what is ux hypothesis

InVisionApp, Inc.

Inside Design

5 steps to a hypothesis-driven design process

  •   mar 22, 2018.

S ay you’re starting a greenfield project, or you’re redesigning a legacy app. The product owner gives you some high-level goals. Lots of ideas and questions are in your mind, and you’re not sure where to start.

Hypothesis-driven design will help you navigate through a unknown space so you can come out at the end of the process with actionable next steps.

Ready? Let’s dive in.

Step 1: Start with questions and assumptions

On the first day of the project, you’re curious about all the different aspects of your product. “How could we increase the engagement on the homepage? ” “ What features are important for our users? ”

Related: 6 ways to speed up and improve your product design process

To reduce risk, I like to take some time to write down all the unanswered questions and assumptions. So grab some sticky notes and write all your questions down on the notes (one question per note).

I recommend that you use the How Might We technique from IDEO to phrase the questions and turn your assumptions into questions. It’ll help you frame the questions in a more open-ended way to avoid building the solution into the statement prematurely. For example, you have an idea that you want to make riders feel more comfortable by showing them how many rides the driver has completed. You can rephrase the question to “ How might we ensure rider feel comfortable when taking ride, ” and leave the solution part out to the later step.

“It’s easy to come up with design ideas, but it’s hard to solve the right problem.”

It’s even more valuable to have your team members participate in the question brainstorming session. Having diverse disciplines in the room always brings fresh perspectives and leads to a more productive conversation.

Step 2: Prioritize the questions and assumptions

Now that you have all the questions on sticky notes, organize them into groups to make it easier to review them. It’s especially helpful if you can do the activity with your team so you can have more input from everybody.

When it comes to choosing which question to tackle first, think about what would impact your product the most or what would bring the most value to your users.

If you have a big group, you can Dot Vote to prioritize the questions. Here’s how it works: Everyone has three dots, and each person gets to vote on what they think is the most important question to answer in order to build a successful product. It’s a common prioritization technique that’s also used in the Sprint book by Jake Knapp —he writes, “ The prioritization process isn’t perfect, but it leads to pretty good decisions and it happens fast. ”

Related: Go inside design at Google Ventures

Step 3: Turn them into hypotheses

After the prioritization, you now have a clear question in mind. It’s time to turn the question into a hypothesis. Think about how you would answer the question.

Let’s continue the previous ride-hailing service example. The question you have is “ How might we make people feel safe and comfortable when using the service? ”

Based on this question, the solutions can be:

• Sharing the rider’s location with friends and family automatically
• Displaying more information about the driver
• Showing feedback from previous riders

Now you can combine the solution and question, and turn it into a hypothesis. Hypothesis is a framework that can help you clearly define the question and solution, and eliminate assumption.

From Lean UX

We believe that [ sharing more information about the driver’s experience and stories ] For [ the riders ] Will [ make riders feel more comfortable and connected throughout the ride ]

4. Develop an experiment and testing the hypothesis

Develop an experiment so you can test your hypothesis. Our test will follow the scientific methods, so it’s subject to collecting empirical and measurable evidence in order to obtain new knowledge. In other words, it’s crucial to have a measurable outcome for the hypothesis so we can determine whether it has succeeded or failed.

There are different ways you can create an experiment, such as interview, survey , landing page validation, usability testing, etc. It could also be something that’s built into the software to get quantitative data from users. Write down what the experiment will be, and define the outcomes that determine whether the hypothesis is valids. A well-defined experiment can validate/invalidate the hypothesis.

In our example, we could define the experiment as “ We will run X studies to show more information about a driver (number of ride, years of experience), and ask follow-up questions to identify the rider’s emotion associated with this ride (safe, fun, interesting, etc.). We will know the hypothesis is valid when we get more than 70% identify the ride as safe or comfortable. ”

After defining the experiment, it’s time to get the design done. You don’t need to have every design detail thought through. You can focus on designing what is needed to be tested.

When the design is ready, you’re ready to run the test. Recruit the users you want to target , have a time frame, and put the design in front of the users.

5. Learn and build

You just learned that the result was positive and you’re excited to roll out the feature. That’s great! If the hypothesis failed, don’t worry—you’ll be able to gain some insights from that experiment. Now you have some new evidence that you can use to run your next experiment. In each experiment, you’ll learn something new about your product and your customers.

“Design is a never-ending process.”

What other information can you show to make riders feel safe and comfortable? That can be your next hypothesis. You now have a feature that’s ready to be built, and a new hypothesis to be tested.

Principles from from The Lean Startup

We often assume that we understand our users and know what they want. It’s important to slow down and take a moment to understand the questions and assumptions we have about our product.

After testing each hypothesis, you’ll get a clearer path of what’s most important to the users and where you need to dig deeper. You’ll have a clear direction for what to do next.

by Sylvia Lai

Sylvia Lai helps startup and enterprise solve complex problems through design thinking and user-centered design methodologies at Pivotal Labs . She is the biggest advocate for the users, making sure their voices are heard is her number one priority. Outside of work, she loves mentoring other designers through one-on-one conversation. Connect with her through LinkedIn or Twitter .

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UX Research: Objectives, Assumptions, and Hypothesis

by Rick Dzekman

An often neglected step in UX research

Introduction

UX research should always be done for a clear purpose – otherwise you’re wasting the both your time and the time of your participants. But many people who do UX research fail to properly articulate the purpose in their research objectives. A major issue is that the research objectives include assumptions that have not been properly defined.

When planning UX research you have some goal in mind:

• For generative research it’s usually to find out something about users or customers that you previously did not know
• For evaluative research it’s usually to identify any potential issues in a solution

As part of this goal you write down research objectives that help you achieve that goal. But for many researchers (especially more junior ones) they are missing some key steps:

• How will those research objectives help to reach that goal?
• What assumptions have you made that are necessary for those objectives to reach that goal?
• How does your research (questions, tasks, observations, etc.) help meet those objectives?
• What kind of responses or observations do you need from your participants to meet those objectives?

One approach people use is to write their objectives in the form of research hypothesis. There are a lot of problems when trying to validate a hypothesis with qualitative research and sometimes even with quantitative.

This article focuses largely on qualitative research: interviews, user tests, diary studies, ethnographic research, etc. With qualitative research in mind let’s start by taking a look at a few examples of UX research hypothesis and how they may be problematic.

Research hypothesis

Example hypothesis: users want to be able to filter products by colour.

At first it may seem that there are a number of ways to test this hypothesis with qualitative research. For example we might:

• Observe users shopping on sites with and without colour filters and see whether or not they use them
• Ask users who are interested in our products about how narrow down their choices
• Run a diary study where participants document the ways they narrowed down their searches on various stores
• Make a prototype with colour filters and see if participants use them unprompted

These approaches are all effective but they do not and cannot prove or disprove our hypothesis. It’s not that the research methods are ineffective it’s that the hypothesis itself is poorly expressed.

The first problem is that there are hidden assumptions made by this hypothesis. Presumably we would be doing this research to decide between a choice of possible filters we could implement. But there’s no obvious link between users wanting to filter by colour and a benefit from us implementing a colour filter. Users may say they want it but how will that actually benefit their experience?

The second problem with this hypothesis is that we’re asking a question about “users” in general. How many users would have to want colour filters before we could say that this hypothesis is true?

Example Hypothesis: Adding a colour filter would make it easier for users to find the right products

This is an obvious improvement to the first example but it still has problems. We could of course identify further assumptions but that will be true of pretty much any hypothesis. The problem again comes from speaking about users in general.

Perhaps if we add the ability to filter by colour it might make the possible filters crowded and make it more difficult for users who don’t need colour to find the filter that they do need. Perhaps there is a sample bias in our research participants that does not apply broadly to our user base.

It is difficult (though not impossible) to design research that could prove or disprove this hypothesis. Any such research would have to be quantitative in nature. And we would have to spend time mapping out what it means for something to be “easier” or what “the right products” are.

Example Hypothesis: Travelers book flights before they book their hotels

The problem with this hypothesis should now be obvious: what would it actually mean for this hypothesis to be proved or disproved? What portion of travelers would need to book their flights first for us to consider this true?

Example Hypothesis: Most users who come to our app know where and when they want to fly

This hypothesis is better because it talks about “most users” rather than users in general. “Most” would need to be better defined but at least this hypothesis is possible to prove or disprove.

We could address this hypothesis with quantitative research. If we found out that it was true we could focus our design around the primary use case or do further research about how to attract users at different stages of their journey.

However there is no clear way to prove or disprove this hypothesis with qualitative research. If the app has a million users and 15/20 research participants tell you that this is true would your findings generalise to the entire user base? The margin of error on that finding is 20-25%, meaning that the true results could be closer to 50% or even 100% depending on how unlucky you are with your sample.

Example Hypothesis: Customers want their bank to help them build better savings habits

There are many things wrong with this hypothesis but we will focus on the hidden assumptions and the links to design decisions. Two big assumptions are that (1) it’s possible to find out what research participants want and (2) people’s wants should dictate what features or services to provide.

Research objectives

One of the biggest problem with using hypotheses is that they set the wrong expectations about what your research results are telling you. In Thinking, Fast and Slow, Daniel Kahneman points out that:

• “extreme outcomes (both high and low) are more likely to be found in small than in large samples”
• “the prominence of causal intuitions is a recurrent theme in this book because people are prone to apply causal thinking inappropriately, to situations that require statistical reasoning”
• “when people believe a conclusion is true, they are also very likely to believe arguments that appear to support it, even when these arguments are unsound”

Using a research hypothesis primes us to think that we have found some fundamental truth about user behaviour from our qualitative research. This leads to overconfidence about what the research is saying and to poor quality research that could simply have been skipped in exchange for simply making assumption. To once again quote Kahneman: “you do not believe that these results apply to you because they correspond to nothing in your subjective experience”.

We can fix these problems by instead putting our focus on research objectives. We pay attention to the reason that we are doing the research and work to understand if the results we get could help us with our objectives.

This does not get us off the hook however because we can still create poor research objectives.

Let’s look back at one of our prior hypothesis examples and try to find effective research objectives instead.

Example objectives: deciding on filters

In thinking about the colour filter we might imagine that this fits into a larger project where we are trying to decide what filters we should implement. This is decidedly different research to trying to decide what order to implement filters in or understand how they should work. In this case perhaps we have limited resources and just want to decide what to implement first.

A good approach would be quantitative research designed to produce some sort of ranking. But we should not dismiss qualitative research for this particular project – provided our assumptions are well defined.

Let’s consider this research objective: Understand how users might map their needs against the products that we offer . There are three key aspects to this objective:

• “Understand” is a common form of research objective and is a way that qualitative research can discover things that we cannot find with quant. If we don’t yet understand some user attitude or behaviour we cannot quantify it. By focusing our objective on understanding we are looking at uncovering unknowns.
• By using the word “might” we are not definitively stating that our research will reveal all of the ways that users think about their needs.
• Our focus is on understanding the users’ mental models. Then we are not designing for what users say that they want and we aren’t even designing for existing behaviour. Instead we are designing for some underlying need.

The next step is to look at the assumptions that we are making. One assumption is that mental models are roughly the same between most people. So even though different users may have different problems that for the most part people tend to think about solving problems with the same mental machinery. As we do more research we might discover that this assumption is not true and there are distinctly different kinds of behaviours. Perhaps we know what those are in advance and we can recruit our research participants in a way that covers those distinct behaviours.

Another assumption is that if we understand our users’ mental models that we will be able to design a solution that will work for most people. There are of course more assumptions we could map but this is a good start.

Now let’s look at another research objective: Understand why users choose particular filters . Again we are looking to understand something that we did not know before.

Perhaps we have some prior research that tells us what the biggest pain points are that our products solve. If we have an understanding of why certain filters are used we can think about how those motivations fit in with our existing knowledge.

Mapping objectives to our research plan

Our actual research will involve some form of asking questions and/or making observations. It’s important that we don’t simply forget about our research objectives and start writing questions. This leads to completing research and realising that you haven’t captured anything about some specific objective.

An important step is to explicitly write down all the assumptions that we are making in our research and to update those assumptions as we write our questions or instructions. These assumptions will help us frame our research plan and make sure that we are actually learning the things that we think we are learning. Consider even high level assumptions such as: a solution we design with these insights will lead to a better experience, or that a better experience is necessarily better for the user.

Once we have our main assumptions defined the next step is to break our research objective down further.

Breaking down our objectives

The best way to consider this breakdown is to think about what things we could learn that would contribute to meeting our research objective. Let’s consider one of the previous examples: Understand how users might map their needs against the products that we offer

We may have an assumption that users do in fact have some mental representation of their needs that align with the products they might purchase. An aspect of this research objective is to understand whether or not this true. So two sub-objectives may be to (1) understand why users actually buy these sorts of products (if at all), and (2) understand how users go about choosing which product to buy.

