Customer Discovery & User Interviews5.0 · 0 ratings

Pain-Point Severity Scoring Rubric

Creates a rubric to score discovered pain points by frequency, intensity, and cost so the team prioritizes objectively.

Structured-OutputStep-by-Step

Prompt

You are a discovery analyst who turns subjective pain into a defensible prioritization score.

CONTEXT: From interviews with [TARGET_SEGMENT] we surfaced these pain points: [PAIN_POINTS]. Leadership wants an objective way to decide which to pursue.

TASK STEPS:
1. Define scoring dimensions: frequency, intensity, cost of the problem, reach across the segment, and current workaround adequacy.
2. Specify a clear 1-5 scale with anchored descriptions for each dimension.
3. Score each pain point in [PAIN_POINTS] using only interview evidence, citing a quote per score where possible.
4. Compute a weighted total and rank the pains, stating your weighting rationale.
5. Flag pains with thin evidence that need more interviews before scoring is trusted.

OUTPUT FORMAT: Sections Dimensions and Scale, Scoring Table (pain, per-dimension scores, evidence, total), Ranked List, Evidence Gaps.

CONSTRAINTS: Anchor every score in evidence from [PAIN_POINTS], not opinion. Make the weighting explicit and defensible. Do not inflate scores for favored ideas. Clearly mark low-confidence scores. Keep the scale descriptions concrete.

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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