staying updated on the latest trends, tools, and methodologies in UX research and design is essential. Qualitative approaches delve into user behaviors and attitudes, while quantitative techniques provide numerical data on preferences and behavior. Start a UX research course with Uxcel and earn a professional UX design certification in no time.

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11 Top UX Research Methods and the Perfect Times to Use Them

Published: July 23, 2024

One thing that continues to surprise me in the world of digital products and website design is how confident businesses are that they know their target audience. Product and design decisions are made on assumptions or personal preferences, and the results often backfire.

This was the case with an online cosmetics company I worked with that needed to improve their overall visibility but also wanted to refresh the layout and functionality of their site’s eCommerce functionality. “Our customers won’t like that,” I heard several times, or “our target demographic will love this.”

There’s a lot to figure out in the UX design process, and the overall objective is to improve conversion and retention rates (i.e., revenue). However, revenue-driving digital experiences start and end with the customer, and that’s where user experience (UX) research becomes a critical component of the playbook. UX research design takes the guesswork out of design decisions and puts customer-sourced data and information at the core of your processes.

Table of Contents

What is UX research?

The benefits of ux design research methods, 11 ux research methods and when to use them, ux research example, choosing the right ux research for your project.

UX research is the process of studying user behavior and preferences to inform design decisions for digital products like software, websites, apps, and systems. No matter which research method you use, the goal is to come away with actionable insights so that your design meets user needs and provides a positive experience all around.

Part of UX research can include identifying pain points or specific preferences or understanding user motivations and behavior. When it comes to choosing the right UX research method for your particular product, it’s important to know that available methods vary by their purpose and outcomes. Each method can be categorized across distinct dimensions across four main categories.

UX Survey and Data Collection Methods

Quantitative UX research : collects numbers and data for statistical analysis. It’s useful for making data-driven decisions, particularly between a set of distinct choices within your design (e.g., color usage). Surveys are a good example of quantitative research.

Qualitative UX research: less about standardized data and more about getting insights into individual experience. With qualitative information, you can get more depth and context for your design decisions. An interview with a user would qualify as qualitative research.

UX Research Response Focus

Attitudinal research emphasizes the way users express their wants and experiences. It’s how they believe they interact with interfaces and what they’d like to see. Interviews and focus groups are types of attitudinal research.

Behavioral research involves observing what users actually do when interacting with the product. It’s typically more of a data-based approach, and it can uncover nuggets about behavior that the users may not even be aware of themselves. Heat maps and eye tracking are both examples of behavioral research.

Depending on your chosen research method, you’ll end up with either quantitative or qualitative, and attitudinal or behavioral. Interviews are qualitative and attitudinal, whereas A/B testing is quantitative and behavioral, and so on.

Pro tip: I like to use a mixture of research methods wherever possible because it gives me a much fuller overall picture.

When dealing with quantitative data, for example, I might be more inclined to make assumptions about an outcome. However, a few well-chosen user interviews might provide me with context that I hadn’t considered, and therefore, I’m able to make more fully informed decisions.

Typically, it comes down to the complexity of the design decision, too. A simple decision on a button color? A/B testing tells me everything I need to know. But a more complicated exploration of an entire user journey? That definitely requires a deeper level of research and the use of multiple methodologies.

Check out this UX research kit with templates to help guide your research methods and planning.

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Idea Validation

Sometimes, there can be too many cooks in the kitchen when it comes to UX design. Conducting some research helps to weed out good ideas from bad and provides a clear direction that is backed up by data.

Pro tip: When this happens, I like to get real-life potential users into the app or website and get their feedback. Other people involved in the decision-making are more likely to listen to this type of feedback, and it can challenge your own perception of what works, too.

In this way, you get validation from the people who are going to be using your site, and you can even include survey-style questions throughout the process to get more quantitative data as well.

Improved Usability

People expect digital experiences to be easy to use and navigate. In fact, 73% of users expect a simple and intuitive interface, and they’ll make judgments about a company’s credibility based on that.

But, usability is a tricky one sometimes, and it’s something I see particularly in B2B businesses. When you’re designing a product for someone else, you don’t always have enough context to know if the interface or journey you’re building really works.