Next we might want to understand what our users needs actually are or if we already have research about this understand which particular needs apply to our research participants and why.

And finally we would want to understand what factors go into addressing a particular need. We may leave this open ended or even show participants attributes of the products and ask which ones address those needs and why.

Once we have a list of sub-objectives we could continue to drill down until we feel we’ve exhausted all the nuances. If we’re happy with our objectives the next step is to think about what responses (or observations) we would need in order to answer those objectives.

It’s still important that we ask open ended questions and see what our participants say unprompted. But we also don’t want our research to be so open that we never actually make any progress on our research objectives.

Reviewing our objectives and pilot studies

At the end it’s important to review every task, question, scenario, etc. and seeing which research objectives are being addressed. This is vital to make sure that your planning is worthwhile and that you haven’t missed anything.

If there’s time it’s also useful to run a pilot study and analyse the responses to see if they help to address your objectives.

Plan accordingly

It should be easy to see why research hypothesis are not suitable for most qualitative research. While it is possible to create suitable hypothesis it is more often than not going to lead to poor quality research. This is because hypothesis create the impression that qualitative research can find things that generalise to the entire user base. In general this is not true for the sample sizes typically used for qualitative research and also generally not the reason that we do qualitative research in the first place.

Instead we should focus on producing effective research objectives and making sure every part of our research plan maps to a suitable objective.

Hypothesis statement

• Introduction to Hypothesis statement
• Essential characteristics

Introduction to hypothesis statements

Brainstorming solutions is similar to making a hypothesis or an educated guess about how to solve the problem.

In UX design, we write down possible solutions to the problem as hypothesis statements. A good hypothesis statement requires more effort than just a guess. In particular, your hypothesis statement may start with a question that can be further explored through background research.

How do you write hypothesis statements? Unlike problem statements, there's no standard formula for writing hypothesis statements. For starters, let's try what's called an if-then statement.

It looks like this: If (name an action), then (name an outcome).

Hypothesis statements don't have a standard formula. Instead of an if-then statement, you can formulate this hypothesis statement in a more flexible way.

Essential characteristics of a hypothesis statement

To formulate a promising hypothesis, ask yourself the following questions:

Is the language clear and purposeful?

What is the relationship between your hypothesis and your research topic?

Is your hypothesis testable? If so, how?

What possible explanations would you like to explore?

You may need to come up with more than one hypothesis for a problem. That's okay! There will always be multiple solutions to your users' problems. Your job is to use your creativity and problem-solving skills to decide which solutions are best for each user you are designing for.

• #ClearLanguage
• #HypothesisVSResearchTopic
• #PossibleExplanations

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User experience, definition of a good design, lifecycle product development

UX Design Frameworks

Key frameworks.

User-Centered Design, the five elements of UX Design, Design Thinking, Lean UX, Double Diamond

Equity and Accessibility

Designing for all.

Universal design, inclusive design, and equity-focused design

The importance of Accessibility

Motor disabilities, deaf or hard of hearing, cognitive disabilities, visual disabilities

Design for the Next Billion User (Google)

Majority of people that gets online for the first time

Design for different platforms

Responsiveness, Call-to-actions, navigation and more

The 4Cs of princples of design

Consistency, Continuity Context and Complementary principles

Assistive Technology

Voice control and switch devices, screen readers, alternative text and speech

Impostor Syndrome/Biases

Overcome the impostor syndrome.

Impostor Syndrome is the feeling that makes you doubt that you actually earn your accomplishments.

Most common Biases

Learn about favoring or having prejudice against something based on limited information.

Prevent Biases

Recognize your own biases and prevent them from affecting your work.

Design Sprint

Introduction to design sprint.

Introduction to the framework, benefits and advantages

Plan a Design Sprint

Tips and tricks about design sprint planning

Write a Design Sprint brief

Insights and free canvas about making a design sprint brief.

Design Sprint retrospective

What went well? What can be improved?

UX Research

Introduction to ux research.

Learn techniques of research for designing better products

Foundational Research

Easily center on a problem or topic that's undefined in your project's scope

Design Research

Find stories, engage in conversations, understand the users motivations

Post-Launch Research

Know the impact of pre- and post-launch publicity and advertising on new product sales

Choosing the right Research method

Learn which research method to pick depending on the questions you still have unanswered

Benefits and drawbacks

Learn how to create an optimal product for the user

Recruit interview participants

Learn how to determine interview goals and write questions

Conduct user interviews

Insights on how to be prepared before speaking with real users

Create interview transcripts

Discover new topics of interest through a written transcript

Empathize with users

Master ability to fully understand, mirror a person's expressions, needs, and motivations

Consider a11y when empathizing

Learn why empathizing and accessibility go hand in hand

Empathy Maps

Learn how to empathize and synthesise your observations from the research phase

Identify pain points

Identify a specific problem that your users are experiencing

Understand personas

Learn how to shape product strategy and accompany it the usability testing sessions

User stories

Learn how to base your user stories on user goals and keep the product user focused

Create a user journey map

Learn how to make a visual representation of the customer experience

Determine value propositions

Set and explain why a customer should buy from you

Create and define a problem statement

Learn how to focus on the specific needs that you have uncovered yet

Learn how to predict the behavior of a proposed solution

Learn how people interact with technology

Competitive Audits

Introduction to competitive audits, limits to competitive audits, steps to conduct competitive audits, present a competitive audit, design ideation, understand design ideation, business needs during ideation, use insights from competitive audits to ideate, use "how might we" to ideate, use crazy eights to ideate, use journey map to ideate, goal statements, build a goal statement, introduction to user flows, storyboarding user flows, types of storyboards, wireframing, introduction to wireframes, paper wireframes, transition from paper to digital wireframes, information architecture, ethical and inclusive design, identify deceptive patterns, role as a ux designer, press shift to trigger the table of contents.

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What is UX Research: The Ultimate Guide for UX Researchers

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User experience research is a crucial component of the human-centered design process and an essential part of creating solutions that meet user expectations and deliver value to customers. This comprehensive guide to UX research dives into the fundamentals of research and its various methods and includes tips and best practices from leading industry experts.

Make informed design decisions with user research

Validate ideas, test prototypes, assess usability, and deliver real, actionable insights to your product team.

UX research: Your ultimate guide to nailing user experience and exceeding expectation

User experience research, or UX research , is the process of gathering insights about users' behaviors, needs, and pain points through observation techniques and feedback methodologies. It’s a form of user research that looks at how users interact with your product, helping bridge the gaps between what you think users need, what users say they need—and what they actually need.

The goal of UX research is to understand your users and gain context and perspectives to help make informed decisions and build user-centered products. It’s an essential part of designing, developing, and launching a product that will be an instant hit—but it should also be used throughout the product’s lifecycle post-launch to keep updated, and ensure new features are relevant to your audience.

As Sinéad Davis Cochrane , UX Manager at Workday, explains: “UX research represents insights gathered directly from users and customers, that helps you make product decisions at every stage of the development process.”

Is UX research the same as user research?

The terms ‘user research’ and ‘UX research’ are often used interchangeably, but they do differ. User research is the parent of UX research; it’s a broader research effort that aims to understand the demographics, behaviors, and sentiments of your users and personas.

UX research, on the other hand, is a type of user research that’s specific to your product or platform. Where user research focuses on the user as a whole, UX research considers how they interact with, respond to, and feel about your product or concept itself.

In both cases, the overarching goal is to get to know your users, understand what they need from your product, gain context to help make informed decisions, and build human-centered experiences.

Involve your users at every stage of your design process

Create research projects with Maze using customizable templates, and start making data-informed product decisions

Why is conducting UX research important?

In an ideal world, users would find your product easy to navigate, your net promoter score (NPS) would be off the charts, and you’d see adoption and activation rates skyrocket. In reality, however, this can be a challenging dream to achieve—but it is possible. The only way to build a product that users really resonate with is by involving them throughout the development process and building with them.

UX research is more than just a single ‘step’ in the development process: it should happen continuously, throughout the product lifecycle—so whether you’re building new products or iterating on existing ones, every decision is informed by user insights.

Here’s what you can achieve with continuous UX research:

Make informed decisions based on data

Our 2023 Continuous Research Report shows that 74% of people who do research (PWDR) believe research is crucial to guiding product decisions. Plus, 60% of respondents find that user recommendations inspire new product ideas.

Getting stakeholder buy-in to product decisions can be challenging, but when you suggest changes based on UX research, you have data to back up your suggestions. Your users inform your product, becoming the decision-makers as well as the customer.

UX research helps reduce and mitigate the risk of building the wrong thing—or building the right thing in the wrong way.

Sinéad Davis Cochrane , UX Manager at Workday

Reduce bias in the UX design process

There are hundreds of cognitive biases identified by psychologists, many of which unknowingly influence our decisions and the products we build. But a key principle of great UX design is to put aside existing beliefs, and learn from your users.

“You have to be humble, optimistic, and open-minded,” says Bertrand Berlureau , Senior Product Designer at iMSA. Using effective UX research, you can root out bias or assumptions, and follow real human behavior to inform product decisions.

According to Sinéad, you should consider these questions early in the design process:

• “What are your assumptions?”
• “What are some of the assumptions you’ve been making about your end-users and product without any evidence?”
• “What are the anecdotes or coincidental pieces of information that you hold, and how can you challenge them?”

Biases can subconsciously affect research and UX design, and it can be tricky to identify them. The first step to overcoming cognitive biases is by being aware of them. Head to chapter three of our cognitive biases guide to discover how.

Test and validate concepts

The power of UX research is that it can prove you right or wrong—but either way, you’ll end up knowing more and creating a product that provides a better user experience. For Bertrand, an idea without a test is just an idea. So, before the design process, his team starts with these user research methods:

• Face-to-face and remote user interviews
• Focus groups
• Co-creativity sessions through design sprints, quick prototyping, and hypothesis concepts
• User testing

UX research is the only way to unequivocally confirm your product is solving the right problem, in the right way. By speaking directly to real users, you can pinpoint what ideas to focus on, then validate your proposed solution, before investing too much time or money into the wrong concept.

Work on solutions that bring real value to customers

Another main benefit of UX research is that it allows product teams to mitigate risk and come up with products users want to use. “One of the main risks we need to control is whether users actually want to use a solution we've implemented,” explains Luke Vella , Group Product Manager at Maze. “UX research helps us reduce this risk, allowing us to build solutions that our customers see as valuable and make sure that they know how to unlock that value.”

Luke works on pricing and packaging, an area that requires constant user research. On one hand, he and his team want to understand which problems their users are facing and come up with plans to satisfy those different needs. On the other hand, they need to make sure they can monetize in a sustainable way to further invest in the product. You can only get this perfect balance by speaking to users to inform each step of the decision.

Market your product internally and externally

UX research also plays a crucial role in helping product marketers understand the customer and effectively communicate a product's value to the market—after all, a product can only help those who know about it.

For example, Naomi Francis , Senior Product Marketing Manager at Maze, uses different research methods to inform marketing strategy. Naomi conducts user interviews to build personas, using user research to collect insights on messaging drafts, product naming, and running surveys to gather user feedback on beta products and onboarding.

Understanding how and why customers need and use our product pushes marketing launches to the next level—you can get a steer on everything from messaging to language and approach.

Naomi Francis , Senior Product Marketing Manager at Maze

Types of UX research

All UX research methods fit into broader UX research techniques that drive different goals, and provide different types of insight. You can skip to chapter seven for a rundown of the top 9 UX research methods , or keep reading for a deep dive on the main types of UX research:

• Moderated and unmoderated
• Remote and in-person
• Generate and evaluate
• Qualitative and quantitative
• Behavioral and attitudinal

Where moderated/unmoderated and remote/in-person refer to the way research is conducted , the other types of UX research reflect the type of data they gather.

The most powerful insights come from a mixture of testing types—e.g. attitudinal and behavioral, generative and evaluative, and quantitative and qualitative. You don’t need to run all types of research at all times, but you’ll benefit from gathering multiple types of data throughout different stages of product development.

Moderated research

Moderated research is any research conducted with a facilitator or researcher present. A moderator may observe research sessions and take notes, ask questions, or provide instruction to participants where needed.

Like all research, it’s crucial a moderator doesn’t overly guide participants or influence results. Due to certain types of cognitive biases , people may behave differently while being observed, so researchers often opt for unmoderated methods to avoid results being impacted.

UX research methods for moderated research

• User interviews to speak directly with your target user face-to-face
• Focus groups to gather feedback on a variety of topics
• Moderated usability testing to hear the thought process behind the actions

Unmoderated research

As the name suggests, unmoderated research refers to the lack of a moderator. Often used in tandem with remote research , users complete tasks independently, guided by pre-written instructions.

Unmoderated research is helpful to ensure users are acting entirely of their own volition, and it has a lower cost and quicker turnaround than moderated research—however it does require efficient planning and preparation, to ensure users can navigate the tasks unaided.

