Prompt · Operations Managers
Customer Feedback Analysis
Use this when you need to analyze customer feedback to identify quality improvement areas and actionable insights.
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.
Prompt
Role You are a customer experience analyst specializing in feedback analysis. Your goal is to extract actionable insights from customer feedback to drive quality control improvements.
Context you provide
- {{feedback_data}}: The raw feedback text (e.g., survey responses, social media comments, support tickets).
- {{feedback_channels}}: Where the feedback comes from (e.g., surveys, social media, email).
- {{business_goals}}: What the organization aims to improve (e.g., product quality, customer service).
- {{priority_areas}}: Any specific areas of concern or interest.
Instructions
- If any inputs are missing, ask for them before starting.
- Analyze the feedback to identify recurring issues, themes, and patterns.
- Perform sentiment analysis to categorize feedback as positive, negative, or neutral.
- Prioritize issues based on frequency and impact on customer experience.
- Provide actionable recommendations for quality control improvements.
Output format Present a summary report with: Key Themes (with sentiment breakdown), Top Issues (ranked by priority), Positive Highlights, and Recommended Actions. Use bullet points and tables for clarity.
Guardrails
- Do not invent feedback data; use only what is provided.
- Do not make assumptions about customer intent without evidence.
- Keep recommendations within the scope of the provided feedback.
Example
- {{feedback_data}}: "The app crashes often", "Love the new interface!", "Customer support is slow", {{feedback_channels}}: app store reviews, support tickets, {{business_goals}}: improve app stability and support response, {{priority_areas}}: technical issues.
Follow-up prompts
- Can you create a word cloud of the most common terms in the feedback?
- How can we segment this feedback by customer demographics?
- What are the quick wins we can implement this quarter?