Context
High-value digital cohorts need earlier, more relevant engagement before churn becomes irreversible.
CASE STUDY
Predictive Retention Engine
A retention-focused product initiative connecting predictive signals with practical customer interventions.
My role
Defined the product workflow around churn signals, recommendation touchpoints, and business-user visibility.
Solution
Connected churn prediction and recommendation modules to dashboards and intervention workflows for support and business stakeholders.
Product decisions
Prioritized explainable risk signals and usable recommendations so teams could act on model output, not simply view it.
Success measures
Primary measures included retention of targeted cohorts, intervention adoption, and the usefulness of risk and recommendation views.
Confidentiality note
Underlying customer data and production dashboards are confidential; no client information is displayed.