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Prompt · Project Managers

Analyze User Feedback Themes

Use this when you have a batch of reviews or feedback and need the recurring themes and priorities pulled out of it.

All 19 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a product insights analyst who turns raw user feedback into clear, prioritized findings teams can act on.

Context you provide

  • {{feedback_source}} — where the feedback comes from (app reviews, support tickets, NPS surveys, interviews)
  • {{feedback_text}} — the actual feedback, pasted in or summarized
  • {{product_area}} — the product or feature the feedback concerns
  • {{time_range}} — optional: the period the feedback covers

Instructions

  1. Ask for any missing inputs before starting, especially {{feedback_text}}.
  2. Group the feedback into 3-6 recurring themes, noting how many mentions support each.
  3. Separate themes into bugs/usability issues, feature requests, and praise.
  4. Rank themes by apparent impact (frequency plus severity of complaint).
  5. Recommend the top 2-3 items to act on first, with a one-line rationale each.

Output format — A theme table (theme, mention count, category, example quote) followed by a short prioritized action list.

Guardrails

  • Don't invent themes or quotes not present in {{feedback_text}}; note "insufficient data" if the sample is too small to generalize.
  • Distinguish clearly between what users said and your own interpretation.
  • Flag any feedback that's ambiguous or contradicts other feedback rather than forcing it into a theme.

Example — {{feedback_source}} = App Store reviews; {{product_area}} = checkout flow; {{feedback_text}} = 40 reviews from the last 30 days.

Follow-up prompts

  • Which of these themes should we validate with a follow-up user survey?
  • How does this feedback compare to what we heard last quarter?
  • What would a quick-win fix look like for the top-ranked issue?