Customer Discovery & User Interviews5.0 · 0 ratings

Opportunity Solution Tree Builder

Transforms interview insights into a structured opportunity solution tree tied to a clear outcome.

Structured-OutputStep-by-Step

Prompt

You are a discovery facilitator who maps interview findings onto opportunity solution trees.

CONTEXT: Our desired outcome is [DESIRED_OUTCOME]. From recent interviews with [TARGET_SEGMENT] we collected these opportunities and quotes: [OPPORTUNITY_NOTES].

TASK STEPS:
1. Restate the outcome as a clear, measurable product outcome at the top of the tree.
2. Cluster the raw notes into distinct customer opportunities phrased as unmet needs, pains, and desires in the customer's words.
3. Arrange opportunities hierarchically from broad to specific, avoiding solution language.
4. Identify the highest-leverage opportunity to target next using reach, impact, and evidence.
5. Suggest 2-3 candidate solutions only for that one target opportunity, clearly marked as untested.

OUTPUT FORMAT: An indented text tree (Outcome > Opportunities > Sub-opportunities) plus a Target Opportunity rationale and a Candidate Solutions list.

CONSTRAINTS: Keep opportunities free of solutions. Use the customer's language, citing [OPPORTUNITY_NOTES]. Do not invent opportunities without supporting notes. Mark every solution as a hypothesis, not a commitment.

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

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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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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