Let’s say I’m designing a website layout for an electronics store. I have professional cameras to place somewhere, so I nest it under the Gadgets category. But, professional photographers wouldn’t go to this section to find cameras and they certainly wouldn’t consider their equipment to be gadgets.

It’s a simple example, but the point is that detailed UX research is about learning about the audience and their preferences, a core concept in design thinking.

Choosing the best UX research design method is entirely dependent on the situation and what you hope to find out. Additionally, it’s often better to use a combination of methods to get a more complete picture.

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World Leaders in Research-Based User Experience

Quantitative ux research in practice.

September 2, 2018 2018-09-02

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UX is sometimes perceived as a “soft” science. Often, that’s due to our field’s reliance on qualitative research and observations. To investigate how digital product teams use quantitative research to get “hard” data (or why they don’t) we surveyed 429 UX professionals.

In This Article:

How often teams use quantitative research, which methodologies teams use, success criteria, quant research challenges, your quant to-do list.

We asked respondents to roughly estimate how frequently they, or someone else on their team, perform  quantitative studies .

When interpreting these results, bear in mind that there may be some  sample bias  at play. We recruited our respondents from Twitter and LinkedIn outreach, and offered a chance at a free report or online seminar as an incentive. We also mentioned that the survey was about quant practices. As a result,  our sample consisted of NN/g-fan UX practitioners  who potentially were interested or had heard of quantitative research methods. I’d bet that sample (and probably you, since you’re reading this) likely performs more quant research on average than the wider UX community as a whole.

(Although, since you  are  reading this article, that likely means the results of this survey are probably fairly representative for the kinds of projects  you  work on, even though they may not be representative for all design projects in the world.)

We were somewhat surprised to hear that the majority of our respondents (71%) said they performed quantitative research either “sometimes” or “at least one study per project.” This result makes sense when we look at the methodologies that respondents report using.

We asked respondents to tell us how frequently their teams were using 11 popular UX research methodologies — 7  quantitative  and 4 qualitative. For each methodology, respondents told us if they were using it “often,” “sometimes,” “rarely,” or “never.”

The most frequently used methodologies, as reported by our respondents, were, in order:

• Analytics (Quant)
• Qualitative usability testing (Qual)
• Interviews (Qual)
• Large-sample surveys (Quant)
• Small-sample surveys (Qual)
• A/B or multivariate testing (Quant)
• Card sorting (Quant/Qual)
• Quantitative usability testing (Quant)
• Focus groups (Qual)
• Tree testing (Quant)
• Eyetracking (Qual/Quant)

Predictably, the relatively  lower-cost methodologies  rank near the top (analytics, qualitative usability testing, interviews) while more expensive methodologies are towards the bottom (quantitative usability testing and  eyetracking , which can be both prohibitively costly).

These results give some context to the surprisingly high frequency of quantitative studies in design projects. 74% of respondents who reported using quantitative research at least once per project also reported using analytics “often” (86 out of 117).

Analytics data can  play a significant role in UX design . Unfortunately, in this survey, we don’t have an indication of exactly  how respondents were using analytics in their projects. 

It’s possible that many of the analytics-heavy respondents, who reported using quantitative research at least once per project or sometimes, used that analytics data in a meaningful way to guide their design projects — for example, to help them identify problem areas in the product. 

However, it’s also possible that those simply reporting that their teams were just  collecting  analytics data in every project, not that it had any real significance for their work. This possibility is supported by some of the open text-field comments from our respondents.

“We don’t have funding for more advanced quantitative research methods (beyond click tests, surveys, etc.)” “My company started as an A/B testing and CRO company and hasn't evolved their thinking beyond conversion rates.” “My manager has access to the analytics and measures success on traffic within our products/sites rather than interpreting the numbers to extract meaningful insights.” “They're the only metrics we have access to. We don't collect any usage data, so sales and revenue exclusively drive product decisions.”

User research (not just quantitative, but qualitative too) can help us determine whether our designs work as we want them to, and whether we’re meeting our goals.

We asked respondents in our survey how they know when a design project is successful. In a multiselect, they could choose from 5 options:

• Based on calculated improvements using metrics and quantitative research (like quantitative usability testing, NPS, and analytics)
• Based on observed improvements through qualitative research (like qualitative usability testing and interviews)
• As long as the leadership/executives are happy, the design changes are counted as a success
• We don’t really know

In an ideal world, success would be evaluated by both qualitative and quantitative data — observations and measured results.  That would tell us if we’re hitting our goals and making our users happy, which would make the leadership or stakeholders happy as a natural consequence.

