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Discover patterns in customer conversations and transform them into actionable product feedback.

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Overview

The Product Insights dashboard surfaces recurring insights from customer calls, automatically extracted and grouped by AI. Each insight represents a pattern that appears across multiple conversations, backed by verbatim customer quotes as evidence.
Key Principle — Every insight is defensible with real customer language. Accuracy is prioritized over coverage — it’s better to miss an insight than hallucinate one.

Evidence-Based

Every insight backed by verbatim customer quotes.

Auto-Grouped

Similar ideas clustered together automatically.

Frequency Tracked

See how often each pattern appears across calls.

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Understanding Insights

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What is an Insight?

An Insight represents a recurring idea that appears across customer conversations. Each insight answers: “What keeps coming up in customer conversations?”

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How Insights Are Created

1

Call Processing

When a call transcript is processed, the AI extracts potential insights.
2

Deduplication

Similar ideas are automatically grouped together using semantic similarity.
3

Evidence Linking

Each mention links the insight to the source call with a verbatim quote.
4

Frequency Tracking

As more calls mention the same idea, the insight’s frequency increases.
Insights are durable. As more calls come in, insights strengthen — they don’t fragment into duplicates.

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Categories

Categories classify the type of feedback, not where it belongs in your product. They answer: “What kind of signal is this?”
  • Bug — Something is broken, not working as expected, or producing errors.
  • Feature Request — Customer explicitly wants new functionality that doesn’t exist.
  • Deal Risk — RARE: Explicit renewal uncertainty, competitive switch, or leadership intervention.
  • Pricing Feedback — Specific comments about cost, value, or pricing structure.
  • Usability Issue — A feature exists but is hard to use, configure, or understand.
  • Workflow Gap — A step, process, or integration is missing entirely.
  • Pain Point — General frustration when no other category clearly applies.
Deal Risk Guidelines — Only categorized as Deal Risk when customers explicitly mention:
  • Renewal uncertainty: “we’re reviewing whether to renew”
  • Competitive switch: “we’re evaluating alternatives”
  • Leadership intervention: “our CFO is doing a cost review”
General complaints or frustrations do not qualify as Deal Risk.

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Dashboard Features

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View Modes

Switch between two display modes:
  • Table View (default): Compact list with sortable columns
  • Grid View: Card-based layout for visual scanning
Combine filters to narrow down results. Click “Clear filters” to reset.

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Exporting Data

Click the Export button to download insights as CSV. The export includes:
  • Insight title and description
  • Category and product area
  • Frequency count
  • First and last seen dates
  • All linked evidence (quotes and sources)

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Insight Details Panel

Click any insight to open the detail panel with three tabs:

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Evidence Tab

View all verbatim quotes supporting this insight:
  • Quote: The exact customer language (never edited or paraphrased)
  • Speaker: Who said it (when available)
  • Sentiment: Positive, neutral, or negative tone
  • Confidence Score: AI certainty (percentage)
  • Source Call: Link to the original conversation
Discover connections:
  • Timeline: When the insight was first and last seen
  • Related Insights: Similar insights based on semantic similarity (shown with match percentage)

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Impact Tab

Understand business context:
  • Affected Accounts: Which CRM accounts mentioned this insight
  • ARR Impact: Total annual revenue from affected accounts
  • Sentiment by Account: Whether each account’s mentions were positive, negative, or neutral

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Product Areas

Product Areas represent how you organize your product, not how the AI categorizes feedback. They’re optional and fully user-controlled. Examples: Billing, Onboarding, Reporting, API, Integrations. To configure product areas, go to Settings → Product Areas.

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Best Practices

Review High-Frequency Insights First — Insights with higher frequency represent patterns mentioned across many calls. These often indicate widespread customer pain, commonly requested features, or critical usability issues.
Track Insight Evolution — Use the timeline feature to understand how long an issue has persisted, whether mentions are increasing or decreasing, and when patterns first emerged.
Cross-Reference with ARR Impact — The Impact tab helps prioritize: High-ARR accounts with negative sentiment = urgent. Multiple enterprise accounts mentioning the same issue = strategic importance.
Use Product Areas for Organization — As insights accumulate, product areas help with team ownership and routing, sprint planning focus, and stakeholder reporting.

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Troubleshooting

  1. Verify integrations are connected in Settings → Integrations
  2. Check that calls have been processed in Dashboard → Processing
  3. Ensure calls contain product feedback (general chat won’t generate insights)
If you see apparent duplicates:
  1. They may have different categories (intentional separation)
  2. Post-processing deduplication runs asynchronously — wait a few minutes
  3. Report persistent duplicates to the product team for threshold tuning
Evidence is only created when:
  1. A verbatim quote is extractable from the transcript
  2. The quote meets quality thresholds
  3. Citation can be validated against source
If an insight has fewer quotes than expected, the AI may not have found clear, extractable evidence in some calls.

Ready to get started?

Connect your first data source and start discovering insights from customer conversations.