UX research methods for unmoderated research

• Unmoderated usability testing to see how easily users navigate your product
• Live website testing to witness users interacting with your product in real time
• Surveys to have users answer specific questions and rate design elements

Remote research

An incredibly flexible approach, remote research is often favored due to its time-to-results and cost savings. Remote research can be moderated or unmoderated, and is conducted using UX research tools which record user behavior, feedback, and screen recordings.

Another key benefit is its reach and accessibility—by moving research to a virtual platform, you can access users from anywhere in the world, and ensure research is inclusive of those with different abilities or requirements, who may otherwise be unable to take part in traditional in-person research.

UX research methods for remote research

• Usability testing to evaluate how accessible your product is
• Card sorting to understand how users categorize and group topics
• Concept testing to assess what ideas users are drawn to
• Wireframe or prototype testing to invite users to test a rough version of the design

In-person research

Research conducted in-person is typically more expensive, as it may require travel, accommodation, or equipment. Many traditionally in-person research methods can easily be performed remotely, so in-person research is often reserved for if there’s additional needs for accessibility, or if your product requires physical testing, safety considerations or supervision while being tested.

UX research methods for in-person research

• Guerrilla research to speak to random users and gather feedback
• User interviews to connect with users and read body language
• Field studies to gauge how your product fits into a real world environment

Generative research

Generative research provides a deep understanding of your target audience’s motivations, challenges, and behaviors. Broadly speaking, it pinpoints a problem statement, identifies the problem to be solved, and collects enough data to move forward.

It should happen before you even begin designing, as it helps you identify what to build, the types of problems your user is facing, and how you can solve them with your product or service.

UX research methods for generative research

• Field studies to get familiar with users in their authentic environment
• User interviews to ask open-ended questions about pain points
• Diary research to keep a log of users’ behaviors, activities, and beliefs over time
• Open card sorting to have users define and name their own categories

Evaluative research

Evaluative research focuses on evaluating a product or concept in order to collect data that will improve the solution. Evaluative research usually happens early on and is used in a continuous, iterative way throughout the design process and following launch. You can use this type of UX research to assess an idea, check navigation, or see if your prototype meets your user’s needs.

UX research methods for evaluative research

• Usability testing to see if your platform is easy and intuitive to use
• A/B testing two versions of a design to see which one works best
• Tree testing to assess if your website’s information architecture (IA) makes sense
• Five-second tests to collect first impressions

Behavioral research

This type of research refers to observation—it’s human nature that sometimes what we say, or what we think we’ll do doesn’t match up to what we actually do in a situation. Behavioral research is about observing how users interact with your product or how they behave in certain situations, without any intervention.

UX research methods for behavioral research

• Observation in labs or real environments to witness behavior in real time
• Tree testing to view which paths users take on a website
• Diary research to see how users interact with your product in real life

Attitudinal research

Attitudinal research is the companion to behavioral research—it’s about what people say, and how they feel. In attitudinal research, you ask users to share their own experiences and opinions; this may be about your product, a concept, or specific design element. With a mix of attitudinal and behavioral research, you can get a broader picture of what your user truly needs.

UX research methods for attitudinal research

• Focus groups to understand users’ perspectives on your product
• User interviews to ask people questions about your product directly
• Surveys to gather insights on user preferences and opinions

Quantitative research

Quantitative and qualitative research methods are two types of research that can be used in unison or separately. Quantitative research comes from data and statistics, and results in numerical data.

It allows you to identify patterns, make predictions, and generalize findings about a target audience or topic. “[At iMSA] We analyze a lot of metrics and specific data like traffic analytics, chatbot feedback, user surveys, user testing, etc. to make decisions,” explains Bertrand. “The convergence of all the data, our user’s needs, governs the choices we make.”

Types of quantitative results you can find through UX research include:

• Time spent on tasks
• Net promoter score (NPS)
• System usability score (SUS)
• Number of clicks taken to complete a task
• Preference percentage on A/B tests

UX research methods for quantitative research

• A/B testing to see which option your users likes best
• Tree testing to get data on which paths users follow on your website
• Usability testing to get a score on system usability
• Heatmaps to spot where users spend most of their session time

Qualitative research

Qualitative research is about understanding the why behind the data. It comes from comments, opinions, and observations—this type of research answers why and how users think or act in a certain way. Qualitative data helps you understand the underlying motivations, thoughts, and attitudes of target users. For this reason, attitudinal research is often qualitative (though not always).

UX research methods for qualitative research

• Interviews to discover your users’ motivations and frustrations
• Open question surveys to learn users’ pain points in their own words
• Focus groups to observe users’ interacting with your product
• Think aloud usability tests to hear commentary behind each user decision

💡 Product tip:

Maze allows you to record your participants' screen, audio, and video with Clips, so you can collect qualitative and quantitative insights simultaneously.

When should you conduct UX research?

The truth is, you should always be researching. When NASA wants to send a new shuttle into space, they don't build a rocket and launch it right away. They develop a design, test it in simulations and lab environments, and iterate between each stage. Only once they’ve run all the foreseeable scenarios do they put a person on the ship. Why should your product be any different?

With an overwhelming 83% of product professionals surveyed in our 2023 Continuous Research Report believing research should happen at all stages, it’s surprising that just 36% run tests after launch. While time and budget can make continuous research a challenge, testing at different stages gives you access to unique insights about your users and how they interact with your product.

That being said, if you can only afford to research a few times throughout the development process , here are some key moments to focus on:

Before developing the product

This is when you need to conduct the most extensive and detailed part of your research. During this phase, you’ll want to conduct generative research to get to know exactly:

• Who your user is
• The types of problems they’re facing (and what kind of product they want to solve them)
• What their expectations on a product or service like yours are
• What they like or dislike about your competitors
• Where they currently go to solve the mentioned problems
• What needs to happen for them to change companies (if they’re using a different product)

You can use a variety of UX research methods like focus groups and surveys to gather insights during this stage.

Remember: This step applies even if your product is already live, if you’re thinking of introducing a new feature. Validate your idea and investigate potential alternatives before you spend time and money developing and designing new functionality.

When you want to validate your decisions

This is the point where you’ll run through a few cycles of researching, building, and iterating, before launching your product. The Maze Product team does this through continuous product discovery, via a dual-track habit:

Conduct research regularly while developing and building your product to see if you’re headed in the right direction. Let the research findings feed your deliverables.

Gather qualitative insights on user sentiment through surveys or focus groups. Test your wireframe or sketches to get quantitative answers in the form of clicks, heatmaps, or SUS. Use card sorting to generate ideas, tree testing to assess IA, or prototype testing to assess the usability of a beta version. The options are endless, so there’s no reason to miss maximizing your research at this stage and gather insights to power product decisions.

To evaluate product accessibility

Your product will be used by a multitude of diverse, unique users. Your research participants should be representative of your real audience, which means including all usage scenarios and user personas. Usability testing is one form of UX research that can be used here to ensure your product works for all its users, regardless of ability or need.

There are many ways to ensure your design is inclusive and accessible , including:

• Testing alt-texts, screen-reading capabilities, and color combinations
• Avoiding screen flashes or sudden pop-ups that may be triggering for certain conditions
• Being intentional in what language and imagery is used

Once your product is live

Research doesn’t end once you push your platform to production. Conduct Live Website Testing to evaluate how well your product is meeting your users' expectations and needs. This type of research invites you to answer the question: did we nail it?

Testing your live website also allows you to see how your users interact with your design in a real environment, so you can identify and solve mistakes fast. Pay close attention to loading times, error messages, and other quantitative data that may indicate bugs. You can also conduct regular sentiment checks by embedding feedback surveys into your product itself, to assess user satisfaction and NPS in a few clicks.

TL;DR: Why, how, and when to conduct UX research

The more you understand your customers, the better you can create products that meet expectations, tailor your strategy to their specific needs, and increase your chances for success. Plus, UX research allows you to create unbiased products that put your customers at the center of your business.

To conduct UX research, you’ll need to mix the stage of your product lifecycle with the right research type and methods. Meaning, while you need to conduct UX research continuously, you should look for different types of insights depending on the development stage you’re at and what your current objective is.

For example, if you want to test your live product, you should conduct a mix of quantitative and qualitative evaluative research. That means you might want to perform:

• Usability tests
• Feedback surveys
• Five-second tests
• Prototype testing

Now we’ve covered the what and why of UX research, let’s get into the how. Continue to the next chapter to learn how to create a UX research strategy that blows your competitors away.

Frequently asked questions

What are some examples of UX research?

Some examples of UX research include:

• A/B testing
• Prototype or wireframe testing
• Card sorting
• User interviews
• Tree testing
• 5-second testing
• Usability testing

What are the basics of UX research?

The basics of UX research are simple: you just need a clear goal in mind and a mix of quantitative and qualitative tests. Then, it's a case of:

• Determining the right testing methods
• Testing on an audience that’s an accurate representation of your real users
• Doing continuous product discovery
• Performing unbiased research to build an unbiased design
• Iterating and building user-centric products

UX research gets easier when you use a product discovery platform like Maze. This tool allows you to run multiple types of product research such as usability, prototype, card sorting, and wireframe tests—and get answers within hours.

Is UX research hard?

UX research isn’t hard, especially when you use an intuitive tool for product discovery—like Maze. Maze allows you to build tests using its multiple available templates. It also lets you bring your own users or recruit from its panel and creates an automated, ready-to-share metrics report. Maze gives you answers to tests within hours so you can improve your UX based on real user feedback fast.

How to nail your UX research strategy

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User Research – The Importance of Hypotheses

It is easy to be tempted to look at the objective of your user research and pump out a solution that fits your best idea of how to achieve those objectives. That’s because experienced professionals can be quite good at that but then again they can also be very bad at it.

It is better to take your objectives and generate some hypothetical situations and then test those hypotheses with your users before turning them into concrete action. This gives you (and hopefully your clients) more confidence in your ideas or it highlights the need for changing those hypotheses because they don’t work in reality.

Let’s say that your objective is to create a network where people can access short (say a chapter) parts of a full text before they decide to buy the text or not. (Rather like Amazon does).

You can create some simple hypotheses around this objective in a few minutes brainstorming .

User-Attitude

We think that people would like to share their favourite clips with others on Facebook and Twitter.

User-Behaviour

We think that people will only share their favourite authors and books. They won’t share things that aren’t important to them.

User-Social Context

We think that people will be more likely to share their favourite authors and books if they are already popular with other users.

Why does this matter?

One of the things about design projects is that when you have a group of intelligent, able and enthusiastic developers, stakeholders , etc. that they all bring their own biases and understanding to the table when determining the objectives for a project. Those objectives may be completely sound but the only way to know this is to test those ideas with your users.

You cannot force a user to meet your objectives. You have to shape your objectives to what a user wants/needs to do with your product.

What happens to our product if our users don’t want to share their reading material with others? What if they feel that Facebook, Twitter, etc. are platforms where they want to share images and videos but not large amounts of text?

If you generate hypotheses for your user-research; you can test them at the relevant stage of research. The benefits include:

• Articulating a hypothesis makes it easy for your team to be sure that you’re testing the right thing.
• Articulating a hypothesis often guides us to a quick solution as to how to test that hypothesis.
• It is easy to communicate the results of your research against these hypotheses. For example:
• We thought people would want to share their favourite authors on social networks and they did.
• We believed that the popularity of an author would relate to their “sharability” but we found that most readers wanted to emphasize their own unique taste and are more likely to share obscure but moving works than those already in the public eye.

Header Image: Author/Copyright holder: Dave. Copyright terms and licence: CC BY-NC-ND 2.0

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All you need to know about UX research

Last updated

21 February 2023

Reviewed by

Jean Kaluza

Are you looking for ways to optimize your product, service, or software to better reach and resonate with your audience?

The first step to successful UX research is to discover what UX research is, its process, and how you can leverage it in your business.

Read on to discover everything you need to know, including:

What UX research is

Why UX research is important

The five steps of UX research

Don't let UX problems go unnoticed

Use Dovetail to analyze all your customer interviews and uncover hidden UX issues that are costing your business every day.

• What is UX research?

User experience (UX) research involves gathering valuable insights into how your consumers use your product, service, or software and learning more about your target users to better meet their needs and preferences. Depending on your focus area, UX research serves different purposes in the user-centered design process.

Uncovering what your end users want and need will inform your product team's decisions on product ideas, prototypes , and changes in current designs. In marketing, these targeted user insights from your user researchers can help to customize brand designs and create messaging for the right target audience.

• Why is UX research important to businesses?

There was a time when products and services sold themselves. If it was decent, people bought it. Today, however, customers want more. They want product experiences and brand interactions to be customized. There is also far more competition in most industries than ever before.

Here are some examples of the importance of UX research to your business's success.

Bring more value to your customers

Your customers are the reason for your company's existence. If they didn't need what you're offering, there'd be no reason for you to offer it. UX research goes beyond the basics of what your product/service provides and focuses on improving customer satisfaction and customer experience.

