Insight
60-90 days
Prediction window. Enough lead time to act before renewal or cancellation.
Use case
Customer churn prediction
Radiantze trains account risk scores from usage, support, and billing history so retention teams act with clear priority.
Reach at-risk accounts while they can still be saved
Radiantze builds churn models on usage trends, support interactions, and billing history, delivering a refreshed risk score and top contributing factors per account for retention teams.
Scores surface in the CRM beside outreach playbooks, so reps spend limited time on the accounts most likely to leave and know whether the lever is billing, usage, or support.
Insight
Weekly
Score refresh. Risk profiles update as behavior changes, not once at renewal.
Insight
Explainable
Outreach context. Reps see why an account flagged, billing issue vs usage decline.
Partnership
Radiantze rollout pattern
Churn scoring succeeds when the model is paired with outreach playbooks and integration into tools reps already use.
- Define churn precisely, cancellation, downgrade, or inactivity threshold.
- Validate historical data and baseline rules the model must beat.
- Run shadow mode before triggering any outreach.
- Pilot with a subset of reps against a control group.
Outcome
Enterprise outcome
Retention teams focus limited time on accounts most likely to churn, with enough context for relevant outreach.
Radiantze capability stack
Risk scoring model
Segment-aware model trained on your account history to rank cancellation risk on a regular cadence.
Factor breakdown
Top drivers per account so retention outreach is targeted to the signal that actually moved the score.
CRM integration
Risk scores and context surfaced in the tools retention teams already open every day.