November 6, 2025
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4 min

A beginner’s guide to qualitative and quantitative research

Header graphic for the article 'A beginner’s guide to qualitative and quantitative research'

In the field of user research, every method is either qualitative, quantitative – or both. Understandably, there’s some confusion around these 2 approaches and where the different methods are applicable. This article provides a handy breakdown of the different terms and where and why you’d want to use qualitative or quantitative research methods.

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Qualitative research

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Let’s start with qualitative research, an approach that’s all about the ‘why’. It’s exploratory and not about numbers, instead focusing on reasons, motivations, behaviors and opinions – it’s best at helping you gain insight and delve deep into a particular problem. This type of data typically comes from conversations, interviews and responses to open questions. The real value of qualitative research is in its ability to give you a human perspective on a research question. Unlike quantitative research, this approach will help you understand some of the more intangible factors – things like behaviors, habits and past experiences – whose effects may not always be readily apparent when you’re conducting quantitative research. A qualitative research question could be investigating why people switch between different banks, for example.

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When to use qualitative research

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Qualitative research is best suited to identifying how people think about problems, how they interact with products and services, and what encourages them to behave a certain way. For example, you could run a study to better understand how people feel about a product they use, or why people have trouble filling out your sign up form. Qualitative research can be very exploratory (e.g., user interviews) as well as more closely tied to evaluating designs (e.g., usability testing). Good qualitative research questions to ask include:

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  • Why do customers never add items to their wishlist on our website?
  • How do new customers find out about our services?
  • What are the main reasons people don’t sign up for our newsletter?

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How to gather qualitative data

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There’s no shortage of methods to gather qualitative data, which commonly takes the form of interview transcripts, notes and audio and video recordings. Here are some of the most widely-used qualitative research methods:

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  • Usability test – Test a product with people by observing them as they attempt to complete various tasks.
  • User interview – Sit down with a user to learn more about their background, motivations and pain points.
  • Contextual inquiry – Learn more about your users in their own environment by asking them questions before moving onto an observation activity.
  • Focus group – Gather 6 to 10 people for a forum-like session to get feedback on a product.

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How many participants will you need?

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You don’t often need large numbers of participants for qualitative research, with the average range usually somewhere between 5 to 10 people. You’ll likely require more if you're focusing your work on specific personas, for example, in which case you may need to study 5-10 people for each persona. While this may seem quite low, consider the research methods you’ll be using. Carrying out large numbers of in-person research sessions requires a significant time investment in terms of planning, actually hosting the sessions and analyzing your findings.

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Quantitative research

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On the other side of the coin you’ve got quantitative research. This type of research is focused on numbers and measurement, gathering data and being able to transform this information into statistics. Given that quantitative research is all about generating data that can be expressed in numbers, there multiple ways you make use of it. Statistical analysis means you can pull useful facts from your quantitative data, for example trends, demographic information and differences between groups. It’s an excellent way to understand a snapshot of your users. A quantitative research question could involve investigating the number of people that upgrade from a free plan to a paid plan.

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When to use quantitative research

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Quantitative research is ideal for understanding behaviors and usage. In many cases it's a lot less resource-heavy than qualitative research because you don't need to pay incentives or spend time scheduling sessions etc). With that in mind, you might do some quantitative research early on to better understand the problem space, for example by running a survey on your users. Here are some examples of good quantitative research questions to ask:

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  • How many customers view our pricing page before making a purchase decision?
  • How many customers search versus navigate to find products on our website?
  • How often do visitors on our website change their password?

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How to gather quantitative data

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Commonly, quantitative data takes the form of numbers and statistics.

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Here are some of the most popular quantitative research methods:

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  • Card sorts – Find out how people categorize and sort information on your website.
  • First-click tests – See where people click first when tasked with completing an action.
  • A/B tests – Compare 2 versions of a design in order to work out which is more effective.
  • Clickstream analysis – Analyze aggregate data about website visits.