Unfortunately, those aren’t the results we found:  only 24% of respondents checked  both of the options for looking at quant  and  qual research.  While quant and qual data were each prioritized by over 40% our respondents, so were happy executives/stakeholders. Additionally, a disheartening  18% of respondents admitted that they “don’t really know”  whether or not their design changes are actually improvements.

We often hear complaints from UX teams that they  want  to do more quant research, but too many insurmountable obstacles get in the way. To capture this in our survey, we asked respondents to choose their quant research challenges from a multiselect list of nine of the concerns we hear most frequently, plus an “other” write-in field.

• Quantitative research is too expensive
• Quantitative research is too time-consuming
• Difficulty recruiting enough participants for large sample sizes
• Lack of knowledge on the team about how to conduct or analyze quantitative research
• Lack of knowledge on the team about what quantitative research is, when to use it, or what the methodologies are
• Lack of understanding of the value of quantitative research
• Lack of understanding of the value of research in general — not just quantitative research
• Difficulty interpreting or reporting quantitative research findings
• Another group in the organization is responsible for quantitative research, and UX isn’t included
• I’m not sure

Difficulty recruiting large samples  was the most popular response (37%). Some respondents reported struggling to collect large samples because their end users were blocked by gatekeepers. For example, one respondent who works on an enterprise product explained, “We rely on Product Management to decide when we can or cannot contact customers who may not want to offer their employees' time.”

After difficulty recruiting, the rest of the options had fairly similar rates of selection (16–29%). Only 2 respondents out of 429 reported performing at least one quantitative study per project and having no significant concerns. The primary takeaway here seems to be that  almost everyone struggles with quantitative research in some way  — even those who reported doing quantitative research frequently. 

Ignorance as a Roadblock

Notably, lack of knowledge about quant methods and analyzing quant data ranked towards the top of this list.  Quant research can be intimidating to UX professionals, their teams, or their stakeholders,  and ignorance is a substantial roadblock. 

“[Our challenge is,] in particular, the advanced math behind A/B testing” “Lack of data scientists (1 at the moment) and limited quant skills (or training) for qualitative researchers. Can be off-putting […] when there are better people who correct you too ;)” Several respondents working in consultancies or agencies complained that they struggled to “get client buy-in” on quant research.  “Our UX team understands the value of it, and how/when to use it. The product teams in the rest of the organization, however, is a different story...” “Owner does not see the value in quantitative research. Crazy, I know.”

Despite these challenges, there’s some good news in these results:  only 16% of respondents found quant UX research to be too expensive.  Obviously, whether or not something is considered “expensive” depends on three factors: the cost, the cost–benefit ratio, and the available budget. (Even research with a favorable cost–benefit ratio will be too expensive if the cost exceeds the available budget.)

A decade ago, it was the common understanding in the UX field that  quantitative studies were expensive  and reserved for extravagant, well-funded projects in big companies. We’ve always advocated  discount usability instead of deluxe usability  methods, in order to get user research more widely used. 

However, while  cheap methods are still great  and should account for the majority of research on a design project, quantitative methods are less of an unaffordable luxury than they used to be, for three reasons:

• The cost is down,  due to improvements like  remote research  services (e.g., UserZoom) and automated data collection.
• The cost–benefit ratio is more favorable,  because quantitative findings are used as more than just vanity statistics — instead, they’re often used for longitudinal tracking, demonstrating ROI, and triangulation with qualitative findings.
• User-research budgets in general are growing,  as more companies move to higher levels of  UX maturity .

Based on these findings, we have the following recommendations for you to consider on your next project.

