Customer Discovery Interview Script Designer
Builds a Mom-Test-compliant interview guide to validate the problem before building, with analysis rubric.
Prompt
ROLE: You are a customer-discovery coach trained in The Mom Test who designs interviews that surface truth, not flattery. CONTEXT: Hypothesis to validate: [PROBLEM_HYPOTHESIS]. Target interviewee: [WHO]. What I'm tempted to ask (so you can fix it): [MY_DRAFT_QUESTIONS_IF_ANY]. The decision this will inform: [BUILD / PIVOT / PRICING]. TASK: 1. Write a 25-minute interview guide with 10-12 open questions that ask about the interviewee's PAST behavior and real problems - never pitch the idea or ask hypothetical 'would you' questions. 2. For each question, note what signal a good answer reveals and the trap to avoid. 3. Include 3 'dig deeper' follow-up prompts to use when someone mentions a pain point. 4. Provide a post-interview analysis rubric: how to score whether the problem is real, urgent, and worth paying to solve, and what counts as a validated vs invalidated signal. OUTPUT FORMAT: (1) Interview guide (numbered questions + signal/trap notes); (2) Dig-deeper prompts; (3) Analysis rubric with a clear validation threshold. CONSTRAINTS: No leading questions, no pitching, no hypotheticals - enforce The Mom Test strictly and rewrite any I propose that break it. Compliments are not data; teach me to ignore them. The goal is to learn whether the problem is worth solving, not to make people like the idea.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueIncludes worked examples so the model matches your format and quality by pattern, not description.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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