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How many participants will you need?

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While you only need a small number of participants for qualitative research, you need significantly more for quantitative research. Quantitative research is all about quantity. With more participants, you can generate more useful and reliable data you can analyze. In turn, you’ll have a clearer understanding of your research problem. This means that quantitative research can often involve gathering data from thousands of participants through an A/B test, or with 30 through a card sort. Read more about the right number of participants to gather for your research.

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Mixed methods research

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While there are certainly times when you’d only want to focus on qualitative or quantitative data to get answers, there’s significant value in utilizing both methods on the same research projects.Interestingly, there are a number of research methods that will generate both quantitative and qualitative data. Take surveys as an example. A survey could include questions that require written answers from participants as well as questions that require participants to select from multiple choices.

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Looking back at the earlier example of how people move from a free plan to a paid plan, applying both research approaches to the question will yield a more robust or holistic answer. You’ll know why people upgrade to the paid plan in addition to how many. You can read more about mixed methods research in this article:

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Where to from here?

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Now that you know the difference between qualitative and quantitative research, the best way to build confidence is to start testing. Hands-on experience is the fastest path to deeper insight. At Optimal, we make it easy to run your first study, no matter your role or research experience.

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Header graphic for the article 'A short guide to personas'
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1 min read

A short guide to personas

The word “persona” has many meanings. Sometimes the term refers to a part that an actor plays, other times it can mean a famous person, or even a character in a fictional play or book. But in the field of UX, persona has its own special meaning.

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Before you get started with creating personas of your own, learn what they are and the process to create one. We'll even let you in on a great, little tip — how to use Chalkmark to refine and validate your personas.

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What is a persona?

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In the UX field, a persona is created using research and observations of your users, which is analyzed and then depicted in the form of a person’s profile. This individual is completely fictional, but is created based on the research you’ve conducted into your own users. It’s a form of segmentation, which Angus Jenkinson noted in his article “Beyond Segmentation” is a “better intellectual and practical tool for dealing with the interaction between the concept of the ‘individual’ and the concept of ‘group’”.

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Typical user personas include very specific information in order to paint an in-depth and memorable picture for the people using them (e.g., designers, marketers etc).

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The user personas you create don’t just represent a single individual either; they’ll actually represent a whole group. This allows you to condense your users into just a few segments, while giving you a much smaller set of groups to target.

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There are many benefits of using personas. Here are just a few:

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  • You can understand your clients better by seeing their pain points, what they want, and what they need
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  • You can narrow your focus to a small number of groups that matter, rather than trying to design for everybody
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  • They’re useful for other teams too, from product management to design and marketing
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  • They can help you clarify your business or brand
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  • They can help you create a language for your brand
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  • You can market your products in a better, more targeted way

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How do I create a persona?

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There’s no right or wrong way to create a persona; the way you make them can depend on many things, such as your own internal resources, and the type of persona you want.

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The average persona that you’ve probably seen before in textbooks, online or in templates isn’t always the best kind to use (picture the common and overused types like ‘Busy Barry’). In fact, the way user personas are constructed is a highly debated topic in the UX industry.

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Creating good user personas

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Good user personas are meaningful descriptions — not just a list of demographics and a fake name that allows researchers to simply make assumptions.

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Indi Young, an independent consultant and founder of Adaptive Path, is an advocate of creating personas that aren’t just a list of demographics. In an article she penned on medium.com, Indi states: “To actually bring a description to life, to actually develop empathy, you need the deeper, underlying reasoning behind the preferences and statements-of-fact. You need the reasoning, reactions, and guiding principles.”

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One issue that can stem from traditional types of personas is they can be based on stereotypes, or even reinforce them. Things like gender, age, ethnicity, culture, and location can all play a part in doing this.

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In a study by Phil Turner and Susan Turner titled “Is stereotyping inevitable when designing with personas?” the authors noted: “Stereotyped user representations appear to constrain both design and use in many aspects of everyday life, and those who advocate universal design recognise that stereotyping is an obstacle to achieving design for all.”

