Understand what users need before building — jobs to be done, workarounds, and decision criteria.
What job or task were you trying to accomplish when you ran into this problem?
Describe the goal, not the problem itself. What were you trying to get done?
How are you currently solving this problem?
Walk us through your current workaround — even if it is manual, awkward, or pieced together from multiple tools.
How often do you encounter this problem?
How much time or effort does your current workaround cost you?
Give us a sense of the burden — minutes per day, hours per week, or the frustration involved.
What would an ideal solution look like?
Don't worry about whether it is technically feasible. Describe what you wish existed.
What would make you choose one solution over another?
Think about the factors that matter most — ease of use, integrations, price, trust, speed.
What concerns would you have about adopting a new tool for this?
Consider switching costs, learning curve, data migration, or organizational buy-in.
Who else in your organization would be affected by this problem or involved in evaluating a solution?
Even a rough sense — 'just me' or 'our IT team would need to approve this' — is useful.
After each completed session, Mayetik generates a structured AI summary. Here's an example of the output format — the actual content reflects each respondent's answers.
The respondent's answers highlighted three recurring themes — each supported by specific examples drawn from their experience. The summary captures what was said, not what was expected.
Two responses stood out as unusually detailed and pointed to an area worth following up on. The full text of each answer is preserved below the summary.
Based on the patterns in this session, the AI identified three concrete actions for the project team to consider. These are drawn directly from the respondent's own suggestions.
Generated from 8 questions · ~15 min session