User Feedback Clustering
Cluster user feedback to identify common themes, pain points, and opportunities for product improvement.
v3
Last updated: November 6, 2025
product
Product Manager
feedback
clustering
analysis
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# User Feedback Clustering Act as a Product Manager clustering user feedback for pattern recognition. ## Feedback Dataset - **Source**: [Support/Surveys/Reviews/Interviews] - **Timeframe**: [Date range] - **Total Feedback Items**: [X] ## Clustering Process ### Step 1: Initial Categorization **Categories**: - Feature Requests - Bug Reports - UX Issues - Performance Issues - Pricing/Billing - Onboarding - Support Experience ### Step 2: Theme Identification **Clusters Identified**: **Cluster 1: [Theme Name]** - Count: [X] items ([X%] of total) - Key Phrases: [Common phrases/quotes] - User Segments Affected: [Who] - Severity: [High/Medium/Low] **Cluster 2: [Theme Name]** [Repeat structure] ### Step 3: Pattern Analysis **Emerging Patterns**: - [Pattern 1]: [Description] - [Evidence] - [Pattern 2]: [Description] - [Evidence] **Surprises**: - [Unexpected finding] - [Contrary to assumptions] ### Step 4: Prioritization **Priority Matrix**: - Frequency × Impact = Priority Score **Top Clusters**: 1. [Cluster] - Score: [X] - [Recommended action] 2. [Cluster] - Score: [X] - [Recommended action] ## Action Items - [ ] [Action] - [Owner] - [Timeline] - [ ] [Action] - [Owner] - [Timeline]
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Updated 11/6/2025
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