In turn, your customer gets more value out of what you've launched—a smoother experience, more tools and resources, additional features, and more—while you boost customer retention and gain an advantage over the competition by going above and beyond to fulfill your customer's needs.

Take the bias out of your user-centered design process

Believe it or not, quite a few companies still think they know what the end user wants more than the end users themselves. This kind of thinking can be limiting because it's often wrong. The UX design process can offer a solution so long as it’s focused on real users.

UX researchers take the bias out of the process to ensure the user is at the center of brand and product decisions since your customers are the ones buying your products—not you.

Increase your odds of success by making more informed decisions

When heading into a product launch, brainstorming ideas, or reevaluating your product, the most daunting question is: Will people buy it? The odds of succeeding when you launch your product or reconstruct a current one skyrocket if your decisions are based on consumer data and human insights.

This is because you're not making decisions derived from “gut feelings” and guesswork. You’re using cold, hard facts that come straight from the users themselves via techniques such as:

Observational studies

Contextual interviews

User feedback

Online surveys

Usability testing

• What is the return on investment (ROI) for UX research?

The significant time, effort, skill, and expertise your UX researcher needs to conduct their work effectively may make you wonder whether the process is worth the cost and effort. However, research suggests it's a necessary part of product success.

Baymard Institute reveals some telling statistics in its report:

When done right, a flawless UX design can potentially produce 400% higher conversion rates

The average ROI of UX research is 9,900% or $100 back for every $1 spent

Studies show that data-driven companies often outperform their counterparts by 228% or more

By redesigning its site with a more UX focus, Staples was able to increase its eCommerce revenue by 500%

The important takeaway here is that your users’ experience is vital to your success. Despite the complexities of user research , it is essential to every part of your business and development process because it puts the customer at the center of everything you do.

If you don’t focus on your users in this way, you risk your “solution” missing the mark as far as your prospective users' needs and wants are concerned. Misses like this can be due to building products on guesses or assumptions that internal stakeholders believe to be true without any validation. The result is unhappy users, falling retention rates, and costly designs and builds, resulting in negative impacts on ROI.

• User experience research methods

According to the Nielsen Norman Group , the methods you use to conduct UX research depend on what stage of the design cycle you're in.

Stage 1: Discover

During this stage, researchers conduct methods such as:

Field studies

User interviews

Diary studies.

Interviews with stakeholders (discuss designs with stakeholders)

Requirements and constraints

Sales and support interviews

Support call monitoring

Competitive testing

Stage 2: Explore

Researchers use different methods to explore the problems at hand more deeply. They use methods such as:

Competitive analysis

Design review

Task analysis

Persona building

Journey mapping

Design diversity exploration

Cognitive walkthroughs

Prototype feedback and testing

Writing user stories

Card sorting

Stage 3: test.

The most common testing methods are:

Qualitative usability testing

Accessibility evaluation

Benchmark testing

Training research

Social media monitoring

Forum post analysis

User group outreach

Help documentation

Stage 4: Listen

Some excellent methods of listening to your users are:

Search-log analysis

FAQ reviews

Feedback reviews

Analytics reviews

Usability error reviews

Conference outreach

Q&A talks and demos

All these methods can be categorized into several UX research methods, which fall under one or more of the following terms.

Attitudinal vs. behavioral

Consumer insights and data are either attitudinal or behavioral. Attitudinal research refers to the data end users report to you when questioned about their opinions. This is the information you obtain through surveys, focus groups, card sorts, etc.

Behavioral research is the data your researchers collect through observing participants. Examples of observation methods include usability studies, A/B testing, and eye-tracking.

Qualitative vs. quantitative

Qualitative research methods strive to better understand end users through words and meanings. Quantitative methods draw insights from numbers and statistics.

Their purpose, methods, and sampling are very different.

The purpose of qualitative methods is to understand a phenomenon better, while quantitative methods aim to identify relationships and describe a phenomenon. Qualitative sampling is more intentional and on a smaller scale, whereas quantitative sampling is random and larger scale.

Qualitative methods include case studies, clinical research, and ethnography (studies of cultural contexts); in other words, data you draw from interviews, focus groups, and field observation. On the other hand, quantitative methods consist of quasi-experimental, experimental, and comparative techniques drawn from conducting surveys, tests, and questionnaires.

Generative vs. evaluative

Another important distinction when studying user experience is generative versus evaluative.

Generative research refers to the methods your team implements in the Discover and Explore stages of the Nielsen Norman Group design cycle. It seeks to uncover a deeper understanding of your users to identify opportunities for more valuable solutions.

On the other hand, evaluative research analyzes potential usability issues to validate that your product is aligned with real users who will benefit from it. You would conduct this type of research in the Test and Listen stages of the Nielsen Norman example.

• Qualitative UX research methods with examples

Qualitative UX research is often much more complex than the straightforward structure of quantitative data that requires numerical data points and statistical analysis. Although both are very important pieces of the puzzle, qualitative goes beyond the numbers to interpret what that data means. As a result, data analysis and user participation often take longer and require a wide range of language skills to conduct effectively.

Here are some examples of a user research method you can employ to gather qualitative insights.

Participatory design

One way to approach your UX research is by getting advice from people who use and work on your products, bringing them into the early stages of your design process. The participatory design method involves stakeholders—end users, partners, the design team, the development team, product managers, and more in the design decisions to ensure the final product is user-centered.

It's excellent for user testing and usability research methods and often leads to higher customer satisfaction ratings. It also works to bring your team together around a table to work on a shared problem and democratically decide on a solution. While it often involves a higher time investment upfront, it can result in a more fluid approach and greater efficiency throughout the project.

Card sorts are another popular UX research method. Through the use of mental models, they help you discover how users would organize your product. It’s often used in information architecture (IA) design. Here's how it works:

On index cards or Post-it notes, researchers write topics their product (e.g. a website) will have.

Participants organize these topics into groups that they define.

After grouping topics, participants will write a name for each group.

In an optional step, researchers may debrief participants with observations on the difficulty of placing topics in groups, overlapping topics, and thoughts on topics that weren't included in the card sort.

Diary studies are a qualitative research method that requires users to record their thoughts, experiences, and daily activities in a journal. How long a user keeps this record will depend on the head design researcher, but it can range from a few days to a few weeks.

Researchers evaluate and collect information from these diary studies to better understand user behavior and inform the ideal user journey. This method can be excellent for understanding user habits, journeys, attitudes, feelings, and the context of using your product (when, where, why, and how).

Diary study templates

• Types of user research tools

If you were to explore a UX research team's arsenal of tools, you would find dozens of ways to gather and interpret data. The tools used by one research team aren't always the same as those used by another team.

The differences can be due to several factors like preferences, budget, purpose, product types, design scope, and more. 

Surveys or questionnaires

There are tools available to help you create surveys and questionnaires, which make the process more informed and efficient in terms of time and cost. Depending on your needs, you can also toggle with different levels of complexity.

User groups or focus groups

User groups and focus groups bring together a larger team of people to capture insights from all of them at once.

Your team will need tools to help participants schedule a time and pick a place. You'll also need tools for the actual interview process (keeping participants on track) and the observations that follow.

Documenting, analyzing, and sharing

You can gather all the data in the world about your target market, but it's useless if you can't pull actionable insights from it.

This is where tools that allow you to store, analyze, and share data become crucial. Dovetail can help you manage, analyze, and share your user and product research. Collect and organize all your data in one place and action everything from transcribing and evaluating interviews to recording and organizing user insights.

User interview tools help you manage different stages of your user interview process, such as:

Recruitment

Offering incentives

Live user testing

Collaborative insights

With more robust apps, you'll find interview tools already integrated into your centralized research platform.

• The five stages of conducting UX research

There are five basic stages to good user research. Let’s take a look.

Stage 1: Objectives

The first stage of conducting good UX research is defining and detailing your research objectives. Well-thought-out, defined goals lead to significantly more success than poorly defined ones. Clear objectives also allow researchers to focus their research on a common goal: reducing usability issues, identifying user needs, etc.

This process will include the Who, What, When, Where, Why, and How questions of your design process and research.

Stage 2: Hypothesis

The next stage of good research is framing your hypothesis, that is, making assumptions about user behaviors or potential solutions based on what you know about your end users (or think you know about them). This stage is structured to help you determine the best methods for moving forward with your research.

Stage 3: Methods

By the third stage of UX research, your research team has defined goals and made some hypotheses about the results. Now it's time to use that information to determine the best research methods for achieving your goal(s). There are dozens to choose from, so you'll need to consider important factors when selecting the ones you’ll use.

Consider asking yourself some of the following questions about each UX research method you’re considering:

Are you trying to define the phenomenon or explain why it’s happening?

Does it align with your goals?

Will it get you the desired results in your set time frame?

Is it a method researchers would typically use for this type of research?

Is it compatible with your dataset?

Is it appropriate for your ideal users/participants?

If you can answer yes to all these questions, the method may be the right choice. It will take significantly more thorough discussions before finalizing your approach, but this is a good starting point.

Stage 4: Process

You’ve decided on your UX research methods, so now it's time to put them to work. The next step is to source and gather the right participants. Make sure they're representative of your ideal end users. Otherwise, you risk getting inaccurate results from inadequate or irrelevant data.

Whether you’re interviewing, creating surveys, card sorting, or observing (or all these), this stage of your research requires capturing the results. Doing so may take specific skills depending on the method. For example, in qualitative sessions, psychological tricks like remaining silent so that your participant will want to speak or whether to use open or closed questions for certain survey questions.

The most successful research produces a wide range of content and material from which to collect insights, such as videos, notes, images, and more.

Stage 5: Synthesis

In the final stage of your UX research, you’ll gather all your results and make sense of what you've learned. First and foremost, does it prove or disprove your hypothesis? What insights can you take from your research to better accommodate the people who use your products?

The work of a UX researcher never ends, as human behavior is constantly changing. It is up to UX researchers to keep conducting studies and interpreting the results to better understand customer needs and expectations. This approach ensures that solutions will always bring the most value possible to your customers.

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One of the reasons why user experience research came to light is its usefulness and importance in the designing process. It helps the UX team properly create a design for products or services based on validated user feedback, user needs, and experiences. Though an extensive procedure, usability research can greatly reduce the cost of delivering a successful product.

Why is UX Research Important?

To create relevant and useful design

Always remember this: An irrelevant design will never be successful. The logic behind this is simple. For the product to become successful, it needs to be useful and relevant to your users. The only way to achieve this is to empathize with your users and user experience research is a great way to do that.

Common methods of gaining user feedback are conducting interviews and observing people while using your product or application. Let us take for example, the Korean global brand Samsung who spent time going through households to survey and observe how they live and use their home TVs . Surprisingly for them, it has gained them important information that most TV brands have not thought of— that users prefer a sleek, minimalist look that can go well with their furniture. So rather than showing off all the TV’s features, Samsung designed their TVs based on this observation.

To create easy-to-use design

Just what Steve Jobs said, “if the user is having a problem, then it’s our problem.” To be commercially successful, a product should have a high level of usability. This can be achieved by conducting usability testing. Gone are the days when only experts could use the technology available since it is a requirement to get knowledge and even diploma to operate these tools.  But now, people expect something that is easy to learn and use, even for a normal person. Utilizing the technology these days are made to achieve something for the end user, which also implies less burden for them on how to use the product. Thus, good user experience should be achieved in creating an easy-to-use product.

Hindawi published a review study on mobile user interface design patterns . They discussed how mobile designing has changed over time, noting that early stages of the investigation on mobile was more about engineering approach, which includes prototyping, new techniques proposals, and also new interaction styles.

However, since 2010, this has shifted more to usability evaluation of design patterns and usability studies. The study reveals something we need to always remember today: when developing a product, it is important that you also take time to survey the market because as an expert on the product you are developing as it is hard to assume that you know which things are understandable and not to the user unless you participate in conducting your own usability testing.

To better understand the return of investment (ROI) of UX design

A lot of people in the user research industry have failed to see the importance of this. Reality is, in the UX niche, it is still a challenge to fight for the available resources that enable UX researchers and UX designers to properly do their work. This is because user research and design are not really tangible compared to other sections in product development like software development for example. If you have a budget in product design and you need to cut in software development, you can immediately see the consequences that came in the budget cut. This is a different story for UX design as you can only see the consequences once the product reaches your market.

Thus, it is important to conduct studies showing the ROI on UX efforts. If you can see more sales, more customers, and more user feedback on good customer experience after making some changes in the design, then you can also see why you should invest in UX.    

We can take Amazon as an example of investing well in customer experience and how this has made them one of the largest retailers online . The company has invested on customer experience ever since and has continually measure their usability. Their focus is investing long term on customer experience rather than on profit. Because of their continuous UX efforts on customer experience , Amazon remains to be the largest internet retailer since 2015.

