Brace blends product usage, support sentiment, and revenue signals into a renewal probability for every account — and triggers the right CS play before churn becomes inevitable. Predicts churn 90 days out at 84% accuracy.
CS teams retaining customers with Brace
Brace shows you exactly which signals moved an account from green to amber, weighted and timestamped. No black-box AI. Your CSMs walk into renewals with evidence, not vibes.
Brace ships with 28 battle-tested CS plays — green→amber check-in, champion-change recovery, expansion-ready outreach — that fire automatically based on score movements. Your CSMs see the right work, in the right order, with drafts ready to send.
"Brace told us in February that our biggest account was going to churn in May. We saw it 84 days before our CSM would have. By April we'd installed a new champion, run two exec syncs, and signed a 3-year expansion instead. That's the kind of moment that pays for the tool for a decade."
Linnea's CS team of 14 manages 312 enterprise accounts. After 12 months on Brace, logo churn fell from 11.4% to 7.0%, and NRR expanded from 134% to 142%. The model identified 38 at-risk accounts CSMs hadn't flagged manually.
Account count doesn't drive price. We don't believe punishing growth for using the tool more.
"We saved a $612k account in Q3 that nobody — including its CSM — thought was at risk. Brace flagged it on a Tuesday because three power-users had stopped using a feature the contract was anchored to."
"I used to need an analyst spending 6 hours/week building a 'risk view' from Tableau. Now my CSMs open Brace on Monday morning and the queue is ranked. The analyst is doing actually-useful work."
"Walking into board prep with 'NRR up 8 points, here's the 14 saves that drove it, each with a Brace play attached' is a different conversation. The board asks better questions now."
Both, deliberately. On Team plans, the score is a weighted-rule model (14 signals, explainable weights you can tune). On Enterprise, we add a gradient-boosted classifier trained on your historical churn outcomes — but every prediction still resolves into the rule-based contributors so CSMs see exactly what's driving the score. You can opt out of the ML layer entirely; some legal/regulated buyers prefer pure rules.
Minimum viable: account_id, user_id, login events, and 3-5 "value moments" (the actions that signify someone is getting value). Most customers are live in 8-12 business days. We pull these via Segment, Mixpanel, Amplitude, your data warehouse (Snowflake/BigQuery), or a thin SDK. You don't need to instrument anything new if you've already done basic product analytics.
Yes — Salesforce is a bidirectional sync (we read accounts/opps, write scores + signal evidence to custom fields). Gainsight and Vitally are read-source integrations (we ingest CTAs, success plans, NPS). We coexist gracefully if you're not ready to replace your CRM-of-record. Most teams keep SFDC and use Brace as the intelligence layer above it.
The Enterprise ML model needs ~18 months of historical outcome data and a minimum of 80 known churns to start performing meaningfully (84% accuracy is a 4-quarter average). For younger companies, we start with our cross-customer baseline and re-train at quarter-end as your data accumulates. Either way, you see the rule-based score from day one.
EU customers can pin tenants to our Frankfurt region (AWS eu-central-1). No cross-region replication, all model inference runs in-region. We sign GDPR-aligned DPAs without negotiation, support DPO requests, and complete TIA assessments on request. SOC 2 Type II + ISO 27001 + GDPR documented in our trust portal.
A 30-minute demo with a CS solution engineer. We'll model one of your at-risk accounts on the call.