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We build churn prediction models from your existing customer data — usage patterns, billing history, support interactions. You get a model that flags at-risk accounts early enough to intervene, so your retention team can focus where it matters most.
By the time most companies notice a customer is churning, it's too late. Cancellation is the last step in a pattern that started weeks or months earlier — but without a model, those signals are invisible.
Share usage events, billing history, support interactions, and any other signals that might indicate engagement or disengagement.
Churn looks different everywhere. We work with you to define exactly what counts — cancellation, downgrade, inactivity — and set the prediction window.
Our team identifies the most predictive signals while AI tests hundreds of model variations to find the combination that predicts churn most accurately for your data.
You get a churn scoring model with per-account risk scores, the key drivers behind each score, and clear documentation. Deploy it yourself or let us run it.
Send us a sample dataset. We'll show you what's predictable.
Book a call