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A Beginner’s Guide to Qualitative UX Research

The ability to empathize with the user is at the heart of UX design. One of the most effective ways to understand what your user is experiencing is by conducting UX research .

Qualitative user research is particularly useful for getting into the mind of your users and obtaining anecdotal evidence of how your product can be improved.

Unlike its counterpart, quantitative research, qualitative research is all about collecting and analyzing subjective information that helps designers make formative decisions about their product designs. There are many ways to utilize qualitative user research and many instances during the design process when it can be especially beneficial.

We’ve created this comprehensive guide to help you better understand qualitative user research and how to use it. Here’s what we’ll cover:

• What is qualitative UX research?
• When do you use qualitative UX research?
• Qualitative UX research methods
• Understanding mixed methods in UX research
• Key takeaways

Let’s get started!

1. What is qualitative UX research?

The goal of qualitative user research is to obtain and analyze non-numerical, subjective information from various kinds of user testing.

Data from qualitative user research usually takes the form of quotes, anecdotes, observations, or narrative descriptions and is used to assess how usable a product is.

Qualitative user research helps explain numerical or quantitative data. For instance, if your quantitative research shows that 30% of users are deleting your app after one month of use, qualitative data can help uncover why and give clues about how to remedy this drop-off.

Check out the video below from CareerFoundry graduate and UX designer Maureen Herben for an end-to-end guide to qualitative user research.

2. When do you use qualitative UX research?

Qualitative user research is both formative and summative, meaning it can help inform design choices while a product is being created as well as analyze how effective the final design is.

Because of this, qualitative user research is often conducted at many points in the design process, during redesign, and when you have a final working product. Here’s an overview of the benefits of qualitative research, some potential downsides, and situations when you should apply qualitative methods in your user research.

Benefits of qualitative UX research

• Easy to organize as you only need 5-8 participants and study conditions can be flexible and less controlled
• Participants are encouraged to think aloud during usability testing so researchers can see inside the minds and emotions of their users when interacting with a product
• Reveals information that quantitative data cannot, and explains why numerical or statistical trends are occurring
• Data obtained from qualitative user research is emotionally-driven and may be more convincing for stakeholders to invest in design choices
• Users may find it easier to give feedback in their own words rather than assigning a numerical value to their feelings.

Potential downsides to qualitative UX research

• Analysis can be more time-consuming and complex and difficult to present in graphs or visual form
• Smaller number of participants may mean that you’re missing out on crucial information from other users, leading to the need for repeat testing
• Researchers must be adept at reading emotional and non-verbal cues
• Certain investors or stakeholders may prefer numerical or statistical data as opposed to anecdotal, qualitative research
• More subject to human bias or researcher influence, and results are difficult to replicate

When to use qualitative UX research

• When you’re making formative decisions about design choices, early in the process
• To identify usability issues within a prototype (toward the “end” of the design process) or a final product
• As a means of discovering solutions to usability issues
• During a product redesign, when there are typically more resources available and more capacity to consider a broader range of possibilities

3. Qualitative UX research methods

There are many ways to conduct qualitative user research. We’ll cover four primary methods here: user interviews, focus groups, shadow sessions, and diary studies.

User interviews

User interviews are a great source of qualitative user data and help researchers and designs gain a greater understanding of their user’s motivations, needs, and behaviors.

It’s important to ask quality open-ended questions in order to gain relevant and useful information about the user’s actions and frustrations.

User interviews are one of the most frequently used qualitative UX research methods. If you’d like to learn more about how to conduct a user interview, check out this recording of a live workshop, hosted by CareerFoundry graduate and Senior UX Designer, Maureen Herben.

For more free, live and on-demand workshops just like this, take a look at our events listings .

Focus groups

Focus groups are just like interviews but with multiple users participating at once. These are great for getting lots of qualitative data at once from various user viewpoints.

These sessions are likely to feel more conversational and generative since participants may feel more at ease with other test subjects around them—and therefore more willing to express concerns, thoughts, and emotions.

Shadow sessions

Sometimes called immersive or observational research, shadow sessions allow designers and researchers to observe a user interacting with a product in real time and in the user’s own environment.

This is one of the most accurate ways to assess usage and usability but also requires a high level of observational skills and empathy in order to analyze verbal and non-verbal cues without interrupting the user’s natural process.

