For active churn programmes

Model Health Partnership

Keep predictive signals trustworthy as customers, campaigns and app behaviour change through recurring model and outcome reviews.

Typical timing: Monthly engagement
Discuss a suitable scope
Team reviewing business information together

Best suited to

Teams that already score churn risk and need independent analytical stewardship

We begin by aligning the prediction target, available evidence and operational decision. The work is then shaped to the quality and depth of your data—not forced into a fixed technical package.

What your team receives

  • Drift and performance review
  • Threshold and segment refinement
  • Intervention outcome analysis
  • Quarterly model refresh assessment
  • Clear monthly decision brief

Responsible and explainable by default

We favour the simplest model that produces reliable, useful separation. Data access is limited to the agreed purpose, outputs are documented and business users are shown both the model's strengths and its limits. No model can guarantee that a customer will churn or that an intervention will retain them.

Begin with a fit check

Tell us about your app, customer lifecycle, existing event and account data, and the retention decisions you want to improve. We will identify feasibility, likely gaps and an appropriate next step.

Arrange a fit check →