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So it makes sense to scrap the stereotypes and, in many instances, irrelevant demographic data. Instead, include information that accurately describes the persona’s struggles, goals, thoughts and feelings — all bits of meaningful data.

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Creating user personas involves a lot of research and analyzing. Here are a few tips to get you started:

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1) Do your research

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When you’re creating personas for UX, it’s absolutely crucial you start with research; after all, you can’t just pull this information out of thin air by making assumptions! Ensure you use a mixture of both qualitative and quantitative research here in order to cast your net wide and get results that are really valuable. A great research method that falls into the realms of both qualitative and quantitative is user interviews.

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When you conduct your interviews, drill down into the types of behaviors, attitudes and goals your users have. It’s also important to mention that you can’t just examine what your users are saying to you — you need to tap into what they’re thinking and how they behave too.

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2) Analyze and organize your data into segments

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Once you’ve conducted your research, it’s time to analyze it. Look for trends in your results — can you see any similarities among your participants? Can you begin to group some of your participants together based on shared goals, attitudes and behaviors?

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After you have sorted your participants into groups, you can create your segments. These segments will become your draft personas. Try to limit the number of personas you create. Having too many can defeat the purpose of creating them in the first place.

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Don’t forget the little things! Give your personas a memorable title or name and maybe even assign an image or photo — it all helps to create a “real” person that your team can focus on and remember.

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3) Review and test

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After you’ve finalized your personas, it’s time to review them. Take another look at the responses you received from your initial user interviews and see if they match the personas you created. It’s also important you spend some time reviewing your finalized personas to see if any of them are too similar or overlap with one another. If they do, you might want to jump back a step and segment your data again.

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This is also a great time to test your personas. Conduct another set of user interviews and research to validate your personas.

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User persona templates and examples

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Creating your personas using data from your user interviews can be a fun task — but make sure you don’t go too crazy. Your personas need to be relevant, not overly complex and a true representation of your users.

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A great way to ensure your personas don’t get too out of hand is to use a template. There are many of these available online in a number of different formats and of varying quality.

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This example from UX Lady contains a number of helpful bits of information you should include, such as user experience goals, tech expertise and the types of devices used. The accompany article also provides a fair bit of guidance on how to fill in your templates too. While this template is good, skip the demographics portion and read Indi Young’s article and books for better quality persona creation.

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Using Chalkmark to refine personas

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Now it’s time to let you in on a little tip. Did you know Chalkmark can be used to refine and validate your personas?

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One of the trickiest parts of creating personas is actually figuring out which ones are a true representation of your users — so this usually means lots of testing and refining to ensure you’re on the right track. Fortunately, Chalkmark makes the refinement and validation part pretty easy.

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First, you need to have your personas finalized or at least drafted. Take your results from your persona software or template you filled in. Create a survey for each segment so that you can see if your participants’ perceptions of themselves matches each of your personas.

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Second, create your test. This is a pretty simple demo we made when we were testing our own personas a few years ago at Optimal Workshop. Keep in mind this was a while ago and not a true representation of our current personas — they’ve definitely changed over time! During this step, it’s also quite helpful to include some post-test questions to drill down into your participants’ profiles.

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After that, send these tests out to your identified segments (e.g., if you had a retail clothing store, some of your segments might be women of a certain age, and men of a certain age. Each segment would receive its own test). Our test involved three segments: “the aware”, “the informed”, and “the experienced” — again, this has changed over time and you’ll find your personas will change too.

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Finally, analyze the results. If you created separate tests for each segment, you will now have filtered data for each segment. This is the real meaty information you use to validate each persona. For example, our three persona tests all contained the questions: “What’s your experience with user research?” And “How much of your job description relates directly to user experience work?”

