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Interview debrief: from transcripts to opportunities, not feature requests

Five user interviews this week. Extract opportunities — not feature requests — while keeping quote-level receipts.

The prompt — copy and run it

You are a product-discovery coach processing user-interview transcripts. I will paste anonymized notes or transcripts. Produce:

A) OPPORTUNITY TABLE — columns: opportunity (the need or pain, phrased in the user's own words), verbatim quote + interview number, frequency across interviews, severity signal (workaround built / paying for alternative / complaining only), existing workaround.

B) FEATURE-REQUEST TRANSLATION — every explicit feature ask in the material, mapped back to the underlying need it expresses, with the quote.

C) NEXT TESTS — the 3 assumptions now most worth testing, each with the cheapest honest test design (fake door, prototype walkthrough, concierge).

Inputs: [PASTE ANONYMIZED TRANSCRIPTS OR NOTES, LABELED BY INTERVIEW NUMBER + SEGMENT] · [PRODUCT + SEGMENT CONTEXT]

Rules: Do not invent user quotes, merge users into composites, or infer needs no quote supports — write "not observed" instead. Verify frequency counts before this enters a roadmap argument. Keep users anonymous: no names, emails, or company identifiers in the output.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Fill in your inputs. Replace each bracketed placeholder with your specifics: [PRODUCT + SEGMENT CONTEXT]
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Translating feature asks back to needs is what separates discovery from order-taking. Frequency and severity columns stop the loudest interview from writing the roadmap, and the quote-level receipts survive the stakeholder who asks 'says who?'

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

Five user interviews this week. Extract opportunities — not feature requests — while keeping quote-level receipts.

Why does this prompt work?

Translating feature asks back to needs is what separates discovery from order-taking. Frequency and severity columns stop the loudest interview from writing the roadmap, and the quote-level receipts survive the stakeholder who asks 'says who?'

What mistake does this prompt help you avoid?

The loudest interview writing the roadmap — frequency and severity columns plus quote-level receipts that survive 'says who?'.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.