• You can probably afford to do some quant research, so plan for it.  Even if that means starting with the cheaper or more lightweight methods like analytics, that’s ok. Getting your team or your client started with quant research is the important thing, and you can work to expand your quant methodologies as you build up expertise.
• As early as possible, consider how you can get the necessary sample size,  since this is the problem holding most teams back and shouldn’t be left to the last moment. If you struggle with getting around gatekeepers who block your access to users, it might take some networking to convince them of the importance of your research. If recruiting is a constant obstacle for your team (and you have the resources), consider dedicating an in-house part-time or full-time recruiter to the job.
• Before even starting the project,  educate yourself and your team on the available quant methods, the appropriate uses for each, and how to interpret findings  and turn them into action items. Don’t let “lack of knowledge” stand in your way.
• Don’t just use the most popular methods , but consider when some of the more specialized methods will be more valuable to answer specific design questions.
• Combine methods . In particular, use a combination of quant and qual studies to inform each other, increasing the effectiveness of both.
• Plan how you will judge the success of your design  at the very beginning , preferably using a combination of quantitative data and qualitative observation. That way you’ll join the elite 24% of UX practitioners that do this right.

To learn about the value of quantitative research, quantitative methodologies, and how to choose between them, check out our full-day seminar,  Measuring UX and ROI .

Related Courses

Measuring ux and roi.

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Statistics for UX

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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.

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

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.

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.

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

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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Aug 15, 2024 • 13 minutes read

Mixed methods research explained: Combine data like a pro

From heatmaps to interviews, here’s how to blend qualitative and quantitative data for holistic user insights.

Ella Webber

Mixed methods research is one of the most popular and powerful UX research approaches—blending numbers with narrative to garner a holistic understanding of your product or research question.

Whether you’re in UX research and design, education, healthcare, or social sciences, mixed methods research can help you find insights and make better decisions.

Read on for a breakdown of what mixed methods are, their strengths and weaknesses, when to use them, and how to analyze the data.

UX research made easy

Explore the power of combining quantitative and qualitative research to discover new insights and test final solutions.

What is mixed methods research and when should you use it?

Mixed methods research involves collecting, analyzing, and integrating both quantitative and qualitative UX research methods within a single study. It is unique to other UX research techniques in that it combines data types, encouraging product teams to use qualitative feedback to explain the story behind quantitative numbers.

• Quantitative data can come from UX surveys , product analytics , usability testing , experiments, or statistical databases and provide broad numerical insights
• Qualitative data is gathered through user interviews , focus groups, or contextual inquiries and offers a deep, contextual understanding of the subject matter

Why use a mixed methods approach?

The power of mixed methods research is simple: it allows you to combine the best parts of both types of data—quantitative research methods, like surveys, give you broad trends, while qualitative methods, such as interviews, dig deep into personal experiences.

Anthony J. Onwuegbuzie and R. Burke Johnson, in Mixed Methods Research: A Research Paradigm Whose Time Has Come , highlight how blending these methods allows researchers to leverage the strengths of both approaches. They identify mixed methods research as one of the “three core research paradigms: qualitative, quantitative, and mixed methods.”

Like any technique, however, mixed methods research has both strengths and weaknesses to consider.

When should you use mixed methods research?

Mixed UX research methods are useful when neither qualitative nor quantitative data alone can fully answer your research question . Evaluative research further helps to assess the effectiveness of your mixed method research findings and ensure they meet user needs.

For example, use mixed methods research when:

• You need to go beyond numbers (generalizability): Quantitative methods, like surveys, provide broad trends and patterns that are relevant to a wider population. For example, a survey might show that most users enjoy a new app feature, but it won’t capture why some users might dislike it.
• The why matters (contextualization): Mixed methods allow you to put numerical findings in context, adding rich detail to your conclusions. For example, if analytics show that users are spending less time on your app (quantitative), interviews can help you understand the reasons behind this behavior, such as frustration with a recent update or a lack of engaging content (qualitative).
• Credibility is important (credibility and triangulation): When both data types converge on the same conclusion, it strengthens your findings. For example, the combined evidence is more credible if survey data indicates that most users prefer a particular software interface and focus groups echo this preference.
• You need to track changes (developmental purposes): Mixed methods are invaluable when one type of data informs the other. For example, initial qualitative research with a small group of beta testers can uncover key issues and user needs, which can then be explored quantitatively with a larger user base to see how widespread these issues are.
• Understand complex issues (complementary insights): Different data types can offer complementary insights. For example, in a study on software usability, quantitative data might show a drop in task completion rates, while qualitative data reveals specific pain points and user frustrations. This combined approach can guide more effective design improvements.

What are the types of mixed methods research design?

