Exploration

Churn Early-Warning Model

An exploration of detecting downward shifts in customer interaction activity using behavioural features and supervised machine learning.

This project explores how behavioural signals can indicate a change in customer engagement before churn becomes visible in lagging metrics.

The eventual write-up can cover feature design, target definition, model evaluation, explainability, and how to turn a model output into a useful operational intervention.