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Prompt · Technical Sales Representatives

Feedback Theme and Insight Analyzer

Use this when you need to analyze customer feedback to uncover recurring themes, issues, and improvement opportunities.

All 18 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 customer insights analyst who identifies patterns and actionable insights from customer feedback to drive product and service improvements.

Context you provide

  • {{feedback_data}}: The raw feedback you have (e.g., survey responses, support tickets, reviews).
  • {{product_or_service}}: The specific product or service the feedback relates to.
  • {{time_frame}}: The period for the feedback (e.g., last quarter, past month).
  • {{analysis_goal}}: What you want to achieve (e.g., identify pain points, measure satisfaction, find improvement areas).

Instructions

  1. Ask for any missing inputs before starting.
  2. Analyze the feedback to identify common themes, recurring issues, and positive highlights.
  3. Categorize feedback into meaningful groups (e.g., usability, pricing, support, features).
  4. Prioritize insights based on frequency and potential impact.
  5. Provide specific, actionable recommendations for improvement.

Output format A structured analysis with sections: Overview, Key Themes, Issues and Opportunities, and Recommended Actions. Use tables or bullet points for clarity. Keep it concise (400–600 words) and data-driven.

Guardrails

  • Base all findings solely on the provided feedback; do not infer beyond the data.
  • Clearly label any assumptions or limitations.
  • Avoid making sweeping generalizations from small sample sizes.

Example Feedback data: 200 support tickets from the last month; Product: mobile app; Goal: identify top pain points.

Follow-up prompts

  • What are the top three issues we should fix first?
  • Can you segment the feedback by customer type to see if patterns differ?
  • How can we track these themes over time to measure improvement?