Signals are the heartbeat of customer intelligence in BuildBetter. They’re automatically extracted insights that help you understand what your customers are really saying—their needs, frustrations, and desires—across every conversation.

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What Are Signals?

Signals are AI-extracted insights from your customer interactions that capture:

Key Feedback

Feature requests, bug reports, pain points, and positive experiences

Emotional Context

Sentiment, urgency, and emotional tone behind customer messages

Business Impact

How feedback affects revenue, adoption, satisfaction, and retention

Patterns & Themes

Recurring topics and trends across your customer base

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Where Signals Come From

BuildBetter extracts signals from multiple sources automatically:
Every recorded meeting, interview, and conversation is analyzed for insights:
  • Customer calls and demos
  • User interviews and research sessions
  • Internal team discussions
  • Support and success calls

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Types of Signals

BuildBetter categorizes signals to help you focus on what matters:

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For External Interactions (Customers)

  • Feature Requests: Desired functionality and improvements
  • Bugs & Issues: Problems users are experiencing
  • Complaints: Frustrations and negative experiences
  • Praise: Positive feedback and success stories
  • Questions: Areas of confusion or curiosity
  • Objections: Sales and adoption blockers
  • Needs: Underlying requirements and use cases

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For Internal Interactions (Team)

  • Decisions: Conclusions and commitments made
  • Ideas: Innovation and improvement suggestions
  • Challenges: Internal blockers and difficulties
  • Priorities: Focus areas and important initiatives
  • Updates: Progress and status information
  • Dependencies: Cross-team requirements
Signal types are automatically detected based on content analysis. You can also manually adjust or add types to any signal.

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Signal Properties

Each signal captures rich context to help you understand and act:

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Core Information

  • Summary: AI-generated description of the insight
  • Context: Additional background information
  • Source: Link to the exact moment in a call or message
  • Speaker: Who provided this feedback
  • Company: Associated organization

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Analytical Properties

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Understanding Signal Sources

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Call-Based Signals

When signals come from recordings, you get:
  • Video/Audio Clip: The exact segment where feedback was given
  • Full Transcript: Complete context of the conversation
  • Timestamp Links: Jump directly to the moment
  • Speaker Details: Who said what and when

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Conversation Signals

From integrated platforms, you see:
  • Message Thread: Full conversation context
  • Platform Link: Navigate to original source
  • Author Info: User details and history
  • Related Messages: Surrounding context

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Feedback Signals

From surveys and forms:
  • Response Data: Complete form submission
  • Question Context: What was asked
  • Metadata: Submission time, source, user details
Click any signal’s citation to view the full context. This helps verify AI interpretation and gather additional insights.

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Signal Quality Indicators

BuildBetter provides confidence indicators for extracted signals:
1

High Confidence

Clear, explicit feedback with obvious sentiment and intent. These signals require little to no verification.
2

Medium Confidence

Implicit feedback or nuanced insights. Review the source for full context.
3

Low Confidence

Ambiguous or complex feedback. Manual review recommended to ensure accuracy.

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Working with Signals

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Viewing Options

  • Card View: Detailed cards with embedded media players
  • Table View: Compact list for bulk operations
  • Timeline View: Chronological signal flow

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Quick Actions

  • Edit: Modify summary, sentiment, or properties
  • Share: Send to teammates or export
  • Create Ticket: Generate support tickets
  • Add to Folder: Organize related signals
  • View Source: Jump to original context

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Bulk Operations

  • Select multiple signals for batch updates
  • Export filtered sets to CSV
  • Create datasets for document generation
  • Apply tags or properties in bulk
Signals update in real-time as new conversations are processed. Set up alerts to be notified of critical signals immediately.

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Best Practices

Review regularly: Check signals daily or weekly to stay on top of customer feedback.
Verify critical signals: Always review the source for high-severity or high-impact signals.
Tag consistently: Develop a tagging taxonomy for your team to enable better filtering.
Act on patterns: Look for recurring themes rather than one-off mentions.
Close the loop: Update signals when issues are resolved or features are shipped.
Signals transform unstructured conversations into actionable insights, helping you build better products by truly understanding your customers’ voices at scale.