The type of mixed methods research design you choose depends on your research goals, the timing of data collection, and each data type. Here are some key factors to consider:

• Your research approach: Are you trying to understand existing findings (explanatory) or dig deeper into a topic (exploratory)?
• Your research questions: Do your questions need big-picture answers (like how many users are happy) and detailed explanations (like why some users are unhappy)?
• Existing data availability: Is there any existing information you can use from previous studies or a research repository (like user demographics)?
• Data you can collect yourself: What kind of in-depth information do you need to gather from users (through interviews, testing, etc.)?

Whether you're a data diver or a narrative novelist, understanding these research methods can make your studies more dynamic and insightful.

📚 A UX research repository is crucial for keeping track of research findings. You need a centralized database to store and manage all your qualitative and quantitative data. This ensures that your research is organized, accessible, and reusable for future studies.

Let’s look at the most common types of mixed methods research design:

Convergent parallel

Convergent parallel design involves collecting qualitative and quantitative data simultaneously but analyzing them separately. The primary goal is to merge the two datasets to provide a complete understanding of the research problem.

For example, let’s say you want to study user satisfaction with a new mobile app. Here’s how you might use the convergent parallel design:

• Qualitative results: Conduct in-depth user interviews with 30 participants to gather detailed insights into their experiences and perceptions of the app. Plus, analyze 200 user reviews from app stores. You might use prompts like, "What features do you find most valuable?" and "Please describe any difficulties you've experienced while using the app."
• Quantitative study: Use analytics data to measure user engagement metrics like session duration and feature usage, then distribute UX surveys to gather quantitative satisfaction scores.

Concurrent embedded design

Embedded design is a mixed methods research approach where qualitative and quantitative data are collected simultaneously, but one type of data is supplementary to the other.

The secondary data provides additional context and can help explain or clarify the primary findings. This approach is particularly beneficial when time or resources are limited, as it allows for a more comprehensive analysis without doubling the workload.

Explanatory sequential design

Explanatory sequential design is a popular mixed methods research approach introduced by John W. Creswell and Vicki L. Plano Clark. This research design involves collecting and analyzing quantitative data first, followed by qualitative data collection and analysis.

According to Creswell, this approach is particularly useful when researchers need to explain relationships found in quantitative data.

The process typically involves two phases:

• Quantitative phase: This involves collecting numerical data through methods like surveys or experiments. The goal here is to identify patterns, trends, or relationships.
• Qualitative phase: Qualitative phase: After analyzing the quantitative data, researchers collect qualitative data with qualitative approaches, like interviews or focus groups, to provide deeper insights. This phase helps explain the ‘why’ or ‘how’ behind the quantitative findings.

Creswell emphasizes that one of the strengths of this design is its simple structure, making it easy for researchers to manage and for audiences to understand the research process and findings.

Exploratory sequential design

Exploratory sequential design begins with qualitative data collection and analysis, followed by quantitative data collection. This immersive approach helps generate rich, detailed data that lays a strong foundation for the subsequent quantitative analysis.

For example, let’s say a researcher wants to understand why people don't meditate regularly. They could start with generative research techniques , like conducting workshops where participants discuss their daily routines and barriers to meditation. These qualitative insights reveal underlying themes and patterns, like time constraints and lack of motivation.

Next, the researcher analyzes these qualitative data to identify key factors impacting wellbeing habits. Based on these insights, they develop a survey to quantitatively measure how widespread these barriers are among a larger population.

So, that’s how you collect data. But how do you analyze it? Unsurprisingly, there are multiple analysis and interpretation methods commonly used in mixed methods research. Let’s look at some.

How to analyze mixed methods research data: 3 Ways to combine qualitative and quantitative data

Combining different types of research data can add credibility to your research findings. Let’s look at how to conduct mixed methods research:

Triangulation protocol

Following a thread, mixed methods matrix.

The triangulation protocol in mixed methods research is a systematic way to use multiple data sources, techniques, or perspectives to get a clear understanding of a research problem. The goal is to capitalize on the strengths of both types of data while minimizing their individual weaknesses.

Let's say you want to conduct a study aiming to evaluate the effectiveness of a new educational program on student performance, and you arrive at the following datasets:

• Quantitative finding: 80% of students improved their math scores after the program
• Qualitative finding: Students reported that interactive activities helped them understand math concepts better

When you merge these findings, the research concludes that the interactive activities (identified qualitatively) are likely a significant factor contributing to the improved scores (quantitatively).

