kienbui1995/feedback-synthesis

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