You are gearing up for a usability test, but here’s the big question: How many test participants do you need? Too many, and you will burn through time and budget. Too few, and you will miss critical insights.
In this article, we will dive into the sample sizes for usability studies and break down how different types of usability testing call for different approaches. We will also explore the key factors that can influence your numbers.
By the end of your read, you will know how to choose the right sample size for your usability studies.
Breaking The 5-User Rule: When It Works & When It Doesn’t
The 5-user rule is a common guideline in usability testing that suggests testing with 5 participants can uncover most usability problems.
The idea is simple: Major issues tend to show up early, so testing with more users causes diminishing returns.
But does it always work?
It is effective when you are doing qualitative usability testing, where the goal is problem discovery rather than statistical confidence. For example, if you are testing a simple interface with a well-defined target audience, five users can catch major usability problems quickly.
Additionally, this rule works when you are doing iterative testing. For example, if you are testing an eCommerce checkout, just 5 users might flag major issues like a missing guest checkout or a confusing payment screen.
To make each round more effective, create a usability testing checklist so you do not miss key steps before testing again.
When does it not work?
If you need quantitative insights, high confidence levels, or user segmentation, 5 users will not cut it. Plus, more users are needed when testing a product with multiple user groups (e.g., customers, admins, power users).
You also need more than 5 testers if you want to measure metrics like task success rates or time on task.
The Takeaway
The 5-user rule is a great starting point, but this is not a one-size-fits-all solution. Know your goals, the number of participants needed, and confidence levels before deciding on a usability testing sample size.
Testing smart, not just small, is what truly improves usability. To help you with this, regardless of how many participants you have, use Loop11 to create and conduct your usability studies. Just follow these 4 easy steps:
Also, to make sure you do not miss or misinterpret any data, get an experienced data analyst. They can identify usability bottlenecks, pinpoint trends across different user segments, and make sure your sample size provides statistically reliable insights before you make product decisions.
Usability Studies Sample Sizes: Finding The Sweet Spot For Every Study
Go through each type of usability study and note how many participants are suggested. Then, discuss with your team to make sure your sample size aligns with your goals and resources.
1. Quantitative Usability Testing
A quantitative usability study measures how well users complete tasks with your product using hard data like:
- Error rates
- Time on task
- Success rates
Unlike qualitative tests that rely on observations, quantitative testing uses numerical data to measure user behavior. It helps you uncover patterns, evaluate design effectiveness, and make decisions backed by concrete metrics.
To do this test, get 20-40 users. Anything fewer skews results. One person struggling does not mean the design is broken, just like one success does not mean it is perfect.
With 20-40 users, patterns emerge that make it easier to see real usability issues instead of random flukes. Say you are testing a new mobile checkout flow. With 5 users, 3 might struggle, but is that a real usability issue or just random?
With 40 test users, if 70% fail at the same step, you know it is a real usability problem, not a coincidence.
2. Card Sorting Usability Testing
A card sorting usability study helps you understand how users group and label information. Participants organize topics into categories that make sense to them, which reveals how your target group naturally expects your content to be structured.
With this method, you can improve navigation to make your website easier to use. But to get statistical significance, you need 30-50 participants.
Here’s why:
When structuring content, you need to identify strong, repeatable patterns. With fewer users, 1 or 2 outliers can completely skew results, making your navigation feel logical to some but confusing to most.
But a larger sample lets you see where they hesitate, what terms they struggle with, and what feels most intuitive overall.
For example, let’s say you are organizing a service-based website, like this one from SIXGUN, and need to structure services like SEO and Search Engine Marketing. With only 5 users, some might group Google Ads under SEO, while others place it in Search Engine Marketing. This will leave you unsure of how to proceed.
But with 50 users, if most agree Google Ads belongs in Search Engine Marketing, that is a clear signal your structure should reflect it; not just a guess based on a handful of opinions.
3. Benchmark Usability Testing
A benchmark usability study measures how well users perform key tasks under consistent conditions to track usability trends over time. Instead of just spotting problems, it sets a baseline for comparison, whether across design updates, competitor products, or industry standards.
Here are the different types of benchmarking tests you can do with Loop11:
How many users do you need?
