Reducing Customer Churn

Overview

We developed a predictive model to identify customers at high risk of churning. By analyzing usage patterns, support interactions, and billing history, the system provides early warnings, allowing the marketing team to intervene with personalized retention offers.

The project successfully helped the client reduce churn by 15% within the first six months of implementation.