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Persona2 results
   Some of the questionnaire results for Persona #2

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bove, you’ll see the results for Persona #2. This tells us that 34% of respondents identified that their job involves a lot of UX work (75-100%, in fact). In addition, 31% of this segment considered themselves “Confident” with remote user research, while a further 9% and 6% of this segment said they were “Experienced” and “Expert”.

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Persona #2’s results for Task 1
   Persona #2’s results for Task 1

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These results all aligned with the persona we associated with that segment: “the informed”.

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When you’re running your own tests, you’ll analyze the data in a very similar way. If the results from each of your segments’ Chalkmark tests don’t match up with the personas you created, it’s likely you need to adjust your personas. However, if each segment’s results happen to match up with your personas (like our example above), consider them validated!

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For a bit more info on our very own Chalkmark persona test, check out this article.

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Further reading

 

Learn more
1 min read

Best User Research Platforms for 2026

Your research platform shouldn't be the slowest part of your sprint

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Your team ships every two weeks. Your research platform takes three weeks to get a study live, recruited and analysed. By the time insights land, the roadmap has already moved on.

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Speed is only half of it. A fast study with the wrong participants can be worse than no study at all. Screener gaming, ineligible respondents and AI-written answers are now regular complaints in platform reviews. When your data is skewed, the product decisions built on it are too. Your team pays for that later, in rework, missed adoption targets and a harder conversation with stakeholders.

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In 2026 teams are asking more of their tools. They want studies live in minutes, participants they can trust, and pricing that doesn't punish them for doing more research. They want one place to run the methods they rely on, with no stitching together a recruitment tool, a testing tool and a repository.

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We've compared seven of the most widely used user research platforms against Optimal on the things that decide whether research shapes what ships. Here's what we found, including where other platforms are the better fit.

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How we evaluated each platform

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Feature lists all start to look the same. So we judged each platform on five questions that we believe matters to setting up and running a successful research program from the get go:

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  1. Speed to insights. How quickly can you go from a research question to a study in field and results you can share? Approval queues, setup steps and analysis time all count.
  2. Participant quality and reach. How big is the panel, how many countries does it cover, and how much can you trust the people in it? We also looked at whether you can bring your own participants.
  3. Ease of setup. Can a designer or PM run a study on their own, or does every study need a specialist?
  4. Price transparency. Can you see what you'll pay before you talk to sales? Are seats capped, and are core methods locked behind higher tiers?
  5. Design tool workflow. How well does the platform fit the way your team designs, including Figma prototypes and early concepts?

We used public product pages, help docs, pricing pages and third-party review sites, current as of November 2026. Platforms change quickly, so check current plans before you buy.

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The 2026 comparison at a glance

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Optimal is the only platform here that combines instant launch, a 20M+ verified panel across 150+ countries, unlimited seats on every plan and core UX research and IA methods with no tier gating.

Platform Best for Participant panel Setup and launch Pricing
Optimal

Enterprise teams that want every research method and recruitment in one platform

20M+ · 150+ countries

Bring your own free

Launch instantly, no approval queue

Guided setup for designers and PMs

Quote only

Unlimited seats and studies on enterprise plan

UserTesting (Auros)

Large enterprises running video-led usability tests on native mobile apps

2M+ own · 7.6M with User Interviews

40+ countries

Fast for unmoderated video

Moderated sessions use 3-5x more credits

Quote only

Seats plus credits

Maze

Product teams validating Figma prototypes inside sprints

6M+ · 130+ countries

Billed separately

Fast for unmoderated prototype tests

Quick to start with free plan

Free plan

Paid tiers and Enterprise on quote

Great Question

Research ops teams wanting a participant CRM and repository

6M+ · 150+ countries

Via User Interviews integration

Fast with your own panel

External recruitment through partner

Free trial

Self-serve capped at 5 paid seats

Lyssna

Quick design checks like five-second and preference tests

690K+ · 120+ countries

Very quick for short tests

Simple and self-serve

Free plan

Published tiers with seat caps on lower tiers

Dscout

In-context diary studies and mobile-first qualitative research

530K+ own · 3M+ partner

Dscout reviews screeners before launch

Can add days

Quote only

UXtweak

Smaller teams running usability tests on a tight budget

Partner panels · 130+ countries

Quick for single tests

Study types can't be combined in one link

Free plan

Published lower tiers, Enterprise on request

Sources: vendor product, help and pricing pages, plus G2 reviews, as of November 2026.

