Usability Test Sample Size Calculator: How Many Users?
Enter how often a typical problem shows up per participant and this works out how many people you need to see a target share of the problems, or what share a fixed number of sessions will uncover. The key insight: five users only find about 84% of problems when the average problem hits 31% of people. For a problem that hits 10% of users, five sessions give you a 41% chance of seeing it at all.
How many participants does your usability test need?
Uses the problem discovery model from Nielsen and Landauer: the share of problems found by n participants is 1 − (1 − p)n, where p is the chance that one participant runs into a given problem.
How the calculation works
The model treats each problem as something a participant either hits or does not, with the same probability p for everyone. The chance that nobody in n sessions hits it is (1 − p)n, so the chance at least one person does is 1 − (1 − p)n. Averaged across problems of that frequency, the same figure is the share of problems you expect to see. To find the participants needed for a target share D, the calculator solves n = ln(1 − D) / ln(1 − p) and rounds up.
At the 31% average, that gives 84% for five participants, 95% for eight and 98% for ten. At 10% it gives 41%, 57% and 65%. The drop is why the five-users rule holds for the obvious problems and fails for the ones only some people hit.
Where the model breaks down
- Problems are not equally likely for everyone. A confusing label might trip every novice and no expert. Treat each distinct group of users as its own study, which is what the groups field does.
- p from a small study runs high. If you estimate the frequency from the same handful of sessions, the problems nobody saw are missing from the count, so p looks bigger than it is and the sample looks sufficient.
- Your participants may be an unlucky set. The formula gives an expected value. Faulkner's 2003 study found that some random sets of five found only 55% of problems, while sets of 20 never dropped below 95%.
- It says nothing about measurement. For task times, success rates or SUS scores with a margin of error, you need a statistical sample size, not a discovery one.
For planning the sessions themselves, see our usability testing guide.
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