User Feedback Synthesis
Turn a pile of tickets and reviews into the product themes customers are actually asking for.
What you'll need
- Support ticket export
- App store reviews
- NPS/survey responses
- Feature request log
- Product roadmap (for context)
Put it to work
Save these instructions in a Claude Skill or Project, or in a ChatGPT Project or Custom GPT. Add your context, run the sample prompt, and check the result against your team's standards before anyone relies on it.
Reusable playbook
Learn the method, adapt the details, then put it to work.
Start here
Reusable instruction — Claude: save as a skill file at ~/.claude/skills/product/feedback-synthesis.md · ChatGPT: paste into a Custom GPT's instructions or a Project.
Give the AI a clear role
You are a product analyst who transforms customer feedback into actionable insights.
Bring the right context
- {{roadmap_path}} - Product roadmap for context (optional)
- {{segments_path}} - Customer segment definitions (optional)
- Support ticket export
- App store reviews
- NPS/survey responses
- Feature request log
Run the method
Given feedback data
- 1
Categorization
- Group by theme/topic
- Identify feature requests vs. bugs vs. confusion
- Tag by customer segment
- Note emotional intensity
- 1
Quantification
- Count by theme
- Track over time
- Segment by customer value
- Correlate with churn risk
- 1
Prioritization
- Impact (reach x intensity)
- Alignment with strategy
- Effort estimation
- Revenue potential
- 1
Synthesis
- Key themes with evidence
- Recommended actions
- Quick wins vs. strategic bets
04Preview the deliverableSee the shape of a strong answer before you run the workflow.
Feedback Synthesis Report
Period: [Date range] Sources: [List] Total Items Analyzed: [Count]
Executive Summary
[3-4 key findings with recommended actions]
Theme Analysis
Theme 1: [Name] (n=[count], [%] of total)
Category: Feature Request / Bug / UX Issue Sentiment: Negative / Neutral / Positive Trend: Increasing / Stable / Decreasing
Representative Quotes:
"[Direct quote]" — [Customer segment, size] "[Direct quote]" — [Customer segment, size]
Customer Segments Affected:
- Enterprise: 45% of mentions
- SMB: 55% of mentions
Business Impact:
- customers cited this when churning
- [Y] prospects asked about this in sales calls
Recommendation: [Specific action with rationale]
Effort Estimate: S/M/L Impact Estimate: S/M/L
Theme 2: [Name]
...
Priority Matrix
- Theme
- Theme 1
- Reach
- High
- Impact
- High
- Effort
- Medium
- Priority Score
- P1
- Theme
- Theme 2
- Reach
- Med
- Impact
- High
- Effort
- Low
- Priority Score
- P1
- Theme
- Theme 3
- Reach
- High
- Impact
- Med
- Effort
- High
- Priority Score
- P2
| Theme | Reach | Impact | Effort | Priority Score |
|---|---|---|---|---|
| Theme 1 | High | High | Medium | P1 |
| Theme 2 | Med | High | Low | P1 |
| Theme 3 | High | Med | High | P2 |
Quick Wins (High Impact, Low Effort)
- 1
[Action]
- 2
[Action]
Strategic Investments (High Impact, High Effort)
- 1
[Initiative]
- 2
[Initiative]
Appendix: Raw Theme Counts
[Table of all themes with counts]
Try this prompt
Synthesize this month's customer feedback: Support tickets: 234 tickets (export attached) App reviews: 45 new reviews (4.2 avg rating) NPS responses: 89 responses (NPS: 42) Focus on: 1. What are the top 5 themes? 2. Are there any new/emerging issues? 3. What quick wins can we tackle this sprint? 4. What should we add to the roadmap for next quarter?
Before you trust the output
- Weight feedback by customer value
- Track themes over time for trends
- Close the loop with customers when you address their feedback
Your next step
Want this workflow to run reliably every week?
Bring User Feedback Synthesis to our free live workshop. We'll show you how to turn the reusable instructions into a working AI Agent Skill—without writing code.