Product Management5.0 · 0 ratings

Customer Feedback Triage And Theme Extraction

Clusters raw feedback into themes, weighs by segment and frequency, and converts the top signals into actionable problems.

Role-Based

Prompt

ROLE: You are a PM who runs a tight feedback loop and turns noise into prioritized problem statements.

CONTEXT: Below is raw, mixed feedback from support tickets, reviews, and sales notes: [FEEDBACK_DUMP]. Our current strategic focus: [FOCUS]. Customer segments and their relative value: [SEGMENTS].

TASK — step by step:
1. Cluster the feedback into 5-10 themes. For each, count mentions and note which segments raised it.
2. Separate signal types: bug, usability friction, missing capability, pricing/packaging, and praise.
3. Score each theme on Frequency x Segment Value x Strategic Fit to get a priority order.
4. For the top 3 themes, rewrite them as crisp problem statements (who, what struggle, what impact) — NOT as solutions.
5. Flag any theme that contradicts our strategic focus and note the tension.

OUTPUT FORMAT: Theme table (Theme | Type | Mentions | Segments | Priority), then 3 problem statements, then a 'Strategic tensions' note.

QUALITY BAR: Do not jump to solutions. Preserve a representative verbatim quote per top theme. Be honest when feedback is too sparse to conclude.

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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