An Introduction to UX Research: A Cheat Sheet

Moe Hachem
Written by Moe Hachem on
An Introduction to UX Research: A Cheat Sheet

It’s been quite some time since I’ve posted anything, so to rekindle my knowledge-sharing flame, I’ll kick off my new efforts with a new post on UX Research. Going forward, I will attempt to publish two posts a month. Here’s to new beginnings.

This is Not a Formula.

I want to highlight that what I’m mentioning here is hardly ground-breaking and is only meant to serve as a cheat sheet to help you (and me) if you’re ever unsure what to do during a research project.

Ideally, you’d research (heh) more about the different parts of the processes since I will not cover the entire spectrum nor the intricate details of the stages of the research process.

Is Research Important?

Short answer: Yes.

User research provides an essential foundation for the design and product strategies. It allows you to create relevant products/designs that are meaningful solutions to real problems users or customers have. It’s hard to solve real problems if you don’t have research to back up your process, and it’s even harder to make sure you’re solving real and pressing issues if you don’t have research to validate that it exists.

Research becomes more imperative in heavily regulated environments such as financial institutions where user research allows you to push the boundaries of the regulatory frameworks to see what is within the realm of possibility and what’s worth pursuing.

Research induces innovation.

Crash Course on the Stages of UX Research

Formulate a hypothesis

When you first start your user research project, you can’t go in guns blazing.

You need to:

  • Identify your research goals
  • Align stakeholders
  • Recognize problems and opportunities
  • Create a hypothesis
  • Relate research goals to larger organizational objectives
  • Define key questions your team needs to answered (e.g. how will introducing X affect conversion rates?)

The keyword here is: Create a hypothesis.

A hypothesis is a statement that can anchor and guide your research and save you the pain of poking around in the dark. The result of your research will allow you to validate or invalidate your hypothesis and help you determine your next course of action.

Identify Resources and Methodologies

When you’ve formulated a hypothesis, it’s time to define what research methods ought to be used based on what resources you have available. Can you rely on previous research? Is there any second-hand research you could use? Can you access previous metrics and analytics? Or do you need to roll up your sleeves and conduct user interviews or shadow them on-site?


When you’ve understood what resources and tools you can use, it’s time to start the discovery process. You want to start talking to (potential) customers to understand their needs. Essentially you want to figure out what they need to put money into your business (i.e. convert). You want to seek and develop a deep understanding of users/customers, the problems they experience, and what they need to help them with their jobs-to-be-done.

Fun Fact: Your product, marketing, development, and customer support teams are not your end-users (unless they are).

When you finish your preliminary research, you’ll want to focus and dig into the information you gathered. You’ll want to map out user/customer journeys and develop personas and user stories to clarify and communicate your findings. These discoveries would then inform the development of wireframes, sketches, and prototypes.

User Test

When you’ve got the wireframes up and running, it’s time to iterate, test and loop back to research if you didn’t get it right the first time (you probably won’t). Your user test might be in a controlled prototype environment or an MVP ready to be tested in the market.

How/where your test takes place will vary depending on your business model, but I won’t go into details in this article.

You might run A/B tests to see which designs users respond to best, measure accessibility, or observe how users will interact with your product. The idea is to build a complete picture of how your UX facilitates or stops users from meeting their needs.

Chances are you’ll loop back to the discovery phase quite a few times before you can call it a day (or week, month, or year).

Document Actionable Insights

The insights you gained through the discovery and testing phases should allow you to validate or invalidate the hypothesis you’ve created at the onset of the research journey. You’ll want to analyze your findings and explain why you arrived at the results you did and how you can translate them into actionable insights. Essentially you’ll be formulating a UX analysis report that is easy to read and understand, and you’ll want to store it in an accessible and searchable repository.

You’ll want to ensure that your findings are in “normal” language and that you’ve not littered them with unnecessary data. Most stakeholders don’t need to know the minute details. Stakeholders need to know: what’s happening, why it’s happening, and how to proceed.

In my experience, most stakeholders don’t bother looking at data-heavy documents because they either resemble gibberish or are overwhelming. You’ll also find that you can’t make sense of it after you revisit it a few months later. Your team and future you will thank you for creating a document that only contains easy-to-read key findings that your team can put into action.

Cheat Sheet of Tools and Methodologies

Which tools should you use?

The specific brand of tools you use shouldn’t matter as much as being able to conduct the research itself. That said, you’ll want to have tools that will facilitate the following functions:

  • Research repositories
    • Notion, Google Docs.
  • Surveys
    • Qualtrics, Google Forms, Typeform, SurveyMonkey, Maze.
  • Brainstorming
    • Miro, pen and paper if appropriate.
  • Wireframing
  • Axure, Balsamiq, pen and paper if appropriate.
    • Not a fan of using them for this phase but you could also use Figma or XD.
  • Prototyping
    • Figma, XD, Axure.
  • Remote User Interviews
    • Google Meets, Zoom.
  • Scheduling Interviews
    • Calendly.
  • A/B testing
    • Google Optimize
  • Passive insights or analytics
    • Google Analytics, Amplitude, Mixpanel.
  • Heatmaps
    • Hotjar.

I’ve only named a few I enjoy using, but I’ll emphasize this again: The tool itself doesn’t matter. What matters is that you’re able to conduct the research you need.

What methods should you use, and when?

