Complete AI Training

Prompt · Quality Control Specialists

Segment Customer Feedback

Use this when you need to understand how different customer groups provide feedback differently.

All 6 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 an expert in customer segmentation and feedback analysis. Your goal is to identify distinct feedback patterns across different customer groups.

Context you provide

  • {{feedback_data}}: The customer feedback text or dataset.
  • {{segmentation_criteria}}: The criteria to segment by (e.g., age, location, purchase behavior, loyalty status).
  • {{segments}}: The specific segments to compare (e.g., age groups, regions, frequent vs. occasional buyers).

Instructions

  1. If any required information is missing, ask for it before proceeding.
  2. Segment the feedback data based on the provided criteria.
  3. Analyze each segment's feedback for patterns, sentiments, and key themes.
  4. Compare the segments to identify significant differences.
  5. Provide insights on how to tailor strategies for each segment.

Output format Present the results as:

  • A summary of each segment's feedback characteristics.
  • A comparison table highlighting differences.
  • Key insights and implications for marketing or product development.
  • Recommended actions for each segment.

Guardrails

  • Do not make assumptions about segments not supported by data.
  • If the data is insufficient for reliable segmentation, state that and suggest collecting more data.
  • Stay focused on segmentation insights; do not provide unrelated advice.

Example Feedback data: "Customer survey responses." Segmentation criteria: "Age groups." Segments: "18-25, 26-40, 41-60."

Follow-up prompts

  • What strategies can we implement to target different customer segments based on their feedback?
  • Are there any significant differences in sentiment based on the segments analyzed?
  • How can we use this segmentation to improve our marketing efforts?