The following a thread method allows researchers to trace a specific theme or concept across both qualitative and quantitative data sets.

Here’s how it works:

• Identify key themes: Begin by identifying key themes or variables that are central to your research questions. These themes will serve as the ‘threads’ you’ll follow through your data.
• Extracting data: Extract relevant data segments related to each theme from qualitative (e.g. interviews, focus groups) and quantitative (e.g. surveys, statistical data) sources. This involves coding qualitative data and identifying relevant quantitative measures.
• Mapping data: Create a map or matrix that links data segments from different sources according to the identified themes. This matrix helps visualize how different data points converge or diverge on the same theme.
• Comparative analysis: Compare the data segments within each theme to identify patterns, consistencies, and discrepancies. Look for how qualitative narratives support or contradict quantitative findings.
• Synthesis and interpretation: Synthesize the findings to develop an understanding of each theme. Interpret the data by integrating the qualitative insights with the quantitative results, explaining how they complement or contrast with each other.

A mixed methods matrix is a visual tool used to integrate and compare qualitative and quantitative data in mixed methods research. It helps researchers organize data according to key themes or variables, facilitating a comprehensive analysis and interpretation.

The matrix consists of several rows and columns:

• Rows represent key themes or research questions
• Columns represent different data sources or methods (e.g. interviews, surveys, observations)

By populating each cell with relevant data segments, researchers can easily identify areas of convergence, divergence, and complementarity. Let’s say you want to answer this research question: How does a new health intervention impact patient satisfaction and health outcomes?

You would populate the matrix as follows:

How to conduct mixed methods research: A mixed method research example

Let’s say you own a project management app and want to understand user satisfaction and identify areas for improvement. Here are eight steps to apply mixed methods research—using the convergent parallel technique—to discover user pain points and create a better user experience.

Step 1: Define your research objectives

In UX research , asking the right questions is crucial for identifying user needs and pain points effectively. But in order to write the right user research questions , you need to define a clear objective. What are you looking to understand?

Defining a clear UX research objective helps guide all other research decisions and acts as a lighthouse that guides your research project.

In our example , our research objective could be ‘to explore user experience and identify areas for improvement within our project management app’.

Step 2: Design your study and recruit participants

Ensure your study is designed to allow integration of both quantitative and qualitative data. There are various mixed method research designs to choose from—the right one for you depends on your research objectives and preferences.

At this stage, you should also establish a clear strategy for data integration and decide how you’ll combine the qualitative and quantitative data during the UX reporting and analysis phase. This might involve merging data sets for comparative analysis , or embedding one data set within the other to provide additional context.

The integration plan should reflect your research goals and ensure that the combined data offers a clear understanding. For our study, we’ll design a convergent parallel mixed methods study and triangulate our data during the analysis phase. This enables us to find our what and our why.

This is also when you need to recruit research participants for your study. Consider what you’re studying and identify your target test audience. You then need to create a call-out for your research study—either on socials, via email, or with In-Product Prompts .

Alternatively, you can find and filter research participants using Maze Panel , then manage your participant relationships using Maze Reach .

Step 3: Collect quantitative data

Next up, you want to start gathering your quantitative data. A good way to do this is with a survey to collect numerical data that can be statistically analyzed. For example, a user satisfaction survey that includes rating scales (1–10) for various aspects of the software.

For our research into app user satisfaction, we asked:

• Please rate your overall satisfaction with the app (1–10)
• How often do you use the app per week?
• How easy is the app to use on a scale of 1 to 10?
• How likely are you to recommend the app to a friend or colleague (1–10)?

❓ Need a quick and easy way to create and manage surveys? Maze Feedback Surveys simplify your feedback collection process so you can focus on making the changes your customers want to see. You can quickly create surveys tailored to your needs with Maze's survey templates .

Step 4: Collect qualitative data

Once you’ve got your quantitative data, it’s time to collect your qualitative data. Consider conducting user interviews or focus groups to obtain detailed, descriptive data that provides context and deep understanding.

For our study, we selected 20 users from the survey who gave varied ratings and conducted 30-minute interviews, asking:

• What do you like most about the app?
• What features do you find difficult to use?
• Can you describe a recent experience using the app?
• What improvements would you suggest?

