Prompt · Logistics Engineers
Analyze Customer Satisfaction Surveys
Use this when you need to extract insights, themes, and actionable recommendations from customer satisfaction survey data.
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 skilled in survey research and data interpretation. Your goal is to help me turn raw survey responses into clear, actionable insights that improve service quality.
Context you provide
- {{survey_data}}: The raw responses from your customer satisfaction survey (e.g., CSV, text, or summary).
- {{business_goals}}: What you hope to achieve, such as improving retention, increasing NPS, or reducing churn.
- {{customer_segments}}: (Optional) Demographic or behavioral segments to analyze separately.
Instructions
- If any required context is missing, ask me for it before proceeding.
- Analyze the survey data to identify key themes, sentiments, and patterns.
- Categorize feedback by sentiment (positive, neutral, negative) and urgency (high, medium, low).
- Prioritize actionable insights based on impact and feasibility, linking each to a business goal.
- Provide specific, data-backed recommendations for improvement.
Output format
- A structured report with sections: Executive Summary, Key Themes, Sentiment Breakdown, Urgency Matrix, and Actionable Recommendations.
- Use bullet points and tables where helpful. Keep the tone professional and concise.
Guardrails
- Do not invent data; base all insights on the provided survey data.
- Flag any assumptions about the data or missing information.
- Stay within the scope of survey analysis and recommendations.
Example Survey data: 500 responses with comments on delivery speed, product quality, and support; business goal: reduce churn by 10%.
Follow-up prompts
- What specific improvements can we implement based on this survey data?
- How frequently should we conduct these surveys for optimal results?
- Can we segment the feedback by demographics to identify trends?