To get results that are 90% reliable with a 10% margin of error, you need 65 users. This means if 70% of users complete a task successfully, the real success rate is likely between 60% and 80%.
Let’s say you are running user research for a project management SaaS dashboard and testing how easily users can create an automated workflow that assigns tasks based on project status. After redesigning the setup process, you conduct a benchmark usability test with 65 users.
The results show that 70% complete the setup successfully, while 30% get stuck on the “Conditions” step because they do not understand how to set task triggers. With this data, your team can rework the step-by-step guidance to make sure more users complete workflows without confusion.
Finding The Perfect Fit: 4 Key Factors That Affect Your Sample Size
Check your user testing plan against these factors. Make sure your sample size fits your research needs so you get meaningful insights without overspending or under-testing.
A. Product Complexity
Ask yourself: How many features, workflows, and decision points users need to navigate in your product to complete tasks?
The more complex a product is, the harder it is to predict how users will interact with it. For example, a basic video converter may only need a handful of testers, but a full-fledged filmmaking suite like Pzaz requires a larger usability sample size to account for different creative workflows.
Why? Because human factors play a huge role. Users have different levels of experience, expectations, and ways of thinking.
What To Do
Here’s how to handle product complexity in usability testing:
- Conduct smaller iterative rounds to refine different features instead of running one massive test.
- Break testers into groups based on experience level, job role, or industry to uncover different usability challenges.
- Focus on the most-used features first, so qualitative research uncovers the biggest usability barriers early.
- Look at customer support data to identify pain points that should be tested for usability gaps.
B. Testing Method
Your testing method, whether remote or in-person, affects how users interact with your product and how you collect insights.
- In-person: Allows for deeper, more hands-on observation.
- Remote testing: Reaches a wider audience, which makes it ideal for quick feedback.
Both have strengths, but each impacts sample size differently.
Remote testing requires more participants because you lack direct observation, and users interact with the product in uncontrolled environments. Meanwhile, in-person testing benefits from fewer users because direct interactions uncover usability issues faster. Testing too many people in person can slow analysis without adding real value.
What To Do
Here’s how to adjust the sample size for each testing method:
For remote testing:
- Keep sessions short to reduce user fatigue and prevent oversampling because of drop-offs.
- Identify where users abandon the test to determine whether more participants are needed or if the test design needs adjustments.
- Use polling software to gather feedback from a large sample to adjust your sample size and gain early insights before full usability testing.
- Set a minimum response rate to make sure enough users complete the study to avoid recruiting more participants than necessary.
For in-person testing:
- Test different features with separate small groups to guarantee broad coverage without increasing your overall sample size.
- Run tests in smaller sessions to refine findings early and reduce the need for a large sample.
- Conduct detailed user interviews to get deeper insights per session while reducing the number of participants required.
C. Device-Specific Behavior
Device-specific behavior refers to how users interact differently with a product depending on whether they are using a desktop, tablet, or mobile device.
How does this affect your sample size?
Usability issues often vary by device. For example, a mobile user can struggle with touch-based navigation, while a desktop user might have trouble finding key actions because of a wider screen layout.
In addition, testing only one device creates blind spots, which makes your findings incomplete. The key is to balance depth and coverage. Test enough users per device to catch major issues without overspending on redundant testing.
What To Do
Here’s how these tactics help adjust sample size for device-specific behavior:
- Assign testers only one primary device to remove bias from repeated exposure and avoid inflating your sample size with duplicate insights.
- Instead of testing every feature on every device, assign specific tasks to each group to make sure you get focused insights with fewer participants.
- Track completion rates by device. If one device shows a higher failure rate, increasing the sample size for that group guarantees the issue is not just a fluke while keeping the rest balanced.
- Test key features separately. Features like hover effects on desktops or swipe gestures on mobile require dedicated testing groups, so you don’t inflate the sample size by testing unrelated issues.
D. Test Participants Availability
Availability of test participants refers to how easy (or difficult) it is to find the right people for usability testing based on their schedule, location, and willingness to participate.
Why does this affect your sample size?
Some audiences, like executives, medical professionals, or niche B2B users, are harder to recruit. If you cannot find enough testers, your sample size shrinks, which increases the risk of missing critical insights.
On the other hand, over-recruiting to compensate for dropouts can inflate costs and slow analysis.