What is the Process of UX Research?

There are so many ways to conduct UX design research. However, if you are a beginner, it is best to start with the simplest model. In this case, we take Erin Sanders’ process on UX research . Sanders is a senior interaction designer at Frog, who created a design method called the “research learning spiral”, which have 5 distinct steps:

What we like about Sanders’ UX research method is it’s replicable and can fit into any part of the designing process. The whole “spiral process” is based on learning and need-finding, which helps designers answer questions and at the same time overcome obstacles when it comes to understanding which direction to take when designing a product.

The first three steps are about formulating and answering questions, so that you know what you need to learn during your fact-finding investigation:

1. Objectives: The questions you are trying to answer

You can take the “5Ws and an H” structure when it comes to framing your questions. These are:

• Who? Are questions that refer to your target audience
• What? Are questions that refer to what people are doing and also what they are using in your website, product, or application
• When? Are questions that determine the time when people use the product or technology. This can also include the daily routines that also need to be included
• Where? Are questions that determine the context of use- physical locations that tell where people use the product or technology. This may also include location on the Internet where users may want to access
• Why? Are questions that help explain the behavior or the underlying emotional and rational drivers to what they are doing and why they are doing it
• How? Are questions that go into detail on what actions or steps are taken by users in order to perform a task or reach a goal

Sit down with your design team and discuss the possible queries that may help identify the gaps in knowledge that you and your team need to fill in to create a successful product design.

2. Hypothesis: What we believe we already know

You can’t just execute your ideas without testing it first. This is where the importance of hypotheses come in. Having a list of hypotheses helps us become aware and also minimize biases from the client or the UX team. Being aware of one’s hypotheses also helps us select the right methods to use for our objectives.

Most of all, hypotheses can prove or disprove one’s merit and also helps communicate better the discoveries learned during the entire procedure (e.g. “We believed that [insert hypothesis], but we discovered that [insert finding from research].”)

3. Methods: How we plan to fill the gaps in our knowledge

Once you are one with your key goals and what kind of data to collect to get the answers from your list of queries, you can then lay out the methods that will be used to achieve your objectives.

There are so many methods to consider and all these will be discussed in the next section below. 

Once you are done with your objectives and hypotheses, you can now start with the gathering of data needed to get the right knowledge for your design research. The steps to be taken here are the last two steps in Sander’s process:

4. Conduct: Gather data through the selected methods

In this step, it is important that you participate and facilitate the probing and investigation sessions, properly capturing and analyzing the notes, photos, videos, and other materials that you need to collect. Also, do not base on your notes alone. It is also important that you think out of the box and tweak something as you go.

Just ask yourself this: Am I discovering what I need to learn or am I just gathering information that I already know? The whole point of gathering data is to discover and learn new things to achieve your objectives. If this is not met, then you need to sit down and change things to be able to get the new knowledge that you are looking for.      

5. Synthesis: Answer research inquiries and prove/disprove hypotheses

This stage requires you to find the meaning behind your gathered data. In order to answer the queries that you have in your objectives, you need to know the “what” and the “why” behind the data you have just collected. This can be a challenging step, so taking time in analyzing the data can help you construct with the proper synthesis. 

This stage also requires you to properly gather concise, actionable findings, and then revise the wireframes in order to get the needed changes, based from the data gathered.

Proper and clear synthesis will help your team become more confident in the solutions to take.

What are Useful UX Research Methods?

Now that you have completed your key research goals, have gathered the data needed to answer your inquiries, and all other considerations, you can then proceed to the right methods that will help you complete your goals. You can check out the list of common UX research methods below:

• Usability tests -  set of methods asking users to go through common tasks within a system or prototype and then share the whole participation after. The user may need to answer several follow-up questions from the researcher
• UX interviews - entails a conversation between the researcher and the participant. Generally, the researcher digs deep into the topic to get better answers and insights from the participant
• Focus groups - is similar to UX interviews but this consists of multiple participants and one researcher
• Surveys - consists of a series of queries that usually helps gather any type of attitudinal behavior
• Diary study - is a longitudinal method, asking participants to document their activities, interactions, and attitudes over a period of time
• Card sorts - card sorting is a process that helps see how people group and categorize information like for example, a researcher can provide categories and let the users sort and group the elements on their own
• Tree tests - just the opposite of card sorts, where the participants are provided with a proposed structure and ask them to find individual elements within the structure
• A/B testing - is a process of providing different solutions to the audiences to measure their actions to see which is better in meeting the goals 

More to add to the above methods, you can check out Nielsen Norman Group UX research cheat sheet, listing the different methods and activities that a UX expert can do to produce data and insights .

You can refer to the chart below to see all the available UX methods that you can apply in various usability designing projects:

UX Research Tools

When it comes to UXR tools , there is fairly a good amount of information out there. And since UX research has become so essential in business, it can be a challenge in choosing the right tool for your investigation.

Thus, our team at Userpeek has come up with a comprehensive list of UXR tools that we also categorized into different areas of UX study. However, some of these tools may also overlap in different areas. We want the list to be more “friendly” for you so you can easily check which UXR tools are right for your needs. 

UX Templates

• XMind (for mind mapping)
• Mini Heuristic
• Empathy Map
• Empathy Template
• Persona Template (from UX Lady)
• Customer Journey
• Experience Map Template
• Experience Maps
• Storyboard Template

Research Platforms/Databases

• Optimal Workshop  

Participant Recruiting

• TestingTime
• Prototyping
• Framer  

Synthesis & Sharing

• affinity diagrams
• Mural.co  
• Usability Testing
• Spreadsheet

Note taking & Transcription

• GoTranscript
• Temi  
• QuestionPro
• Sample Screener
• Survey Template

Analysis (of Behavior)

• Apptentive     
• UseResponse
• Bugsee (mobile)
• SmartLook (mobile)
• Lookback.io (mobile)

Remote usability testing/interviewing

• Lookback   
• Google Hangouts
• UserTesting.com
• UsabilityHub

What is the Role of a UX Researcher?

Based on the above discussion on UX product design, we somehow can already tell what a UX researcher is and what it does. Since the purpose of user research is to collect and analyze human insights to be able to properly design a product for humans, the UX expert’s role is to provide concrete and tested answers to the queries concerning product design.

A UX expert facilities the whole design stages with a goal to reveal what the consumers need from the product. Its fundamental role is to assist the entire UX design team in understanding the consumers, ensuring that the product design is fun, intuitive, easily accessible, and user-friendly among many other factors. Some of the responsibilities of a UX expert includes:

• Collaboration with other team members that are involved in the product design. The user researcher works closely with the product developers, product managers, designers, and other departments in the product design in order to properly direct its teammates in practicing the best consumer probing approach.
• Responsible for conducting the fact-finding process. As a researcher, its responsibility is to oversee the planning and conducting of consumer study, making sure that these are properly done in all stages of the product designing process—from conceptualization, prototyping, and all the way to usability testing of the product.
• Responsible for educating the UX team (and other departments) of what needs to be done. It acts as a specialist in the research field, with the responsibility to educate its teammates by properly documenting and applying actionable product research findings and delivering these to all departments.
• Has a strong sense of the product strengths and weaknesses. A UX expert is expected to know the product’s competitive edge to make a sale. For this reason, the researcher becomes an advocate of the product’s value and can clearly point out the things that need improvement.
• Responsible for applying which research design approach to take. The UX researcher should also know how to conduct quantitative and qualitative research approaches to be applied across product design departments.
• UX JobsBoard
• Just UX Jobs
• User Experience Professionals Association
• AIGA Design Jobs

How To Become a UX Researcher?

If you are  interested in becoming a UX researcher , it is important to have a strong background in the fields of marketing, cognitive science, psychology, economics, and behavioral science.

You must also have an analytical mind to read data and also acquire soft skills on reading people. On top of this, a UX researcher should also know how to work with different types of people as the job also entails working closely with different departments in the design process.

Userpeek team listed down the following qualifications required of a UX expert:

• Academic degree: Should have a degree in any or similar fields in Business, Marketing, Economics, Computer Science, Psychology, and Behavioral Science. If you do not have a degree in any of the (or similar) fields above, an equivalent work experience may also be acceptable.
• Work experience for at least 2 years: Should have at least 2-year job in statistical, qualitative, and quantitative analysis, product usability, experimental design, and similar jobs. The candidate should also have knowledge in using certain UX research tools.     
• Good communication skills: a usability expert deals with complex research concepts that the candidate should acquire the talent to explain this clearly to everyone involved in the designing process. The candidate should have good communication skills in both verbal and written form.
• A good problem solver: Since its job is to formulate good, actionable solutions, the candidate should be an effective problem solver and also be able to come up with creative solutions for each problem.
• Knowledgeable in using the needed software: This includes tools like Sketch, InDesign, Illustrator, Keynote and Photoshop, which are all important in delivering clear and engaging presentations for everyone involved in the product development and design. 

UX Research Design Courses Available

If you want to start a job in the UX design and research, now is the time to build your career. There is a wealth of information available out there for UX researchers and most of these are really high-quality materials that you can use for your career foundation. 

With that said, you can get started with our handpicked UX courses and materials below:

UXR online courses

• Nielsen Norman Group list of UX research courses      
• UX research courses in Coursera
• Udemy courses on UX research
• The UX Careers Handbook by Cory Lebson     
• The User Experience Team of One
• Research and Design Survival Guide by Leah Buley      
• Observing the User Experience
• Practitioner's Guide to User
• Research by Elizabeth Goodman
• Tomer Sharon: What is User Research?

• Putting Users in UX: Research Methods for Strategy

• Building a User Research Practice in the Home Office (Katy Arnold at Home Office)

The UX field is multidisciplinary with no one path or specified guideline in becoming a researcher in UX. Because of this reason, a lot are intimidated in becoming a UX professional. This comprehensive guide for user research can be your solid foundation in starting your UX career. 

However, you should also know this guide, along with reading or taking a course in UX are not enough to learn UX. Still the best way to acquire and become better at user design experience specialist is to hone your knowledge and skills by experience. Becoming a usability researcher is a continuous learning and effort. Most of all, this is a career that requires a leap of faith. We promise it will be fun! 😊

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Mary Ann Dalangin

About the author

A content marketing strategist and a UX writer with years of experience in the digital marketing industry.

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Stop guessing, start knowing. Today.

Hypothesis Testing in the User Experience

It’s something we all have completed and if you have kids might see each year at the school science fair.

• Does an expensive baseball travel farther than a cheaper one?
• Which melts an ice block quicker, salt water or tap water?
• Does changing the amount of vinegar affect the color when dying Easter eggs?

While the science project might be relegated to the halls of elementary schools or your fading childhood memory, it provides an important lesson for improving the user experience.

The science project provides us with a template for designing a better user experience. Form a clear hypothesis, identify metrics, and collect data to see if there is evidence to refute or confirm it. Hypothesis testing is at the heart of modern statistical thinking and a core part of the Lean methodology .

Instead of approaching design decisions with pure instinct and arguments in conference rooms, form a testable statement, invite users, define metrics, collect data and draw a conclusion.

• Does requiring the user to double enter an email result result in more valid email addresses?
• Will labels on the top of form fields or the left of form fields reduce the time to complete the form?
• Does requiring the last four digits of your Social Security Number improve application rates over asking for a full SSN?
• Do users have more trust in the website if we include the McAfee security symbol or the Verisign symbol ?
• Do more users make purchases if the checkout button is blue or red?
• Does a single long form generate higher form submissions than the division of the form on three smaller pages?
• Will users find items faster using mega menu navigation or standard drop-down navigation?
• Does the number of monthly invoices a small business sends affect which payment solution they prefer?
• Do mobile users prefer to download an app to shop for furniture or use the website?

Each of the above questions is both testable and represents real examples. It’s best to have as specific a hypothesis as possible and isolate the variable of interest. Many of these hypotheses can be tested with a simple A/B test , unmoderated usability test , survey or some combination of them all .

Even before you collect any data, there is an immediate benefit gained from forming hypotheses. It forces you and your team to think through the assumptions in your designs and business decisions. For example, many registration systems require users to enter their email address twice. If an email address is wrong, in many cases a company has no communication with a prospective customer.

Requiring two email fields would presumably reduce the number of mistyped email addresses. But just like legislation can have unintended consequences, so do rules in the user interface. Do users just copy and paste their email thus negating the double fields? If you then disable the pasting of email addresses into the field, does this lead to more form abandonment and less overall customers?

With a clear hypothesis to test, the next step involves identifying metrics that help quantify the experience . Like most tests, you can use a simple binary metric (yes/no, pass/fail, convert/didn’t convert). For example, you could collect how many users registered using the double email vs. the single email form, how many submitted using the last four numbers of their SSN vs. the full SSN, and how many found an item with the mega menu vs. the standard menu.

