Startup Strategy & Fundraising5.0 · 0 ratings

Customer Discovery Interview Script Designer

Builds a Mom-Test-compliant interview guide to validate the problem before building, with analysis rubric.

Role-BasedFew-ShotStep-by-Step

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. 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. 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. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Few-Shot

Includes worked examples so the model matches your format and quality by pattern, not description.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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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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