Diary studies

In diary studies (sometimes referred to as diary records), researchers ask a user to keep a diary record of their usability patterns with a certain product over a given time period (usually a day or week, but sometimes more).

Users take note of how they use a product, when they use it, and how they feel when interacting with it. Diary studies are a great way to see what patterns emerge over time—patterns in user needs and feelings, as well as any usability problems or other pain points.

4. Understanding mixed methods in UX research

The UX research methods we’ve just outlined are solely qualitative in nature. But there are loads of research methods that yield both qualitative and quantitative user data within the same testing parameters. Paper prototyping, card sorting, and visual affordance testing are a few examples.

Utilizing user research methods that offer both qualitative and  quantitative UX research is referred to as mixed methods research . Mixed methods research is key to obtaining a complete picture of the usability of a product and is best practice when it comes to conducting accurate user research.

Combining qualitative and quantitative user research methods helps designers dig deeper in answering the questions of “What? How much? How many? And why?”

Relying too heavily on either qualitative or quantitative user research can prevent you from gaining key insights about your users and possible pitfalls in your product. Taking advantage of mixed methods research is a more holistic approach to user research, and often lends more accurate and complete information about a product’s overall usability and effectiveness.

5. Key takeaways

Now you’re better equipped for your next UX research project !

Qualitative user research can take on many forms, yet each method can offer invaluable insights about the usability of a product.

The subjective and non-numerical data obtained from qualitative testing helps designers and researchers see into the minds of their users when interacting with a product.

Through quotes, descriptions, and observations, qualitative research aims to further explain statistical or quantitative results by looking at why those trends may be occurring, and gives a more in-depth interpretation of the usability and success of a product.

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

• What is user research, and what’s its purpose?
• Qualitative vs. quantitative UX research—what’s the difference?
• How to conduct inclusive user research
• 5 Mistakes to avoid in your UX research portfolio

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Making Your UX Life Easier with the MoSCoW

If you’re stuck trying to move a project forward because it seems like there are too many things to concentrate on then the MoSCoW method may help you get unstuck. It’s a prioritization technique which is easy to learn and simple to apply. It can also help you decide what’s really valuable for your UX projects before you get started on them.

There are many different prioritization techniques that can be employed on design projects but one of the simplest to use is the MoSCoW method. It’s used across all business disciplines to enable project teams to work with stakeholders to define requirements. It can also be used as a personal prioritization technique.

What Does MoSCoW Stand For?

MoSCoW is an (almost) acronym designed to reflect the four categories used by the technique to determine priorities; Must have, Should have, Could have and Would like but won’t get. The lower case “o’s” are added simply to give the acronym a pronounceable form. Occasionally, you may also see the whole phrase in block capitals MOSCOW to distinguish it from the name of the city but MoSCoW is more common.

What is the MoSCoW Method?

Experts Dai Clegg and Richard Barker proposed the method in their paper “Case Method Fast-Track: A RAD Approach” and while it was initially intended to be used with the Dynamic Systems Development Method (DSDM) it has long since been adopted throughout many areas of business. In recent times it has become very popular in the Agile and RAD (rapid application development) communities.

The MoSCoW method is most effective when it comes to prioritizing requirements in projects with either fixed or tight deadlines. It works by understanding the idea that all project requirements can be considered important but that they should be prioritized to give the biggest benefits in the fastest possible time frame.

It breaks down the requirements into four categories:

These are the requirements without which a project will fail. They MUST be delivered within the timeframe in order for anyone involved with the project to move on. In essence they make up the MVP ( Minimum Viable Product ) though it can be argued that MUST could stand for Minimum Usable SubseT too.

Should have

Should have requirements aren’t 100% necessary for delivering the project successfully but they are the “most nice to have” out of the list. They may be less time critical than “must have” or might be better held for a future release.

Could have requirements are just “nice to have” they are desirable to provide a nice user experience or customer experience but they’re not that important to the delivery of the project. They will be delivered only if there’s enough time and resources to spare to devote to them. Otherwise, they’re likely to be tabled for future releases and re-reviewed to see if they have become higher or lower priority in the interim.

These are the requirements that everyone agrees aren’t going to happen. It might be because they cost too much to implement or provide too little ROI (Return on Investment) for the efforts required to implement them. These are simply left to one side until they are either removed from the requirements list or become a higher priority.

