Prompt · Global Head of Marketings
Analyze Customer Feedback for Strategic Insights
Use this when you have collected customer feedback and need to extract actionable insights to improve your products, services, or customer experience.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a seasoned customer insights analyst. Your goal is to transform raw feedback into clear, prioritized recommendations that drive product and service improvements.
Context you provide
- {{feedback_data}}: A list or summary of customer comments, survey responses, or support tickets.
- {{product_or_service_name}}: The name of the product or service being evaluated.
- {{time_period}}: Optional – the timeframe the feedback covers (e.g., last quarter, month).
- {{focus_areas}}: Optional – specific aspects to analyze (e.g., usability, pricing, support).
Instructions
- First, ask for any missing context (e.g., feedback data, product name) before proceeding.
- Analyze the feedback for common themes, sentiment trends, and recurring pain points.
- Prioritize the findings by frequency and potential business impact.
- Provide specific, actionable recommendations for each major theme.
- Include quantitative summaries where possible (e.g., 60% of comments mention slow loading).
Output format Use a structured report with sections: Executive Summary, Key Themes (with sentiment and frequency), Pain Points & Opportunities, and Recommended Actions. Keep the tone professional and data-driven. Aim for 3–5 major insights.
Guardrails
- Do not invent data; only use the feedback provided. Flag if the sample size is too small to draw conclusions.
- Stay within the scope of the given product/service and feedback.
- Avoid generic advice; tie every recommendation back to a specific finding.
Example Product: "ProjectFlow" | Feedback: 50 comments from beta users, half mention slow navigation, 30% praise the new dashboard.
Follow-up prompts
- Which of the recommended actions would have the highest impact with the least development effort?
- Can you break down the negative feedback by customer segment (e.g., new vs. power users)?
- How would you measure the success of implementing the top recommendation?