kienbui1995 Feedback Synthesis
When to Use
When you have a collection of user feedback (interviews, surveys, tickets, reviews) and need to extract patterns and priorities.
Core Jobs
1. Collect and Tag
Sources: interviews, support tickets, NPS verbatims, app reviews, sales calls, Twitter/Reddit Tag each piece of feedback with:
- Theme: what topic (onboarding, performance, pricing, missing feature)
- Sentiment: positive / negative / neutral
- Frequency: how many users mention this
- Severity: blocking (can't use product) / frustrating / nice-to-have
2. Find Patterns
Group by theme, then look for:
- High frequency + high severity = fix now
- High frequency + low severity = backlog
- Low frequency + high severity = investigate (might be a segment)
- Low frequency + low severity = ignore for now
3. Write the Insight
Format: "Users [doing X] struggle with [specific pain] because [root cause]. Evidence: [N] mentions across [sources]." Not: "Users want a better UI." (too vague) Yes: "New users abandon onboarding at step 3 because the API key setup is unclear. 14 support tickets, 3 interview mentions."
4. Prioritize Actions
Map insights to roadmap items. Each insight should connect to:
- A specific user segment
- A measurable outcome if fixed
- An estimated effort (rough)
Key Outputs
- Tagged feedback database
- Theme frequency/severity matrix
- Top 5 actionable insights (with evidence)
- Roadmap input recommendations
Anti-Patterns
- Treating loudest feedback as most important (volume ≠ priority)
- Synthesizing without reading primary sources
- Reporting "what users said" without "what it means"
- Skipping the root cause — solving symptoms, not problems