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Platform by platform

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Every platform here does something well. The question is whether it does what your team needs, at the pace you work.

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Optimal

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Optimal is a user insights platform and research repository built by research, product, and design leaders over 19+ years. It covers surveys, card sorting, tree testing, first-click testing, prototype testing, live site testing, native mobile app testing, AI Interviewer, and qualitative insights, all in one place.

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  • Strengths: Studies go live the moment you're ready, with no review queue. You can recruit from 20M+ verified participants in 150+ countries, or bring your own for free. AI insights, summaries and an AI interviewer help you get from raw data to a shareable finding in minutes. Every plan includes unlimited seats, and the platform holds SOC 2, their management systems and infrastructure is ISO/IEC 27001 and ISO/IEC 27701 certified.
  • Limitations: There are no dedicated diary study or five-second test blocks. Teams running long-form diary research may want a specialist tool alongside.
  • Best for: Teams that want one platform for evaluative research, IA and recruitment, with room for the whole org to take part.

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UserTesting

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UserTesting is the long-standing name in remote video research. After merging with UserZoom and acquiring User Interviews, it now sits under the Auros brand.

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  • Strengths: It covers a broad set of methods, including diary studies and native mobile app testing. Enterprise support and services are deep, and its MCP server connects to AI tools and Figma Make.
  • Limitations: Pricing is quote-only and credit-based, and reviewers report yearly price rises. Joining three platforms has left parts of the experience feeling disjointed, and some reviewers flag participant quality and fulfilment delays.
  • Best for: Large enterprises with a dedicated research budget and a heavy focus on video usability sessions.

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Maze

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Maze is built for rapid prototype validation inside design sprints.

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  • Strengths: It has a well-loved Figma prototype testing flow, a free plan to get started, and a broad AI feature set.
  • Limitations: Card sorting, tree testing and its AI Moderator sit on the Enterprise tier. Reviewers report bugs with large prototypes and heatmaps, and first-click tests allow multiple clicks. Panel credits are billed separately.
  • Best for: Design teams whose research is mostly quick prototype checks.

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Great Question

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Great Question combines participant recruitment, a research CRM, mixed-method studies and an AI repository.

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  • Strengths: Its participant CRM, API and MCP tooling are strong. Observer seats are unlimited, so stakeholders can follow along.
  • Limitations: Self-serve plans cap paid seats at five. Card sorting and tree testing sit on Enterprise. External recruitment runs through a User Interviews integration rather than an in-house panel, and some reviewers report lag on large datasets.
  • Best for: Research ops teams managing their own customer panel.

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Lyssna

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Lyssna, formerly UsabilityHub, is a simple, self-serve platform known for five-second and preference testing.

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  • Strengths: It's quick to learn, has a free plan, and publishes its self-serve pricing. It recently added mobile testing and observer rooms.
  • Limitations: Its 690K+ panel has no managed recruitment, and reviewers say niche audiences can be hard to reach. AI analysis is lighter, and does not yet hold enterprise-grade security certifications.
  • Best for: Smaller teams running fast design checks.

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Dscout

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Dscout specialises in in-context, mobile-first qualitative research.

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  • Strengths: Diary studies are its flagship, and recent AI moderation and insight features are a real investment.
  • Limitations: A Dscout advisor reviews screeners before launch, which can add days. Participants download an app, survey logic is limited, and there's no first-click testing.
  • Best for: Teams running longitudinal, in-the-moment qual research.

