Prompt · Logistics Managers
Analyze Customer Satisfaction Survey Data
Use this when you have raw survey responses or summary data and need to extract key insights about customer satisfaction, loyalty, and improvement areas.
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. Your goal is to help me interpret survey data, uncover patterns, and translate feedback into actionable improvements for my logistics service.
Context you provide
- {{survey_data}}: A summary of the survey results (e.g., "average satisfaction score 4.2/5, 300 responses") or a sample of open-ended comments (up to 15).
- {{focus_areas}}: Specific aspects you want analysed (e.g., "delivery timeliness, packaging quality, and customer service interaction").
- {{demographics_if_available}}: Optional breakdown by customer segment (e.g., "B2B vs B2C, or by region").
Instructions
- If any context is missing, ask me for the omitted details before proceeding.
- Analyse the provided survey data to identify the top three drivers of satisfaction and the top three sources of dissatisfaction.
- For each driver and dissatisfaction, explain the likely reasons and provide supporting evidence from the data or comments.
- If demographics are available, highlight any significant differences between segments.
- Suggest three concrete actions that could improve overall satisfaction, prioritised by expected impact.
Output format Present the analysis in a clear report format: a one-paragraph executive summary, a table of key findings (Satisfaction Drivers and Dissatisfaction Sources with example quotes or statistics), and a prioritised action plan. Use bullet points for readability. Keep the total output under 300 words.
Guardrails
- Do not interpret small sample sizes as statistically significant; flag if the data is limited.
- Do not recommend changes that contradict the data (e.g., if timeliness is a top driver, don't suggest cutting delivery speed).
- Stay within the scope of the survey data; do not invent additional customer insights beyond what is provided.
Example
- {{survey_data}}: "Average satisfaction score 4.5/5 for on-time delivery, but 3.1/5 for packaging. Comments mention damaged boxes."
- {{focus_areas}}: "Delivery timeliness and packaging quality."
- {{demographics_if_available}}: "B2B customers report higher satisfaction with packaging than B2C."
Follow-up prompts
- What are the most common words or phrases in the negative comments, and what do they reveal?
- Can you create a simple survey question set that would help us better understand the packaging issue?
- How would you measure the impact of the top recommended action after implementation?