customer-feedback-analyzer

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

// Contextual feedback
<FeedbackWidget
  context={{
    page: 'dashboard',
    feature: 'export',
    user_action: 'clicked_export'
  }}
  placeholder="How can we improve exports?"
/>

Pros: High quality (contextual), immediate Cons: Can interrupt user flow

2. NPS Surveys

Best for: Measuring overall satisfaction and loyalty

Question: "How likely are you to recommend [Product] to a friend or colleague?"
Scale: 0-10

Scoring:
  Promoters (9-10): Love your product, will advocate
  Passives (7-8): Satisfied but not enthusiastic
  Detractors (0-6): Unhappy, will churn

NPS = % Promoters - % Detractors

Benchmarks:
  Excellent: ≥50
  Good: 30-49
  Needs Work: <30

Follow-up question: "What's the main reason for your score?"

3. Support Tickets

Best for: Identifying recurring issues

Pattern Recognition:
  - Same issue reported 5+ times → UX problem, not edge case
  - Support time > 10 min per ticket → Needs better docs
  - Ticket volume spike → Recent deploy likely caused issue

4. User Interviews

Best for: Deep qualitative insights

Interview Structure:
  1. Background (5 min): Their role, use case
  2. Problem Discovery (10 min): Challenges they face
  3. Solution Validation (10 min): Show prototype, get reaction
  4. Wrap-up (5 min): Any other feedback?

Sample Size: 5-10 users per persona

5. Feature Request Voting

Best for: Prioritizing roadmap

Tools: Canny, ProductBoard, Upvoty

Benefits:
  - See most requested features
  - Reduce duplicate requests
  - Public roadmap transparency
  - Close the loop automatically

Avoid:
  - Building everything requested
  - Letting voters drive strategy