What To Do
Adjust sample size based on participant availability:
- Reduce test length to increase participation and prevent dropouts.
- Invite loyal users or power users who already actively engage with your product.
- Prioritize key user segments. For example, if you are testing a hospital scheduling system, focus on administrators and nurses who handle appointments daily.
- Use Loop11’s panel if you struggle to find testers. Loop11 provides access to verified user experience participants to save you time.
3 Pitfalls When Deciding Sample Size (And What To Do Instead)
Jot down where you may be misjudging your sample size. Spot a red flag? Adjust it now so your usability test gives you results you can trust.
I. Not Having Enough Time
Tight deadlines can force you to cut corners when choosing a sample size. If you do not have enough time, you might test too few users, resulting in incomplete insights that do not reflect real usability issues.
On the flip side, rushing to test too many users at once can overwhelm your team, which leaves you with data you cannot fully analyze before the deadline.
What Should You Do?
Plan and set a clear testing timeline upfront so you do not scramble at the last minute. You should also recruit participants early to avoid delays. But if you cannot find enough users, do a test in waves rather than waiting to recruit a huge sample at once.
Use Loop11’s online usability testing feature, and choose between these 2 testing options:
What makes Loop11 an even bigger time saver is its AI-powered insights, which help you analyze results faster and spot accurate usability trends.
Another way to save time is to tap into surveys, live chat, and support calls for real user feedback. Bonjoro nailed this, using these tools to fine-tune their UI:
You can do the same. Tweak small details early, so that when it is time for a full usability study, you can focus on bigger, game-changing improvements instead of minor fixes.
II. Testing All Features At Once
Trying to test everything at once is a fast track to confusing results and bloated sample sizes. If you cram too many features into a single usability study, participants struggle to focus.
Additionally, analyzing data from too many interactions at once creates noise instead of clear insights. Instead of testing smart, you end up with a huge sample size just to compensate for messy data.
What Should You Do?
Prioritize critical features first. For example, if you are testing a project management tool, focus on task creation and assignment. If, if teams cannot organize their work efficiently, the rest of the features will not matter.
Use applied research techniques like think-aloud testing to capture real-time user frustrations and uncover hidden usability issues. This can help you avoid cramming too much into one study because it forces you to focus on one feature at a time.
When users talk through their experience as they complete a task, you quickly see:
- What actually works
- What frustrates them
- Where they get confused
Instead of throwing everything at them and hoping for useful feedback, you get clear, immediate insights on specific features.
Rotate features across participants. To do this, test different features in smaller groups instead of all at once. Lastly, review early data before scaling up your sample size unnecessarily.
III. Ignoring Budget Constraints
Blowing your usability testing budget on an unnecessarily large sample size can leave you short on resources for deeper analysis or follow-up testing. On the flip side, if you cut costs too much, you may not test enough users to get reliable insights.
What Should You Do?
Set a budget first to know how much you can spend before deciding on sample size, so you do not overshoot. For example, if you only have $3,000, testing a large group might seem ideal, but without funds for proper analysis, you will end up with data you cannot fully use.
You should also tap into your loyal customers or beta users because they are already in your products. Another option is to use wireframe or prototype testing if you are still in early design to reduce full-scale testing costs.
Here are additional ways to maximize your budget:
- Use heatmaps and session recordings to get behavioral insights without recruiting extra testers.
- Offer discounts instead of cash incentives. For example, instead of paying testers, give them product credits or exclusive access.
- Conduct guerilla testing. To do this, test in casual environments like coffee shops to gather quick insights without a formal lab.
Conclusion
Decide on your next move and do not let sample size hold you back. Review your usability goals and determine how many participants will give you meaningful insights without wasting resources.
You should also assess what is feasible now. If your budget is tight, start with a smaller, well-targeted group instead of overtesting.
Remember, sample sizes for usability studies are not about simply testing more users; they are about testing smart. To help you with this, use Loop11 to conduct your usability tests and get detailed insights. Create an account now and start your free trial.
- Sample Sizes for Usability Studies: One Size Does Not Fit All - May 28, 2025
- Does Thinking Aloud Uncover More Usability Issues? - December 9, 2024
- What Is DesignOps And Why Is It Important? - October 29, 2024
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