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BuildBetter’s Clustering feature uses advanced AI to automatically group similar customer feedback into themes, revealing patterns and trends you might otherwise miss. Transform thousands of individual signals into actionable insights with powerful visualizations and reports.

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Understanding Clustering

Clustering automatically organizes your customer feedback into meaningful themes:

AI-Powered Grouping

Machine learning identifies similar feedback and groups them by semantic meaning, not just keywords

Dynamic Analysis

Clusters update in real-time as new feedback arrives, keeping insights current

Trend Detection

Automatically identifies rising and declining themes to spot emerging issues early

Visual Analytics

Rich dashboards with 15+ visualization types for different analytical perspectives

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How Clustering Works

1

Automatic Processing

As signals are extracted from calls, chats, and feedback, the AI analyzes their semantic content
2

Theme Identification

Similar feedback is grouped into clusters based on meaning, creating themes like “onboarding issues” or “pricing concerns”
3

Continuous Refinement

Clusters evolve as more data arrives, becoming more accurate and nuanced over time
4

Insight Generation

AI generates reports for each cluster with key insights, root causes, and recommendations
Clusters require a minimum of 3 similar signals to form, ensuring themes represent actual patterns rather than one-off feedback.

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Cluster List View

Access your clusters through the main clustering page:
  • All Clusters
  • Favorites
Browse all identified themes with:
  • Cluster names and descriptions
  • Signal counts and growth indicators
  • Trending badges for rising themes
  • Search and filter capabilities

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Cluster Detail Pages

Click any cluster to explore in-depth:
Each cluster includes timestamped reports with:
  • Key Insights: Main patterns identified
  • Root Cause Analysis: Underlying issues
  • Business Impact: How this affects your company
  • Recommendations: Suggested actions
  • Trend Analysis: Growth or decline patterns
Representative feedback from real customers:
  • Direct quotes with context
  • Source attribution with timestamps
  • Click-through to original recordings
  • Sentiment indicators
Understand who and what is affected:
  • Company breakdown
  • User persona distribution
  • Revenue impact potential
  • Product area mapping

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Creating Custom Dashboards

Build visual analytics dashboards tailored to your needs:

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Dashboard Builder

1

Start Building

Click “Customize Dashboard” to enter edit mode
2

Add Visualizations

Choose from 15+ card types and drag them onto your dashboard
3

Configure Each Card

  • Select data source and filters
  • Choose visualization style
  • Set card width (full, half, third, quarter)
  • Add titles and descriptions
4

Arrange Layout

Drag and drop cards to create your ideal layout
5

Save and Share

Save your dashboard and share the URL with teammates

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Available Visualizations

Bar Charts

  • Top clusters by volume
  • Cluster growth comparisons
  • Category breakdowns
  • Time period analysis

Pie Charts

  • Persona distribution
  • Sentiment breakdown
  • Category allocation
  • Company distribution

Ridge Charts

  • Sentiment distribution curves
  • Severity patterns
  • Bias analysis
  • Emotion distributions

Heatmaps

  • Cluster activity over time
  • Cross-category correlations
  • Temporal patterns
  • Intensity mapping

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Advanced Visualizations

  • Timeline Charts
  • Statistical Charts
  • Metric Cards
Track cluster evolution:
  • Signal volume over time
  • Growth rate trends
  • Seasonal patterns
  • Event correlations

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Filtering and Analysis

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Query Builder

Create sophisticated filters using the visual query builder:
Type queries in plain English:
  • “Show negative feedback about onboarding from last month”
  • “Find pricing concerns from enterprise customers”
  • “What are new users complaining about?”
The AI converts these to structured filters automatically.
Build complex queries with:
  • AND/OR logic combinations
  • Date range selections
  • Sentiment thresholds
  • Company/persona filters
  • Custom property matching
Save frequently used filter combinations:
  • Name your filter sets
  • Apply with one click
  • Share with teammates
  • Use across dashboards

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Cluster Reports

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Understanding AI Reports

Each cluster generates comprehensive reports containing: Trend Analysis
  • Current period volume vs. previous
  • Percentage change calculations
  • Growth trajectory predictions
  • Seasonal pattern identification
Key Insights
  • Main themes identified
  • Common pain points
  • Satisfaction drivers
  • Emerging concerns
Root Cause Analysis
  • Underlying issues identified
  • Contributing factors
  • System dependencies
  • Process breakdowns
Business Impact
  • Revenue implications
  • Churn risk assessment
  • Adoption barriers
  • Competitive threats

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Using Reports Effectively

1

Regular Review

Check trending clusters weekly to catch emerging issues early
2

Share Insights

Copy report content or share links with stakeholders
3

Track Progress

Monitor how clusters evolve after taking action
4

Create Actions

Use recommendations to drive product and process improvements

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Best Practices

Monitor trending clusters weekly: Early detection of emerging issues prevents escalation
Create role-specific dashboards: Product, support, and sales teams need different views
Combine filters thoughtfully: Layer time, sentiment, and persona filters for deeper insights
Act on insights: Use cluster reports to drive concrete improvements
Share visualizations: Export dashboards for presentations and team alignment

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Common Use Cases

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Product Management

  • Track feature request themes
  • Identify usability issues
  • Monitor adoption barriers
  • Prioritize roadmap items

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Customer Success

  • Spot at-risk accounts early
  • Identify common support themes
  • Track satisfaction trends
  • Prevent churn patterns

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Marketing & Sales

  • Understand objections
  • Track competitive mentions
  • Identify value propositions
  • Monitor market trends

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Leadership

  • Strategic theme tracking
  • Quarterly trend analysis
  • Department performance
  • Market intelligence
Data Requirements: Clustering works best with 100+ signals. Smaller datasets may not form meaningful clusters.

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Automation Features

Clustering includes several automated capabilities:
  • Real-time Updates: Dashboards refresh as new data arrives
  • Trend Alerts: Get notified of significant cluster changes
  • Report Generation: Scheduled cluster analysis reports
  • Integration Hooks: Connect cluster insights to workflows
Clustering transforms overwhelming amounts of feedback into clear, actionable themes, helping you understand what matters most to your customers at scale.
The power of clustering lies in its ability to surface insights you didn’t know to look for, turning raw feedback into strategic intelligence that drives better decisions.