It’s necessary to understand what methods you can use to conduct research and when to use them. For example, I would conduct a focus group if I want to leverage group-think insights because people behave differently in groups. So if I need to build a large amount of qualitative data and capture the emotions around it, a focus group might work best. On the other hand, if I want to look at how potential users might arrange elements, I might set up a card-sorting exercise. A hypothesis statement will help you determine what methodologies you ought to employ to get the information you need to validate or invalidate it.

I’ve left a cheat sheet below of different methodologies that include qualitative and quantitative methods. These are in no way comprehensive or fully detailed, but I’m hoping they might be good references for you:

Focus Group

A focus group is a research method where you place a group of 5-10 users in a room and engage them in a discussion. Done correctly, you’ll be able to gather a wealth of qualitative data that will help you assess user needs, problems they face, and how they feel.

Card sorting

Card sorting is an exercise where you ask users to organise information into groups that make the most logical sense. The idea here is that you will give your users a series of (labelled) cards and ask them to organise/sort them in a manner they think is appropriate. You typically want around 8-10 users per card sorting group to get the group-think going.

Variant Testing

Ok, this is where we need to be careful about understanding the differences between each method because many companies fall into the trap of using these terms interchangeably even though they refer to very different methodologies.

A/B Testing

A/B Testing is when you split users into two groups and show them two different designs (hence the name A or B). The catch is that you’re testing in a live environment where the difference is in a few select elements.

You essentially test how the original variant performs compared to the new proposal.


Multivariate testing is similar to A/B Testing, but instead of having a single design variant, you might introduce four variations of your landing page. This test will allow you to quickly understand which design performed the best and where to target your redesign efforts. The limitation is that multivariates are more complex than A/B testing and more dependent on your landing page’s traffic. If you’re not generating enough traffic on your landing page, A/B testing might be the better choice.

Preference Testing

Preferential testing is where you show users several design options and ask them to choose the variant they prefer. It’s that simple.

You can use these tests to measure aesthetic appeal or to understand which design variant might seem more authoritative or trustworthy to your users. The advantage of preferential testing is that it allows you to test designs before they go live.

Unfortunately, many companies will equate A/B testing with Preferential testing. That’s not so bad until you consider that many companies will translate preferential tests as “the department head and CEO prefer this, so the users will too!”. If your company or department mishandles these tests, they can become tools that dismiss the entirety of the UX process.


When conducting surveys, the more participants you have, the better your results. Nielsen Norman Group recommends aiming at 40 participants as a minimum sample size for the survey.

User Interviews

Interviews are when you sit down with a potential customer or a stakeholder and try to understand their needs more thoroughly. You can conduct interviews in person or remotely. What matters during an interview is that you do not try and lead your interviewee on with your question, and most importantly, you need to be actively listening and not hogging the mic. Typically you want 3-10 interviews, but honestly, that number varies depending on the insights gathered. Interview quantity doesn’t matter as much as quality since you’ll reach a point of diminishing returns where excess interviews are slowing down the process.

Ethnographic Research

Ethnographic research involves a group of methods that examine how people, your potential customers, relate to technology in their natural settings. You would use these methods to learn more about their daily lives, tendencies, and behavioural patterns as they unfold during the day while trying to complete their tasks.

Ethnographic research includes techniques such as inductive reasoning, exploratory, longitudinal (behaviour over time), diary studies (literally giving a user a diary of sorts so they can log their thoughts and feelings), photography, and video recordings. Each method has its advantages and disadvantages, and there’s quite a bit more than what I’ve listed, but I’ll cover these at another time.

A Note on Random Sampling

When selecting a research method, it’s worthwhile to randomize your participants. The idea would be to randomly select users with varying amounts of experience from varying demographic data, or it could be as simple as randomly selecting a user from a participant list. Randomizing can lead to a more evenly distributed population and help you avoid sorting bias (i.e. alphabetically or chronologically ordered participants list). It can also stop a distinct group from distorting or skewing the narrative in your findings.

If you don’t introduce this kind of check, you might fall into the trap of always interviewing a specific group of users. Some users are a pleasure to interview, and you might forget others exist. You can’t base your research solely on a single user because you’ll find you’re not solving user problems but rather a user’s problem.

User Testing vs Usability

It’s a little pet peeve of mine, but I want to highlight the difference between user testing and usability testing since companies use them interchangeably.

You conduct user tests in the discovery and ideation phase. If we use a car as an example, a user test is where you ask potential customers if it’s visually appealing or if the seats are comfortable.

Usability testing takes place when you need to ensure your MVP/high-fidelity prototype works well before you go live. Using the car metaphor again, this is about asking: How does the car feel when users drive it? In other words, they’re questions you need to ask before you start mass-producing it.

Final Thoughts

Research is a vital part of the UX and product development process, but before we jump in, we need to create structure. The whole premise of the research is to create a hypothesis, or what we think should happen, and find answers that will validate or invalidate it. As UX specialists and designers, it’s our job to use user-informed evidence-based findings to help steer our companies/clients in the right direction. I did not provide a comprehensive list, but I hope this post will serve you as a handy cheat sheet.

Further Reading

[Complete Beginner’s Guide to UX Research UX Booth. (n.d.). Retrieved October 29, 2022, from](

Philips, M. (2019, August 6). The Complete Guide to UX Research Methods. Toptal Design Blog.

The 2021 UX Research Tools Map. (2022, August 25).

UsabilityHub. (n.d.). User Testing Guides. Retrieved October 29, 2022, from

[What is UX Research? Methods & Types UserTesting Blog. (n.d.). UserTesting. Retrieved October 29, 2022, from](

When to Use Which User-Experience Research Methods. (n.d.). Nielsen Norman Group. Retrieved October 29, 2022, from


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