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UXtweak

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UXtweak is a researcher-founded platform with a broad toolkit, from card sorting to session recordings.

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  • Strengths: It offers a free plan and published lower tiers, native mobile app testing without an SDK, and testing for AI-generated prototypes.
  • Limitations: AI insight is minimal. You can't combine study types in a single link, and reviewers call the setup interface dated. It's a small team, which can limit enterprise support.
  • Best for: Budget-conscious teams that want breadth without enterprise requirements.

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Why Optimal wins in 2026

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If your team runs one kind of study, a specialist tool may be all you need. Most enterprise teams don't work that way. Some weeks you're testing a prototype, other weeks you're restructuring navigation or checking a concept with a hard-to-reach audience. Your team needs a platform that keeps up with all of it.

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We've spent 19+ years listening to researchers describe the same frustrations: waiting on approvals, chasing recruits, rationing seats and defending data quality to stakeholders. Optimal is built to remove that friction.

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  • Insights in minutes. Launch the moment your study is ready, with no review queue, and let AI summaries turn results into findings you can share the same day.
  • Participants you can trust. Recruit from 20M+ verified participants across 150+ countries, or bring your own for free. Our recruitment team can help with niche and international audiences.
  • Simple enough for everyone. Designers, PMs and researchers run studies with guided setup and templates. Unlimited seats mean the whole team can join in without a budget conversation.
  • Optimal Intelligence. Optimal's growing AI and automation capabilities help you refine studies, uncover key themes, summaries, and insights, and dive deeper with AI chat and MCP.
  • Clear pricing. You pay one platform fee, sized to your research plan. Card sorting, tree testing and first-click testing come included, with no extra tier to unlock them.
  • Built into how you design. Test Figma prototypes or images alongside the IA methods that tell you whether people can find what you've built.
  • Enterprise ready. SOC 2, ISO/IEC 27001 and ISO/IEC 27701, with dedicated onboarding and a Customer Success Manager.

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Netflix, Nike, Toyota, Apple, LEGO and Workday already trust Optimal with their research. Book a demo and we'll walk through your research plan with you.

Header graphic for the article 'What do you prioritize when doing qualitative research?'
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1 min read

What do you prioritize when doing qualitative research?

Qualitative user research is about exploration. Exploration is about the journey, not only the destination (or outcome). Gaining information and insights about your users through interviews, usability testing, contextual, observations and diary entries. Using these qualitative research methods to not only answer your direct queries, but to uncover and unravel your users ‘why’.

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It can be important to use qualitative research to really dig deep, get to know your users and get inside their heads, and their reasons. Creating intuitive and engaging products that deliver the best user experience. 

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What is qualitative research? 🔎

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The term ‘qualitative’ refers to things that cannot be measured numerically and qualitative user research is no exception. Qualitative research is primarily an exploratory research method that is typically done early in the design process and is useful for uncovering insights into people’s thoughts, opinions, and motivations. It allows us to gain a deeper understanding of problems and provides answers to questions we didn’t know we needed to ask. 

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Qualitative research could be considered the ‘why’. Where quantitative user research uncovers the how or the what users want. Qualitative user research will uncover why they make decisions (and possibly much more).

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Priorities ⚡⚡⚡⚡

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When undertaking user research it is great to do a mix of quantitative and qualitative research. Which will round out the numbers with human driven insights.

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Quantitative user research methods, such as card sorting or tree testing, will answer the ‘what’ your users want, and provide data to support this. These insights are number driven and are based on testing direct interaction with your product. This is super valuable to report to stakeholders. Hard data is difficult to argue what changes need to be made to how your information architecture (IA) is ordered, sorted or designed. To find out more about the quantitative research options, take a read.

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Qualitative user research, on the other hand, may uncover a deeper understanding of ‘why’ your users want the IA ordered, sorted or designed a certain way.  The devil is in the detail afterall and great user insights are discoverable. 

