Templates

Detect feedback patterns that predict churn before it shows up in health scores or renewal conversations.

Functions
Customer Success
Voice of Customer / Customer Experience
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Identify churn signals in customer feedback

For when your health scores say green but customers are already frustrated — and you can't see it until the cancellation email arrives.
The Challenge
Health scores lag reality
NPS was 8 last quarter, but the account is now sending 3 frustrated tickets a week. Health scores don't capture the trajectory.
Churn signals are scattered
The warning signs are buried across support tickets, NPS verbatims, and sales call transcripts. No single team sees the full picture.
Reactive, not proactive
By the time churn risk surfaces in a QBR, the relationship has already eroded. The save conversation starts too late.
How teams use Enterpret today
Situation
A CS team overlaid churn data with feedback themes to understand why accounts left. They had 18 months of churned account data but no systematic way to find common patterns.
Action - asked Wisdom, Enterpret's AI assistant
What feedback themes are most common among accounts that churned in the last 12 months? Compare to active accounts of the same segment.
Impact
Discovered that accounts mentioning "data export limitations" were 3.2x more likely to churn — a pattern invisible in NPS alone. Product prioritized an export overhaul.
Situation
A CS team needed account health briefs before every customer call, but manually compiling feedback from tickets, NPS, and call transcripts took 30+ minutes per account.
Action - prompted Claude with Enterpret MCP connector
Built an internal "Create Brief" tool that queries Enterpret Wisdom MCP to auto-generate account health summaries for CSMs before every call.
Impact
CSMs now click "Create Brief" before any customer call and get a complete account summary — support tickets, call themes, sentiment trajectory, NPS scores — synthesized into a 2-minute read. Pre-call prep went from 30 minutes to zero.
Situation
A VP of CS was tired of discovering at-risk accounts during QBR prep. By then, frustration had been building for weeks. They needed real-time detection.
Action -
Action — configured an Enterpret Escalation Agent in Slack
Escalation Agent flags accounts where frustration language or "evaluating alternatives" appears — posts to #cs-alerts with full context.
Impact
Within the first week, the agent flagged 3 accounts that had used "looking at alternatives" language in Gong calls and support tickets. Two were within 60 days of renewal. Proactive outreach saved both.
Related Use Cases
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