Catch churn before the cancel

Churn prediction software uses behavioral, billing, and engagement data to identify which customers are likely to cancel, before they do. Customerscore.io scores every account for churn risk on a 1–5 scale, refreshed daily, and shows the specific drivers behind each score so your team can intervene while there's still time.

In our study of 13,259 B2B SaaS customers, customers with the highest Churn Risk Score churned 31 times more often in the next 60 days than customers with the lowest score. The model is pre-trained across tens of thousands of SaaS users and tuned to your accounts, so you reach at-risk customers 60+ days before they cancel, while a save play can still work.

Often 60 days or more. Because the model scores daily against trends in each customer's own behavior, it catches the gradual disengagement that precedes most churn, not just the moment someone clicks cancel. That's enough runway to run a save play before the renewal conversation.

It's strongest for SaaS with product usage. Connect billing (Stripe, Chargebee) and product analytics (Mixpanel, PostHog, Segment, Amplitude), optionally CRM and support (HubSpot, Salesforce, Intercom, Freshdesk). For best accuracy the model wants roughly two months of history and a set of past churn events to learn from.

Rule-based scoring makes you pick signals, set weights, and maintain thresholds, and it can't catch patterns you haven't coded for. ML churn prediction learns the patterns that actually preceded churn in your data, adapts as your product changes, and explains the per-account drivers. Customerscore.io is ML-based with full driver-level explainability.

They're closely related: a churn-risk score is the predictive half of a health score. Customerscore.io's health score combines a churn-risk score and an upsell score; this page focuses specifically on predicting churn. If you want both directions, see our customer health score software.