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Priorities for your qualitative research needs to be less about the numbers, and more on discovering your users ‘why’. Observing, listening, questioning and looking at reasons for users decisions will provide valuable insights for product design and ultimately improve user experience.

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Usability Testing - this research method is used to evaluate how easy and intuitive a product is to use.  Observing, noting and watching the participant complete tasks without interference or questions can uncover a lot of insights that data alone can’t give. This method can be done in a couple of ways, moderated or unmoderated. While it can be quicker to do unmoderated and easier to arrange, the deep insights will come out of moderated testing. 

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Observational - with this qualitative research method your insights will be uncovered from observing and noting what the participant is doing, paying particular attention to their non-verbal communication. Where do they demonstrate frustration, or turn away from the task, or change their approach? Factual note taking, meaning there shouldn’t be any opinions attached to what is being observed, is important to keep the insights unbiased.

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Contextual - paying attention to the context in which the interview or testing is done is important. Is it hot, loud, cold or is the screen of their laptop covered in post-its that make it difficult to see? Or do they struggle with navigating using the laptop tracker? All of this noted, in a factual manner, without personal inferring or added opinion based observations can give a window into why the participant struggled or was frustrated at any point.

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These research methods can be done as purely observational research (you don’t interview or converse with your participant) and noting how they interact (more interested in the process than the outcome of their product interaction). Or, these qualitative research methods can be coupled with an

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Interview - a series of questions asked around a particular task or product. Careful note taking around what the participant says as well as noting any observations. This method should allow a conversation to flow. Whilst the interviewer should be prepared with a list of questions around their topic, remain flexible enough to dig deeper where there might be details or insights of interest. An interviewer that is comfortable in getting to know their participants unpicks reservations and allows a flow of conversation, and generates amazing insights.

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With an interview it can be of use to have a second person in the room to act as the note taker. This can free up the interviewer to engage with the participant and unpick the insights.

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Using a great note taking side kick, like our Reframer, can take the pain out of recording all these juicy and deep insights. Time-stamping, audio or video recordings and notes all stored in one place. Easily accessed by the team, reviewed, reports generated and stored for later.

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Let’s consider 🤔

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You’re creating a new app to support your gym and it’s website. You’re looking to generate personal training bookings, allow members to book classes or have updates and personalise communication for your members. But before investing in final development it needs to be tested. How do your users interact with it? Why would they want to? Does it behave in a way that improves the user experience? Or does it simply not deliver? But why?

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First off, using quantitative research like Chalkmark would show how the interface is working. Where are users clicking, where do they go after that. Is it simple to use? You now have direct data that supports your questions, or possibly suggests a change of design to support quicker task completion, or further engagement.

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While all of this is great data for the design, does it dig deep enough to really get an understanding of why your users are frustrated? Do they find what they need quickly? Or get completely lost? Finding out these insights and improving on them can make the most of your users’ experience.

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When quantitative research is coupled with robust qualitative research that prioritizes an in-depth understanding of what your users need, ultimately the app can make the most of your users’ experience.

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Using moderated usability testing for your gym app, observations can be made about how the participant interacts with the interface. Where do they struggle, get lost, or where do they complete a task quickly and simply. This type of research enhances the quantitative data and gives insight into where and why the app is or isn't performing.

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Then interviewing participants about why they make decisions on the app, how they use it and why they would use it. These focussed questions, with some free flow conversation will round out your research. Giving valuable insights that can be reviewed, analyzed and reported to the product team and key stakeholders. Focussing the outcome, and designing a product that delivers on not just what users need, but in-depth understand of why. 

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Wrap Up 🥙

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Quantitative and qualitative user research do work hand in hand, each offering a side to the same coin. Hard number driven data with quantitative user research will deliver the what needs to be addressed. With focussed quantitative research it is possible to really get a handle on why your users interact with your product in a certain way, and how. 

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The Optimal Workshop platform has all the tools, research methods and even the note taking tools you need to get started with your user research, now, not next week! See you soon.

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