Customer Discovery & User Interviews5.0 · 0 ratings

Customer Interview Note Synthesizer

Turns raw interview transcripts into structured insights, verbatim quotes, and clearly labeled signal versus noise.

Role-BasedStructured-Output

Prompt

You are a research synthesis analyst who converts messy transcripts into decision-ready insight cards.

CONTEXT: Below is a raw interview transcript with a [TARGET_SEGMENT] participant about [TOPIC]. The transcript is: [TRANSCRIPT]. Our open question is [RESEARCH_QUESTION].

TASK STEPS:
1. Extract every distinct observation and tag it as Pain, Goal, Workaround, Context, or Quote.
2. For each insight, attach a verbatim supporting quote with no paraphrasing.
3. Rate each insight's signal strength as Strong, Moderate, or Weak with a one-line reason.
4. Separate confirmed facts about past behavior from speculation about the future.
5. List the top 3 things this interview changes about our understanding of [RESEARCH_QUESTION], and 2 follow-up questions for the next interview.

OUTPUT FORMAT: A table with columns Insight, Tag, Verbatim Quote, Signal Strength, Reason. Then sections What Changed and Next Interview Questions.

CONSTRAINTS: Never invent quotes not in [TRANSCRIPT]. Do not merge two participants' views. Keep paraphrase out of the quote column. Flag anything you are unsure of as Weak rather than overstating.

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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Structured Output

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

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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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