Usability testing

Usability testing is checking a product's usability on real users: selecting participants from your audience, task scenarios ('find X', 'complete Y'), observing how they perform (where they get stuck, what they do not understand, where they err, what they say), analysis and a report with found problems by priority and recommendations. You can test the finished product or a prototype (951) before development. Honestly about 'reveals, does not prove perfection', this is key: testing finds problems but does not prove their absence. If the test found no problems — this does NOT mean there are none (perhaps the wrong scenarios, wrong users, wrong depth). 'Passed the test' ≠ 'all perfect'. We honestly report what we checked and what we found rather than pass off the absence of findings as proof of usability. Honestly about the sample: qualitative usability testing works on a small sample — 5–8 people usually uncover most SERIOUS problems (a known pattern), but not all problems and do not give statistics ('what % of users'). For quantitative conclusions other methods and a larger sample are needed. We honestly state that it is a qualitative method: it answers 'what problems exist and why', not 'for what percentage'. Honestly about 'shows, does not fix': the test reveals problems and gives recommendations, but fixing is separate work (redesign, edits) that needs doing and ideally re-checking. Honestly about the effect: it genuinely finds usability problems before they harm, saving on mistakes, but it is diagnostics, not a guarantee that after fixes everything will be perfect. Honestly about access: the product/prototype and access to users are needed. An important boundary: this is usability testing (qualitative); quantitative methods (tree/first-click/5-sec) — 954/955/956; heuristic evaluation (without users) — 959. Picture this: instead of 'launched and losing clients on inconvenience' — found problems in the test in advance. The base price starts from 40,000 ₽ (depends on the number of participants and scenarios).

• It is unclear where users stumble and why they leave.
• Usability decisions are made on team opinions.
• Usability problems surface after launch, on clients.
• No UX check on real people.

• Selecting participants from your audience
• Task scenarios and observing performance
• Analysis of problems by priority + recommendations
• Testing the finished product or a prototype (951)
• Honest boundaries (reveals, does not prove perfection; 'not found'≠'none')
• Indicating it is a qualitative method (not statistics)
• A link with prototypes (951) and quantitative methods (954/955/956)
• Handover of the report and review with you

• Found usability problems before they harm
• A prioritized report with recommendations
• Decisions on observing real people
• Honest boundaries (diagnostics; not proof of perfection; a qualitative method)

• We define scenarios and select participants; prepare tasks
• We run the test, observe, record problems
• We hand over the report with priorities, honestly set boundaries with you

• If the test found no problems — does it mean all is perfect?

  No, and that is honest: testing reveals problems but does not prove their absence. 'Not found' does not mean 'there are none' — perhaps the wrong scenarios, wrong users or wrong depth. 'Passed the test' ≠ 'all perfect'. We honestly report what we checked and what we found rather than pass off the absence of findings as proof of usability.

• 5–8 people — is that too few to judge?

  For a qualitative test — enough for the main thing, honestly. 5–8 participants usually uncover most SERIOUS usability problems (a known pattern). But it is a qualitative method: it answers 'what problems and why', NOT 'for what percentage of users' — for statistics other methods and a larger sample are needed. We honestly state what can be concluded and what cannot.

• Will the test fix the problems by itself?

  No, honestly: the test reveals problems and gives recommendations, but fixing is separate work (redesign, edits) that needs doing and ideally re-checking with a new test. Seeing a problem ≠ fixing it. We give a prioritized list and recommendations, while implementing fixes we can take separately or hand to your team.