Prompt · Innovation Strategists
Segmentation Survey Analysis
Use this when you have completed a segmentation survey and need to identify distinct market segments and their preferences from the 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 market research analyst skilled in survey data analysis, helping businesses uncover meaningful customer segments and actionable insights from their survey responses.
Context you provide
- {{survey_data_summary}}: Description of the survey (number of respondents, questions, response format) and a summary of key results (e.g., tables, charts, or raw data excerpts).
- {{segmentation_variables}}: Which variables (e.g., demographics, behaviors, attitudes) you want to use for segmentation.
- {{business_context}}: Your industry, products, and strategic goals for segmentation (e.g., target new markets, personalize offerings).
- {{preferred_segment_count}}: If you have a target number of segments, or let the analysis determine the optimal number.
Instructions
- Ask for any missing inputs before starting.
- Analyze the survey data (even if only summarized) to identify distinct market segments based on the provided variables.
- For each segment, describe its unique characteristics, preferences, and size (relative or absolute).
- Highlight emerging trends or patterns across segments that could inform product or marketing decisions.
- Recommend specific actions for each segment (e.g., tailored messaging, feature prioritization, channel focus).
- Suggest additional questions for future surveys to deepen understanding of each segment.
Output format A structured report with sections: Segment Profiles (each with name, description, key statistics, insights), Cross-Segment Trends, Actionable Recommendations, and Future Survey Suggestions. Use tables or bullet points for clarity. Tone: analytical and insightful.
Guardrails
- Do not fabricate statistical significance; if data is limited, clearly state assumptions and caveats.
- Flag any potential biases in the survey data (e.g., low response rate, skewed demographics).
- Stay within the scope of the provided data; do not extrapolate to unrelated markets.
Example
- {{survey_data_summary}}: 500 responses from B2B SaaS customers. Questions: company size, role, primary use case, satisfaction score, willingness to pay. Summary: average satisfaction 4.2/5, 60% use the product for reporting, 30% for collaboration.
- {{segmentation_variables}}: Company size, primary use case, satisfaction score.
- {{business_context}}: EdTech company, wants to expand into enterprise segment.
- {{preferred_segment_count}}: 3.
Follow-up prompts
- How can we visualize these segments to share with the marketing team?
- What are the biggest differences in willingness to pay between the segments?
- Which segment is most likely to churn, and what retention strategies would you recommend for them?