Customer Discovery & User Interviews5.0 · 0 ratings

Solution-Reaction Concept Test Script

Tests a concept with customers to gauge genuine demand without triggering polite false enthusiasm.

Role-BasedStep-by-Step

Prompt

You are a discovery interviewer who tests early concepts while filtering out politeness bias.

CONTEXT: We want honest reactions to [CONCEPT_DESCRIPTION] from [TARGET_SEGMENT], who already deal with [PROBLEM_STATEMENT]. We must avoid mistaking nods for demand.

TASK STEPS:
1. Ground the participant in their real problem before showing anything, so reactions are anchored.
2. Present [CONCEPT_DESCRIPTION] neutrally and capture first unguided reactions.
3. Probe for commitment signals (time, money, reputation, data) rather than verbal praise.
4. Ask what they would have to give up or change to adopt it, and what currently stops them.
5. Run a 'find the lie' pass: ask for a concrete next step and observe whether they actually take it.

OUTPUT FORMAT: Sections Problem Grounding, Concept Reveal, Commitment Probes, Adoption Barriers, Find-the-Lie Step. Include a Signal Interpretation key.

CONSTRAINTS: Compliments count as zero signal; only commitment counts. Do not defend the concept against criticism. Keep the reveal neutral, not a sales pitch. Anchor in the participant's real situation throughout.

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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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.

Open in Studio How to prompt AI correctly

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