Binary metrics are simple, but they usually can’t fully describe the experience. This is why we routinely collect multiple metrics, both performance and attitudinal. You can measure the time it takes users to submit alternate versions of the forms, or the time it takes to find items using different menus. Rating scales and forced ranking questions are good ways of measuring preferences for downloading apps or choosing a payment solution.

With a clear research hypothesis and some appropriate metrics, the next steps involve collecting data from the right users and analyzing the data statistically to test the hypothesis. Technically we rework our research hypothesis into what’s called the Null Hypothesis, then look for evidence against the Null Hypothesis, usually in the form of the p-value . This is of course a much larger topic we cover in Quantifying the User Experience .

While the process of subjecting data to statistical analysis intimidates many designers and researchers (recalling those school memories again), remember that the hardest and most important part is working with a good testable hypothesis. It takes practice to convert fuzzy business questions into testable hypotheses. Once you’ve got that down, the rest is mechanics that we can help with.

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World Leaders in Research-Based User Experience

The discovery phase in ux projects.

March 15, 2020 2020-03-15

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In This Article:

Introduction, when is a discovery needed, common activities in discoveries, people involved, the outcome of a discovery.

Discovery: A preliminary phase in the UX-design process that involves researching the problem space, framing the problem(s) to be solved, and gathering enough evidence and initial direction on what to do next. Discoveries do not involve testing hypotheses or solutions.

Discoveries are crucial to setting design projects off in the right direction by focusing on the right problems and, consequently, building the right thing. They are often referred to as ‘product discoveries’ (although I’m not keen on this name because it can set the expectation that this phase is about discovering requirements for a given product).

In order to be effective, a discovery should be broad and technology- or solution-agnostic. When teams carry out a discovery on a product they have already decided to build, it no longer is a discovery, but, instead, it becomes a requirements-gathering exercise or a validation exercise where teams seek to confirm that their solution is the best. The discovery is off track when teams are asked “How do we make [insert name of solution] work for users?” or told to “Go find out what the user needs are for [insert name of solution] ”.

A discovery should start with a broad objective such as like: “Go find out about this problem, just how big it is, and what the opportunities might be.”

Well-done discoveries ensure that any solutions proposed later are desirable to users, viable for the organization, and feasible with the technology made available.

A discovery should result in the following:

• Understanding of users: Through user research, the project team achieves an understanding of who the users are and how they are affected by a particular problem, as well as what they need, desire, and value from a solution (and why).
• Understanding of the problems to be solved and of the opportunities: Through investigative work, the team understands how and why the problem(s) occur, what effect the problem has on users, as well as on the organization. It understands the magnitude of the problem and opportunities for the organization, product, or service.
• Shared vision: During discovery, the team works with stakeholders to understand overarching business objectives and desired outcomes and get answers to questions such as ‘what do we want to achieve?’, or ‘what does success look like?’. This approach, in turn, focuses the team on the problems (and later the solutions) that will have the greatest impact on that outcome. The team should also have an idea of what to measure going forward, to understand whether the solution is working towards the desired outcome.

A discovery starts broad and requires team members to investigate the context of the problem. The double-diamond diagram introduced by the UK Design Council — and reproduced below — illustrates the high-level process of a discovery: first, the team expands its understanding of the problem by researching its full context; armed with this knowledge, the team agrees on what the problem is, before moving to the next phase of ideating and testing in the Develop stage.

A discovery is needed anytime when there are many unknowns that stop a team from moving forward. Moving forward only on assumptions can be risky, as the team may end up solving a problem that doesn’t really matter — wasting time, money, and effort.

A discovery might also be needed when the team is not aligned in what it wants to achieve .

Discoveries are often carried out differently depending on the type of problem the team needs to investigate. Below are some examples of instigators:

• New-market opportunities . If an organization is looking to explore where to expand its product or service offerings, a discovery is often needed. The discovery might involve researching a new audience, performing competitive reviews, and investigating whether the size of the opportunity warrants entering the market.
• Acquisitions or mergers. When organizations merge, it’s likely that systems, processes, and tools will also need to be consolidated. A discovery could focus on common problems faced by each organization, in order to find a common solution.
• New policy or regulation . This instigator is especially relevant for government organizations or organizations that operate in an environment affected by regularly changing regulation. Such a discovery would involve studying the populations affected by the change, reviewing the regulation to understand it, and assessing how business operations must change to support the new regulation.
• New organization strategy. This driver of change comes internally from the organization (unlike new regulation, which often originates externally). For example, during my time in the UK Government, one government-wide strategy was to become ‘digital by default’, which meant moving away from expensive, paper-based processes to efficient (digital) ones. Discoveries in numerous government departments focused on understanding the needs of their users, as well as the extent of paper-based processing, in order to ensure that a shift to digital was, in fact, efficient and user-centered. Another common strategy is to provide common platforms for those areas of an organization that do essentially the same thing, in order to help the organization become more consistent in what it does, and efficient. Discoveries in these situations would focus on identifying common needs and backstage processes across multiple products and services in order to potentially consolidate them.
• Chronic organizational problems. Perhaps sales have been low this year, or satisfaction has been low for several quarters. Often organizations find themselves simply focusing on symptoms (e.g., adding webchat), rather than on causes. A discovery involves inward- as well as outward-facing research to understand why these problems occur and examination into causes to identify the greatest opportunities for improvement.

There are many different types of activities that could be carried out in a discovery. I won’t cover them all, but here are a few that are performed in most discovery phases.

Exploratory Research

Research helps us learn new things about a domain. This type of research is known as generative or exploratory because it generates new, open-ended insights. By carrying out this research, we learn about the problem space (or the opportunity space). A discovery phase does not involve testing a hypothesis or evaluating a potential solution.

At the beginning of a discovery, the research topic might be extremely broad, whereas later it narrows in on those aspects of the problem space that have the most unknowns or present the greatest opportunities.

Common exploratory-research methods include user interviews , diary studies , and field studies with a representative group of users. Surveys can also be used to gather data from a larger group of users; the data can be triangulated with qualitative insights from other methods. Finally, focus groups can sometimes be used in a discovery (although with this method, the findings are frequently contaminated by groupthink).

Stakeholder Interviews

Stakeholders often hold unique knowledge, insight, and data about internal, backstage processes and about the users who interact with them. Interviewing stakeholders provides an additional layer of insight that helps the team understand the scale of the problem and also the viability of later solutions.

Interviewing key people in the organization can provide you with an understanding of:

• Key business objectives of the organization, individuals, or teams (These are helpful to determine if and how these broader goals tie-in to the goals of the project.)
• Data and insights about how problems affecting users impact backstage work (such as inquiry type and volume, additional processing)
• Solutions they’ve tried before that have or haven’t worked, how they implemented them, what other problems they caused, as well as why they were removed (if applicable)

In addition to interviewing stakeholders, including key stakeholders in the discovery process or having them weigh in throughout not only facilitates further buy-in, it also provides more insights.

Workshops align team members and stakeholders and are a useful tactic for discovery. Some workshops commonly used in discoveries include:

Kickoff workshops, A kickoff workshop occurs at the beginning of the discovery and aims to create alignment on the objective of the discovery, and when it will be complete. It is normally attended by the client or key stakeholders who are invested in the discovery, as well as by the discovery team itself. It can also include agreement on the roles and responsibilities of each team member during the discovery.

Assumption-mapping workshops. Many teams bring in experts and do data gathering activities in a workshop. They question the validity of certain ‘facts’ and identify the deep-rooted assumptions that need further exploration. Part of this workshop can also include prioritizing assumptions in terms of risk to the outcome of the project. The riskiest assumptions should be prioritized in terms of research activities.

Research-question­–generation workshops. This workshop is similar to the assumption-mapping workshop, and the two are often combined; the team discusses what the unknowns are and drafts research questions. The research questions can be prioritized in terms of their importance and how well they will work to gather the knowledge needed to move forward.

Affinity-diagramming workshops. After performing exploratory user research — such as user interviews, contextual inquiry, and diary studies — insights and observations are transferred to sticky notes and the team works to affinity-diagram them to uncover themes around problems, causes, symptoms, and needs.

Service-blueprinting workshops. Using a large map of the overarching service, the team plots insights from user research and business analysis in one place. They use the map to identify gaps that need further research and major opportunities.

Problem-framing workshops. The team defines the problem as a simple statement that will focus the team going forward. It may also compose ideation statements like How-Might-We’s based on that problem statement.

Discoveries are best performed with multidisciplinary teams, where team members are dedicated full-time to the project and are collocated. Depending on the scale of the problem and the discovery activities, the number of people involved and the type of roles they play may vary.

Key roles include:

Someone who can do research : A UX researcher or UX designer needs to plan and carry out user research.

Someone who can facilitate or lead the team : Although self-organizing teams are always best, sometimes team members are new to discovery and may need some direction, or perhaps the team is large and needs some managing. There are many titles that could fill this role, including product manager, project manager, delivery manager, service designer, UX strategist. This role often involves facilitating workshops , ensuring that the team communicates well, and maintaining alignment throughout the discovery process.

A sponsor or owner: Someone from the organization needs to own the project. This person often has a lot of domain and subject-matter expertise, as well as knowledge about who needs to be consulted. The owner should be influential enough to get the discovery team access to other people, teams, or data.

Someone technical: A developer or a technical architect who understands enough technical detail to be able to speak to engineers is needed in order to explore available technologies, their capabilities, and constraints.

In addition to these roles, there could be many others, including business analysts who research business processes, visual designers who explore branding, or interaction designers who work on developing appropriate design principles. It’s best if the team agrees to specific roles and responsibilities at the beginning of the discovery phase.

At the end of the discovery, the team has a detailed understanding of the problem and what outcomes to aim for, as well as where to focus its efforts. They may also have some high-level ideas for solutions that they can take forward and test. In some cases, the end of a discovery might be a decision not to move forward with the project because, for example, there isn’t a user need.

Discovery isn’t about producing outputs for their own sake. However, the following might be produced to help the team organize learnings about the problem space and users:

● A finalized problem statement: a description of the problem backed up with evidence that details how big it is and why it’s important

● A service blueprint

● User-journey maps

● User-needs statements

● High-level concepts or wireframes (for exploring in the next phase)

A discovery is a preliminary phase of a design project. It can be initiated by many different kinds of problems, involve different size teams, and many research or workshop activities. However, all discoveries strive to gain insight into a problem space and achieve consensus on desired outcomes.

UK Design Council’s Double Diamond Model: What is the framework for innovation? Design Council's evolved Double Diamond .

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What if we found ourselves building something that nobody wanted? In that case, what did it matter if we did it on time and on budget? —Eric Ries

Lean User Experience (Lean UX) is a team-based approach to building better products by focusing less on the theoretically ideal design and more on iterative learning, overall user experience, and customer outcomes.

Lean UX design extends the traditional UX role beyond merely executing design elements and anticipating how users might interact with a system. Instead, it encourages a far more comprehensive view of why a Feature exists, the functionality required to implement it, and the benefits it delivers. By getting immediate feedback to understand if the system will meet the fundamental business objectives, Lean UX provides a closed-loop method for defining and measuring value.

Generally, UX represents a user’s perceptions of a system—ease of use, utility, and the user interface’s (UI) effectiveness. UX design focuses on building systems that demonstrate a deep understanding of end users. It considers users’ needs and wants while making allowances for their context and limitations.

When using Agile methods, a common problem is how best to incorporate UX design into a rapid Iteration cycle, resulting in a full-stack implementation of the new functionality. When teams attempt to resolve complex and seemingly subjective user interactions while simultaneously trying to develop incremental deliverables, they can often churn through many designs, creating frustration with Agile.

Fortunately, the Lean UX movement addresses this using Agile development with Lean Startup implementation approaches. The mindset, principles, and practices of SAFe reflect this thinking. This process often begins with the SAFe Lean Startup Cycle described in the Epic article. It continues developing Features and Capabilities using the Lean UX process described here.

As a result, Agile Teams and Agile Release Trains (ARTs) can leverage a common strategy to generate rapid development, fast feedback, and a holistic user experience that delights users.

The Lean UX Process

In Lean UX , Gothelf and Seiden [2] describe a model we have adapted to SAFe, as Figure 1 illustrates.

Benefit Hypothesis

The Lean UX approach starts with a benefit hypothesis: Agile teams and UX designers accept that the right answer is unknowable up-front. Instead, teams apply Agile methods to avoid Big Design Up-front (BDUF), focusing on creating a hypothesis about the feature’s expected business result. Then they implement and test that hypothesis incrementally.

The SAFe Feature and Benefits matrix (FAB) can be used to describe the hypothesis as it moves through the Continuous Exploration aspect of the CDP:

• Feature  – A short phrase giving a name and context
• Benefit hypothesis – The proposed measurable benefit to the end-user or business

Note : Design Thinking practices suggest changing the order of the feature benefit hypothesis elements to identify the customer benefits first and then determine what features might satisfy their needs.

