Agent skill · marketing growth · daffy0208
customer-feedback-analyzer
Synthesize user feedback from multiple channels and identify patterns to inform product decisions. Use when analyzing feedback, prioritizing feature requests, conducting NPS surveys, or understanding user sentiment. Covers feedback collection, categorization, prioritization frameworks, and closing the feedback loop.
Why this skill is useful
Provides specific frameworks and patterns for analyzing and prioritizing user feedback that the AI wouldn't reliably generate on its own.
What it needs
About 6k tokens when loaded. Last updated 2025-12-25. 33 stars on the source repository.
What this skill does
Customer Feedback Analyzer Collect, analyze, and prioritize user feedback to inform product decisions. Core Principle Never collect feedback you won't act on. Collecting feedback creates expectation of action. If you can't commit to reviewing and acting on it, don't ask for it. Destroys trust. Feedback Channels 1. In-App Feedback Widget Best for: Contextual feedback, low friction Pros: High quality (contextual), immediate Cons: Can interrupt user flow 2. NPS Surveys Best for: Measuring overall satisfaction and loyalty Follow-up question: "What's the main reason for your score?" 3. Support Tickets Best for: Identifying recurring issues 4. User Interviews Best for: Deep qualitative insights 5. Feature Request Voting Best for: Prioritizing roadmap Tools: Canny, ProductBoard, Upvoty 6. Exit Interviews Best for: Understanding why users churn Feedback Categorization By Type By Severity By Frequency By User Segment Prioritization Framework Priority Score Formula Example: Close the Feedback Loop 1. Acknowledge 2. Act 3. Notify Users Who Requested It 4. Public Changelog Common Feedback Patterns Squeaky Wheel Syndrome Silent Churn Feature Bloat Risk Synthesis & Reporting Weekly Feedback Summary Tools & Software Feedback Cadence Quick Start Checklist [ ] Set up in-app feedback widget [ ] Schedule NPS survey (monthly) [ ] Create feedback tracking spreadsheet [ ] Review support tickets weekly [ ] Conduct 2-3 user interviews [ ] Set up public roadmap (optional) [ ] Create email templates for acknowledging feedback [ ] Document feedback categorization process Common Pitfalls ❌ Collecting feedback without acting: Damages trust ❌ Building everything requested: Feature bloat ❌ Not validating with data: Vocal minority ≠ majority ❌ Ignoring silent majority: Not everyone gives feedback ❌ No follow-up: Users want to know you listened Summary Great feedback analysis: ✅ Multiple channels (surveys, tickets, interviews) ✅ Categorize and prioritize systematically ✅ Act on high-priority feedba …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills daffy0208/customer-feedback-analyzer