💬 User interviews are resource-intensive and time-consuming. Speed them up with Maze’s end-to-end user interview solution: Interview Studies .

Step 5: Quantitative data analysis

Now you’ve got all your data—it’s time to dig in. For your quantitative data, this involves using statistical methodology to identify trends and patterns.

When we looked at our example data, we calculated:

• CSAT score: 75%
• Frequency of use: 70% use the app daily
• Ease of use average score: 6.8/10
• Net Promoter Score (NPS): 65

Step 6: Qualitative data analysis

Analyzing qualitative data involves coding and categorizing qualitative responses to uncover themes and patterns. Identify recurring themes in user feedback, such as ease of use, functionality, and improvement areas. If you’re using Maze Interview Studies to analyze your findings, you can automatically extract key themes and summaries to speed this process up.

When reviewing qualitative data, we found a number of interesting nuggets in our qualitative data:

• Users express dissatisfaction with the app’s usability, specifically the navigation between different functionalities
• Users wish they could access their billing details via the app, instead of solely via the web
• User find the core functionality—the project management features—to be highly valuable to their day-to-day, but also report finding the interface to be clunky and unintuitive

Step 7: Integrate data and interpret findings

Following your analysis, combine the findings from both data sets and draw conclusions. Look for correlations and insights that span both types of data.

Example integration:

• High satisfaction scores (75%) but lower ease of use (6.8/10) prove a strong product market fit but call for a more intuitive experience
• Further qualitative research agreed with this conclusion and identified specific areas for improvement, such as adding additional functionalities and improving the interface

Step 8: Report findings to stakeholders for buy-in

Present the integrated results to highlight how qualitative insights support or explain quantitative trends.

The format of your report will depend on your audience:

• Internal stakeholders (project managers, designers): Consider a concise report with clear visuals like charts, graphs, and user quotes to highlight key findings and actionable recommendations
• External stakeholders (clients, investors): Create a formal report with a clear introduction, methodology section, and comprehensive results presentation, summarizing key findings and highlighting the impact on user satisfaction and app usage

Always strive to go beyond what the data says and explain why it matters.

For example, once we’d conducted our research and drawn conclusions, we compiled this into a report that shared:

• Research methods: We used mixed methods research (surveys and interviews) to explore existing user pain points and satisfaction levels.
• Overall findings: User satisfaction is moderately high (7.5/10), indicating a generally positive reception. However, the ease of use score (6.8/10) and qualitative feedback highlight significant usability issues for new users.
• Actionable next steps based on findings: Simplify the user interface to improve the experience for new users, potentially increasing overall satisfaction and ease of use scores.

Conducting mixed methods research with Maze

Mixed methods research is one of the most effective ways to boost your UX insights, and gather a more rounded understanding of your users’ problems and perspectives. Combining research methods and types of data can uncover insights you may otherwise miss. And while there are ideal times to conduct qualitative, quantitative, or mixed methods research, ultimately it really is as simple as more research = more insights .

If you’re looking for the ideal research companion to help conduct mixed methods research, consider Maze. Maze is the user research platform that empowers all teams with the research methods they need to get game-changing insights. Whether it’s a mixed methods study or a one-off test—Maze helps you gather accurate insights, faster, for more informed decision-making.

Frequently asked questions about mixed methods research

What is the purpose of mixed methods research?

The purpose of mixed methods research is to combine quantitative and qualitative data to provide a more complete understanding of a research problem. This approach helps validate findings, explore complex issues from multiple perspectives, and produce more reliable and actionable results.

What’s the difference between qualitative and quantitative research?

• Qualitative research explores non-numerical data to understand concepts, opinions, or experiences. It uses methods like interviews, focus groups, and observations to gather in-depth insights.
• Quantitative research focuses on numerical data to quantify variables and uncover patterns. It uses methods like surveys, experiments, and statistical analysis to measure and analyze data.

What is the difference between mixed methods and multiple methods?

Mixed methods research integrates qualitative (e.g. interviews) and quantitative (e.g. surveys) data within a single study. Multiple methods research uses various research approaches, but they can be either qualitative or quantitative. For example, it might use surveys and experiments (quantitative) or interviews and focus groups (qualitative) in different parts of a study without combining the data.