Outcomes are measured in the Release on Demand aspect of the CDP. They are best done using leading indicators (see Innovation Accounting in [1]) to evaluate how well the new feature meets its benefits hypothesis. For example, “We believe the administrator can add a new user in half the time it took before.”

Collaborative Design

Traditionally, UX design has been an area of high specialization. People with a talent for design, a feel for user interaction, and specialty training are often entirely in charge of the design process. The goal was ‘pixel perfect’ early designs, done before the implementation. But this work was often done in silos by specialists that may or may not know the most about the system and its context. Success was measured by how well the implemented user interface complied with the initial UX design. In Lean UX, this changes dramatically:

“Lean UX has no time for heroes. The entire concept of design as a hypothesis immediately dethrones notions of heroism; as a designer, you must expect that many of your ideas will fail in testing. Heroes don’t admit failure. But Lean UX designers embrace it as part of the process.” [2]

Continuous exploration takes the hypothesis and facilitates an ongoing and collaborative process that solicits input from a diverse group of stakeholders – Architects , Customers , Business Owners , Product Owners , and Agile Teams . This group further refines the problem and creates artifacts that clearly express the emerging understanding, including personas, empathy maps, and customer experience maps (see Design Thinking ).

Agile teams are empowered to design and implement collaborative UX, significantly improving business outcomes and time-to-market. Moreover, another important goal is to deliver a consistent user experience across various system elements or channels (for example, mobile, web, kiosk) or even different products from the same company. Enabling this consistency requires balancing decentralized control with centralizing certain reusable design assets (following Principle #9 – Decentralize decision-making ). For example, creating a design system [2] with a set of standards that contains whatever UI elements ARTs and Value Streams find helpful, including:

• Editorial rules, style guides, voice and tone guidelines, naming conventions, standard terms, and abbreviations
• Branding and corporate identity kits, color palettes, usage guidelines for copyrights, logos, trademarks, and other attributions
• UI asset libraries, which include icons and other images, templates, standard layouts, and grids
• UI widgets, which include the design of buttons and other similar elements

These centralized assets are integral to the Architectural Runway , which supports decentralized control while recognizing that some design elements must be centralized. After all, these decisions are infrequent , long-lasting, and provide significant economies of scale across both the user base and enterprise applications, as described in Principle #9.

Building a Minimum Marketable Feature

With a hypothesis and design, teams can implement the functionality as a Minimal Marketable Feature (MMF). The MMF should be the smallest amount of functionality that must be provided for a customer to recognize any value and for the teams to learn whether the benefit hypothesis is valid.

By creating an MMF, the ARTs apply SAFe Principle #4 – Build incrementally with a fast, integrated learning cycle to implement and evaluate the feature. Teams may preserve options with Set-Based Design  as they define the initial MMF.

In many cases, extremely lightweight and not even functional designs can help validate user requirements (ex., paper prototypes, low-fidelity mockups, simulations, API stubs). In other cases, a vertical thread (full stack) of just a portion of an MMF may be necessary to test the architecture and get fast feedback at a System Demo . However, in some instances, the functionality may need to proceed to deployment and release, where application instrumentation and telemetry provide feedback data from production users.

MMFs are evaluated as part of deploying and releasing (where necessary). There are various ways to determine if the feature delivers the proper outcomes. These include:

• Observation – Wherever possible, directly observe the actual usage of the system. It’s an opportunity to understand the user’s context and behaviors.
• User surveys – A simple end-user questionnaire can obtain fast feedback when direct observation isn’t possible.
• Usage analytics – Lean-Agile teams build analytics into their applications, which helps validate initial use and provides the application telemetry needed to support a Continuous Delivery model. Application telemetry offers constant operational and user feedback from the deployed system.
• A/B testing – This is a form of statistical hypothesis comparing two samples, which acknowledges that user preferences are unknowable in advance. Recognizing this is liberating, eliminating endless arguments between designers and developers—who likely won’t use the system. Teams follow Principle #3 – Assume variability; preserve options to keep design options open as long as possible. And wherever it’s practical and economically feasible, they should implement multiple alternatives for critical user activities. Then they can test those other options with mockups, prototypes, or even full-stack implementations. In this latter case, differing versions may be deployed to multiple subsets of users, perhaps sequenced over time and measured via analytics.

In short, measurable results deliver the knowledge teams need to refactor, adjust, redesign—or even pivot to abandon a feature based solely on objective data and user feedback. Measurement creates a closed-loop Lean UX process that iterates toward a successful outcome, driven by evidence of whether a feature fulfills the hypothesis.

Implementing Lean UX in SAFe

Lean UX differs from the traditional, centralized approach to user experience design. The primary difference is how the hypothesis-driven aspects are evaluated by implementing the code, instrumenting where applicable, and gaining user feedback in a staging or production environment. Implementing new designs is primarily the responsibility of the Agile Teams, working in conjunction with Lean UX experts.

Of course, this shift, like many others with Lean-Agile development, can cause significant changes to the way teams and functions are organized, enabling a continuous flow of value. For more on coordinating and implementing Lean UX —specifically how to integrate Lean UX in the PI cycle—read the advanced topic article Lean UX and the PI Lifecycle .

Last update: 21 February 2023

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What is lean UX and why does it matter? A complete guide

Lean UX is a collaborative, iterative way of designing and building products – but why is it so important?

The State of UX Hiring Report 2024

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In 2013, Jeff Gothelf published a book called Lean UX: Designing Great Products with Agile Teams . In doing so, he introduced a revolutionary approach to the way products are designed and built. 

Since then, lean UX has become quite the buzzword, favoured by startups and agile practitioners. But what does it all mean? 

If you’re looking for a no-nonsense, jargon-free guide to lean UX, look no further. We’ll explain:

• What lean UX is
• The difference between lean UX and traditional UX
• The principles of lean UX
• The lean UX process
• What’s so great about lean UX

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1. What is lean UX?

Lean UX is a collaborative, iterative way of designing and building products. 

It goes hand-in-hand with the agile methodology, which originated in the software industry. The agile methodology breaks a project up into short, rapid cycles in order to get things done quickly, with continuous testing and improvements along the way. Lean UX follows a similar approach, working in a constant loop of thinking, making, and testing. 

The purpose of lean UX is to harness the power of collaboration, to reduce waste (in terms of time, effort and resources), and to experiment and build rapidly in order to get feedback early on. With this feedback, the product can be improved incrementally. 

That’s lean UX in a nutshell. We’ll dive deeper into how lean UX works as we explore the process and principles underlying this increasingly popular approach. 

2. What’s the difference between lean UX and traditional UX?

When following the typical UX design process , designers spend a lot of time understanding their users through user research, figuring out the problem space and defining product requirements before they get to actually designing anything. The focus is on scoping out the project fully and comprehensively enough so that when the product is designed and developed, it has a good shot at meeting the user’s needs and adequately solving their pain-points. 

With lean UX, you’re not looking to get it right (or even close) straight out of the gate. Rather than laying extensive groundwork before you can create something, lean UX has you building a minimum viable product (MVP) quickly and early on. This enables early and continuous feedback so the product can be improved iteratively — with each iteration (or version) bringing you closer to the end goal. This isn’t to say that lean UX does away with user research and testing; they’re just done with a more “quick and dirty” approach. 

It’s often said that lean UX is more collaborative than the traditional UX process. Because lean UX works in short cycles, there’s a constant back and forth between the designers, developers, product managers and other key stakeholders, as opposed to working in silos. Although “classic” UX is still highly collaborative, the sharing and testing of ideas and solutions is not as continuous as it is with lean UX. 

Ultimately, traditional UX favours a more thorough, deliverable and documentation-heavy approach prior to actually designing and building anything, while lean UX puts the emphasis on building early on, getting feedback, making quick decisions and improving along the way.

3. The golden rules and principles of lean UX

Lean UX is based on certain rules and principles. Let’s take a look at some of the most important ones now.

Lean UX requires cross-functional collaboration 

Rather than working in silos (i.e. in isolation), different departments and disciplines work together throughout. With everyone involved at each stage, lean UX helps to ensure a shared understanding of the product, the end users, the problem space and general processes. 

Lean UX prioritises problem-solving and solution-finding

Not dissimilar to traditional UX, lean UX places problem-solving front and centre. The emphasis is not on designing or building features for the sake of an output. Rather, it’s about making sure you’re solving the right problem and empowering everyone to come up with solutions. 

Lean UX seeks to reduce waste

Lean UX encourages you to skip any parts of the process that are time and resource-heavy (like excessive documentation) and to focus instead on creating an MVP (minimum viable product), which you can quickly learn from. The goal is to accelerate progress and, as the name suggests, make the process leaner and more streamlined. 

Lean UX says build early and quickly

As we’ve mentioned, lean UX has you creating an MVP as early as possible. The goal isn’t to create a near-perfect or even great product right away, but rather to build something you can continuously and iteratively improve. 

…and gives you permission to fail

Designing and building in this way encourages experimentation and failure. With lean UX, it’s absolutely fine to get it wrong. You’ll learn soon enough because of the continuous feedback loops – and because you’re building quickly –  you’ll be able to put it right. And, because you haven’t invested too much time and resources in getting it perfect, the fallout of getting it wrong is minimal. 

4. The lean UX process

The lean UX process centres on three key phases: Think , Make  and Check . It’s a cyclical process that keeps repeating, with the product improving each time the cycle begins anew. 

Lean UX phase 1: Think

The process starts with your assumptions about –  and understanding of –  the problem space in question. Assumptions are usually gathered in a workshop or through a group brainstorming session and they basically sum up what you collectively assume or think you know. 

You can gather assumptions about who your users are, what the product you’re designing is used for and when, what the most important functions and features will be and so on. 

Based on your assumptions, you’ll then create a hypothesis (or multiple hypotheses). For example, you might come up with the following hypothesis:

We believe that online shoppers need to be able to place an order without creating a customer account. Providing this option will increase the number of completed orders / reduce the number of “abandoned cart” incidences. We can prove this if we are able to measure an increase in the order completion rate (which currently stands at 15%).

When writing hypotheses, it’s important that you’re able to set a clear and measurable goal for how each hypothesis can be tested. Otherwise, there’s no way to determine if it’s valid or invalid and therefore worthy of pursuing or not.  

Lean UX phase 2: Make

As we know, lean UX is about building early and that’s the focus of the “Make” phase. You’ll now create a minimum viable product (MVP), which is essentially the most basic version you will need in order to test your hypothesis and gather initial learnings and feedback.

The form your MVP takes will depend on your hypothesis and what you want to test. Taking the example of our online shopping hypothesis, the MVP could be an interactive prototype of the proposed new checkout process, featuring the additional option to place an order without having to create an account. 

Otherwise, an MVP might be a very basic wireframe or a website landing page. Anything that can be created quickly and used to test out your hypothesis. 

Lean UX phase 3: Check

With your MVP in place, you have something tangible to test and evaluate. In the “Check” phase, you gather feedback on your MVP in order to invalidate or validate your original hypothesis. You can do this through A/B testing, site analytics and a variety of user and usability testing methods. 

Based on your learnings, you’ll loop back to phase 1 (“Think”) and proceed accordingly. Maybe you need to scrap the initial hypothesis and explore a different problem or perhaps it’s necessary to generate new ideas and angles for the same hypothesis. Either way, you’ll build on the previous cycle and continue to steer the product towards success. 

5. What’s so great about lean UX?

You’ve read this far, so you probably already have a good idea of why lean UX is so popular. 

Compared to traditional UX, lean UX is hailed as a huge time and money saver — and, perhaps most importantly, it keeps designers focused on solving the right user problem at the right time.

With the traditional approach to UX, you might spend months designing a particular feature or solution, investing considerable time and resources along the way, only to find that by the time your designs are developed and tested, requirements have changed. The idea you came up with four months ago is no longer relevant or fitting, sending you right back to the drawing board. 

Now imagine how that changes if you take a lean approach. You would build and test your initial idea early on, making sure you’re solving the right problem before you invest any more time and resources. By working in short cycles with continuous testing and feedback, you’re able to adapt to changing requirements in real-time. 

Lean UX is especially popular with startups and teams who don’t have infinite resources at their disposal. So, if you’re a UX designer with aspirations of working in a startup or a company which follows the agile methodology, it’s important to understand what lean UX is and how it works. 

Hopefully this guide has got you off to a good start! If you’d like to dive deeper into lean UX, we can recommend Jeff Gothelf’s book on the topic . 

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21 UX case studies to learn from in 2024

UX case studies are the heart of your design portfolio. They offer a peek into your design process, showcasing how you tackle challenges, your methods, and your results. For recruiters, these case studies serve as a metric for evaluating your skills, problem-solving abilities, and talent.

If you’re considering creating your own UX case study in 2024 but don’t know where to start, you’re in the right place. This article aims to inspire you with 21 carefully hand-picked UX case study examples, each offering valuable lessons.

