AI Churn-Risk Signals for a SaaS Customer Success Team
A weekly risk view per account that combines usage, tickets and call notes, explains why an account is at risk and drafts the outreach.
Customer success learned about churn at renewal time. The signals existed in product data, tickets and calls, but nobody had time to read them across 600 accounts.
The approach.
- 01Joined usage events, billing, support tickets and call transcripts per account.
- 02Scored risk with a simple, explainable model trained on two years of renewals.
- 03Summarised the reasons and drafted a tailored check-in for the CSM.
- 04Reviewed predictions against actual renewals every month.
Claude reads tickets and call notes for sentiment and risk themes, explains the score in plain language and drafts the outreach email.
How we measure it.
Retention is compared for the two quarters after launch against the two before. Warning time is the gap between the first risk flag and the renewal date. Time saved is self-reported by CSMs.
Before you ask.
No. Beyond Technologies uses an explainable model and shows the reasons behind each score, so CSMs can judge it.
HubSpot and Salesforce through their APIs. The output can also be a weekly email or Slack digest.
Want this measured on your own data? Start with a pilot.
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