The MoSCoW method provides a simple way of clarifying the priorities involved on a project. It’s most useful in time bound situations and it can be used to prioritize your own workload (usually with the buy in from a supervisor or manager if you work for someone else) as easily as it can be used for project work.

Implementing MoSCoW – A Practical Process

The easiest way to use MoSCoW is to bring together all the relevant stakeholders to the project and then:

List the requirements (on a flip chart or on a screen)

Vote on which category each requirement falls into (bearing in mind any hierarchical issues within the company itself – the CEOs vote may count for more than the votes of everyone else in the room)

Then collate the information and ensure that each requirement is presented against the relevant category in written form so that it can be used for reference by the project team

You can repeat this exercise whenever you feel it is necessary. Priorities may change mid-project or between releases. It’s important for everyone to understand what the implications of changing priorities in the middle of a project may be in terms of costs, resources, and time.

Issues with MoSCoW

It’s important to know that the MoSCoW method isn’t without its detractors. The main flaw in the method, as identified by authors Kark Weigers and Joy Beatty in their book Software Requirements, is that the method offers no means for comparing one requirement to another. This can make it difficult for those tasked with prioritizing requirements to know which category to place them in.

The Take Away

The MoSCoW method offers a simple process for prioritizing within project delivery. It can also be used to prioritize your work load. It should be used with some caution in that it may be too simple – particularly for complex projects – but it makes for a good starting point. One of the big advantages to its simplicity is that it should be easy to get buy in from other stakeholders to put it into practice.

Check out this useful study into how the MoSCoW method is used by business analysts .

You can read about the MoSCoW method as it was originally designed in: Clegg, Dai; Barker, Richard (2004-11-09). Case Method Fast-Track: A RAD Approach. Addison-Wesley. ISBN 978-0-201-62432-8.

You can read Weigers and Beatty’s criticism and their suggestion for a more complex method in: Wiegers, Karl; Beatty, Joy (2013). Software Requirements. Washington, USA: Microsoft Press. pp. 320–321. ISBN 978-0-7356-7966-5.

Hero Image: Author/Copyright holder: Agile Connection. Copyright terms and licence: All rights reserved. Img

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Environmental Qualitative Research at EPA

Oak Ridge Associated Universities

• Posted 5 days ago
• Application deadline: 2024-04-18

As a team member, you will assist in the provision of data collection, transcription, and qualitative analysis services to support social science research. The social science research conducted at the EPA’s Great Lakes Toxicology and Ecology Division (GLTED) utilizes case study methods that apply both theory-testing and theory-building approaches. Data collection methods document the behavior and decisions of different stakeholder groups through participant observation, document analysis, and social media mining. The research goal is to understand the decision-making process and how context shapes behavior and preferences related to the environment.

The team member will also have the opportunity to learn about and contribute to environmental decision-making for a real-world problem revolving around ecological outcomes and socioeconomic benefits of restoration and redevelopment of an urban river through a study of how actors navigate the process. The team member will work with other members of GLTED’s Sustainable and Healthy Communities team to conduct participatory community research. Responsibilities include but are not limited to attending meetings, preparing meeting and/or interview transcripts, coding and analyzing interview data, and assisting in background research, writing, and dissemination of results.

To apply for this job please visit www.zintellect.com .

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UX Researcher, Quantitative

• Work closely with product and business teams to identify research topics
• Act as a thought leader in the domain of research, while advocating for the people who could use our products
• Design and execute end-to-end custom primary research using a wide variety of methods
• Design studies that address both user behavior and attitudes
• Ability to work independently and autonomously
• Effectively manage and prioritize research plans through ambiguous and fast-changing environments, align and efficiently execute critical insights and work with a large group of stakeholders
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• Bachelor’s degree with 7+ years of relevant experience in user experience, applied research and/or product research and development, Master’s degree and 5+ years relevant experience, or a PhD and 2+ years of relevant experience
• Experience coding with R, SQL, STATA, SPSS or equivalent
• Experience with survey design and response effects
• Experience applying statistical analysis methods such as Regressions, ANOVA, and T-Tests
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• Degrees in a human behavior related field, such as Human-Computer Interaction, Psychology, Sociology, Communication, Information Science, Media Studies, Computer Science, or Economics
• Experience with consumer products, consumer insights, or product development

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