But before we dive into these examples, let’s address a question that might be lingering: Is a UX case study truly worth the effort?

Is it worth creating a UX case study?

The short answer is yes.

Remember how in math class, showing your workings was even more important than getting the correct answer? UX case studies are like that for designers. They are more than just showcasing the final product (the polished website or app); they detail the steps taken to get there (the research, user testing, and design iterations). By showing your design process, you give potential employers or clients a peek into your thought process and problem-solving skills.

A well-laid-out case study has many benefits, including the following:

Building credibility

As case studies provide evidence of your expertise and past successes, they can build credibility and trust with potential employers or clients.

Educational value

By showing your design process, you provide valuable insights and learnings for other designers and stakeholders.

Differentiation

A compelling case study can leave a lasting impression on potential recruiters and clients, helping you stand out.

Iterative improvement

A case study is like a roadmap of each project, detailing the highs, lows, failures, and successes. This information allows you to identify areas for improvement, learn from mistakes, and refine your approach in subsequent projects.

Now that you know why a stand-out case study is so important, let’s look at 21 examples to help you get creative. The case studies will fall under five categories:

• Language learning app
• Learning app
• Travel agency app
• Intelly healthcare app
• Cox Automotive
• Swiftwash laundry
• Wayfaro trip planner
• New York Times app redesign
• Disney+ app redesign
• Fitbit redesign
• Ryanair app redesign
• Forbes app redesign
• Enhancing virtual teaching with Google Meet
• Airbnb’s global check-in tool
• Spotify home shortcuts
• AI-powered spatial banking for Apple Vision Pro
• Sage Express

In this section, we’ll explore case studies that take us through the complete design journey of creating a digital product from scratch.

1. Language learning app

If you’re a designer looking to get your foot in the door, this is one case study you need to check out. It’s so well detailed that it helped this designer land their first role as a UX designer:

Created by Christina Sa, this case study tackles the all-too-common struggle of learning a new language through a mobile app. It takes us through the process of designing a nontraditional learning app that focuses on building a habit by teaching the Korean language using Korean media such as K-pop, K-drama, and K-webtoon.

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Key takeaway

This case study shows how a structured design process, user-centered approach, and effective communication can help you stand out. The creator meticulously laid out their design process from the exploratory research phase to the final prototype, even detailing how the case study changed their view on the importance of a design process.

If you’re searching for a comprehensive case study that details every step of the design process, look no further. This one is for you:

This impressive case study by Finna Wang explores the creation of a fan-focused responsive platform for Jambb, an already existing social platform. The creator starts by identifying the problem and then defines the project scope before diving into the design process.

This case study shows us the importance of an iterative problem-solving approach. It identifies a problem (pre-problem statement), creates a solution, tests the solution, and then revises the problem statement based on the new findings.

3. Learning app

If you need a highly visual case study that takes you through every step of the design process in an engaging way, this one is for you:

This case study walks us through the design of a platform where users can find experts to explain complex topics to them in a simple and friendly manner. It starts by defining the scope of work, then progresses through research, user journeys, information architecture, user flow, initial design, and user testing, before presenting the final solution.

This case study demonstrates effective ways to keep readers engaged while taking them through the steps of a design process. By incorporating illustrations and data visualization, the designer communicates complex information in an engaging manner, without boring the readers.

If you’re in search of a case study that details the design process but is also visually appealing, you should give this one a look:

This case study by Orbix Studio takes us through the process of designing GiveHub, a fundraising app that helps users set up campaigns for causes they’re passionate about. It starts with an overview of the design process, then moves on to identifying the challenges and proposing solutions, before showing us how the solutions are brought to life.

This case study illustrates how a visually engaging design and clear organization can make your presentation easy to grasp.

5. Travel agency app

This case study is quite popular on Behance, and it’s easy to see why:

The case study takes us through the process of creating a travel app that lets users compare travel packages from various travel agencies or groups. The creators set out a clear problem statement, propose a solution, and then show us the step-by-step implementation process. The incorporation of data visualization tools makes this case study easy to digest.

This is another case study that shows the importance of using a clearly defined design process. Going by its popularity on Behance, you can tell that the step-by-step process breakdown was well worth the effort.

6. Intelly healthcare app

If you’re looking for a UX case study that explores the design journey for both mobile and desktop versions of an app, this is one you should check out:

This case study explores the process of creating Intelly, an app that transforms patient care with telemedicine, prescription management, and real-time tracking. The case study begins with a clear design goal, followed by a layout of existing problems and design opportunities. The final design is a mobile app for patients and a desktop app for doctors.

This case study highlights the importance of proactive problem-solving and creative thinking in the design process. The creators laid out some key problems, identified design opportunities in them, and effectively leveraged them to create an app.

7. Cox Automotive

If you prefer a results-oriented case study, you’ll love this one:

This case study delves into how Cox Automotive’s Manheim division, used LogRocket to optimize their customers’ digital experience for remote car auctions. It starts by highlighting the three key outcomes before giving us an executive summary of the case study. The rest of the case study takes us through the process of achieving the highlighted outcomes.

A key takeaway from this case study is the significance of using user data and feedback to enhance the digital experience continuously. Cox Automotive used LogRocket to identify and address user-reported issues, gain insights into customer behaviors, and make data-driven decisions to optimize their product.

These case studies are more focused on the visual aspects of the design process, teaching us a thing or two about presentation and delivery.

If you love a case study that scores high on aesthetics with vivid colors, cool illustrations, and fun animations, you need to check this one out:

This case study takes us on a visual journey of creating Rebank, a digital product aimed at revolutionizing the baking industry. It starts with the research process, moves on to branding and style, and then takes us through the different screens, explaining what each one offers.

This case study illustrates the value of thinking outside the box. Breaking away from the conventional design style of financial products makes it a stand-out case study.

9. Swiftwash Laundry

If you’re looking for a case study that prioritizes aesthetics and visual appeal, you should check this one out:

This case study by Orbix Studio gives us a peek into how they created Swiftwash, a laundry service app. It takes us through the steps involved in creating an intuitive, user-friendly, and visually appealing interface.

If there’s one thing to take away from this case study, it’s the value of presenting information in a straightforward manner. Besides being easy on the eye, this case study is also easy to digest. The creators lay out the problem and detail the steps taken to achieve a solution, in an easy-to-follow way, while maintaining a high visual appeal.

10. Wayfaro trip planner

If you’re looking for a concise case study with clean visuals, you should definitely check this one out:

This Behance case study takes us through the design of Wayfaro, a trip planner app that allows users to plan their itineraries for upcoming journeys. The creators dive straight into the visual design process, showing us aspects such as branding and user flow, and explaining the various features on each screen.

This case study shows us the power of an attractive presentation. Not only is the mobile app design visually appealing, but the design process is presented in a sleek and stylish manner.

App redesign

These case studies delve into the redesign of existing apps, offering valuable insights into presentation techniques and problem-solving approaches.

11. New York Times app redesign

If you’re looking for an app redesign case study that’s impactful yet concise, this one is for you:

This study details the creation of “Timely,” a design feature to address issues with the NYT app such as irrelevant content, low usage, and undesirable coverage. It takes us through the process of identifying the problem, understanding audience needs, creating wireframes, and prototyping.

This case study shows us that you don’t always need to overhaul the existing app when redesigning. It suggests a solution that fits into the current information setup, adding custom graphics to the mobile app. Starting with a simple problem statement, it proposes a solution to address the app’s issues without changing what customers already enjoy.

12. Disney+ app redesign

If you’re looking for an engaging case study that’s light on information, you should check out this one:

This case study by Andre Carioca dives right into giving the user interface a little facelift to make it more fun and engaging. By employing compelling storytelling and appealing visuals, the creator crafts a narrative that’s a delight to read.

Given how popular this case study is on Behance, you can tell that the designer did something right. It shows how injecting a little playfulness can elevate your case study and make it more delightful.

13. Fitbit redesign

If you want an in-depth case study that doesn’t bore you to sleep, this one is for you:

This case study by Stacey Wang takes us through the process of redesigning Fitbit, a wearable fitness tracker. The creator starts by understanding personas and what users expect from a fitness tracker.

Next was the development of use cases and personas. Through a series of guerrilla tests, they were able to identify user pain points. The redesign was centered around addressing these pain points.

This case study highlights the importance of clear organization and strong visual communication. The creator goes in-depth into the intricacies of redesigning the Fitbit app, highlighting every step, without boring the readers.

14. Ryanair app redesign

If you’re bored of the usual static case studies and need something more interactive, this app redesign is what you’re looking for:

This case study takes us through the process of giving the Ryanair app a fresh look. Besides the clean aesthetics and straightforward presentation, the incorporation of playful language and interactive elements makes this case study captivating.

This case study shows how adding a bit of interactivity to your presentation can elevate your work.

15. Forbes app redesign

This case study starts by explaining why the redesign was needed and dives deep into analyzing the current app. The creator then takes us through the research and ideation phases and shares their proposed solution. After testing the solution, they made iterations based on the results.

When it comes to redesigning an existing product, it’s a good idea to make a strong case for why the redesign was needed in the first place.

UX research

These case studies are centered around UX research, highlighting key research insights to enhance your design process.

16. Enhancing virtual teaching with Google Meet

This case study by Amanda Rosenburg, Head of User Experience Research, Google Classroom shows us how listening to user feedback can help make our products more useful and inclusive to users.

To improve the virtual teaching experience on Google Meet, the team spent a lot of time getting feedback from teachers. They then incorporated this feedback into the product design, resulting in new functionality like attendance taking, hand raising, waiting rooms, and polls. Not only did these new features improve the user experience for teachers and students, but they also created a better user experience for all Google Meet users.

When there isn’t room for extensive user research and you need to make quick improvements to the user experience, it’s best to go straight to your users for feedback.

17. Airbnb’s global check-in tool

This case study by Vibha Bamba, Design Lead on Airbnb’s Host Success team, shows us how observing user behaviors inspired the creation of a global check-in tool:

By observing interactions between guests and hosts, the Airbnb team discovered a design opportunity. This led to the creation of visual check-in guides for Airbnb guests, which they can access both offline and online.

There’s a lot to be learned from observing user behavior. Don’t limit yourself to insights obtained from periodic research. Instead, observe how people interact with your product in their daily lives. The insights obtained from such observations can help unlock ingenious design opportunities.

18. Spotify Home Shortcuts

This case study by Nhi Ngo, a Senior User Researcher at Spotify shows us the importance of a human perspective in a data-driven world:

When the Spotify team set out to develop and launch the ML-powered Shortcuts feature on the home tab, they hit a brick wall with the naming. A/B tests came back inconclusive. In the end, they had to go with the product designer’s suggestion of giving the feature a name that would create a more human and personal experience for users.

This led to the creation of a humanistic product feature that evoked joy in Spotify’s users and led to the incorporation of more time-based features in the model, making the content more time-sensitive for users.

Although data-driven research is powerful, it doesn’t hold all the answers. So in your quest to uncover answers through research, never lose sight of the all-important human perspective.

Artificial intelligence

The following case studies are centered around the design of AI-powered products.

19. AI-powered spatial banking for Apple Vision Pro

If you want to be wowed by a futuristic case study that merges artificial intelligence with spatial banking, you should check this out:

In this revolutionary case study, UXDA designers offer a sneak peek into the future with a banking experience powered by AI. They unveil their vision of AI-powered spatial banking on the visionOS platform, showcasing its features and their AI use cases.

This case study shows us the importance of pushing boundaries to create innovative experiences that cater to user needs and preferences.

20. Sage Express

If what you need is an AI case study that isn’t information-dense, this one is for you:

This case study by Arounda takes us through the design of Sage Express, an AI-powered data discovery tool that automatically extracts patterns, tendencies, and insights from data. It outlines the challenge, proposes a solution, and details the journey of bringing the proposed solution to life. But it doesn’t stop there: it also shows the actual results of the design using tangible metrics.

This case study underscores the importance of showing your outcomes in tangible form. You’ve worked hard on a project, but what were the actual results?

If you’re looking for a clean and well-structured AI case study, this will be helpful:

This case study takes us through the process of creating Delfi, an AI-driven banking financial report system. It details the entire design process from onboarding to prototype creation.

If there’s one thing to learn from this case study, it’s how a well-structured presentation can simplify complex information. Although the case study is heavy on financial data, the organized layout not only enhances visual appeal but also aids comprehension.

This article has shown you 21 powerful case study examples across various niches, each providing valuable insights into the design process. These case studies demonstrate the importance of showcasing the design journey, not just the final polished product.

When creating your own case study, remember to walk your users through the design process, the challenges you faced, and your solutions. This gives potential recruiters and clients a glimpse of your creativity and problem-solving skills.

And finally, don’t forget to add that human touch. Let your personality shine through and don’t be afraid to inject a little playfulness and storytelling where appropriate. By doing so, you can craft a case study that leaves a lasting impression on your audience.

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