A Python pipeline to identify SaaS customers at risk of churning, from synthetic data generation to model comparison, with a Streamlit dashboard for risk analysis and prediction.
The challenge
Identifying customers at risk of churning helps SaaS companies focus their retention efforts.
The response
A pipeline with synthetic data generation, exploratory analysis, data preparation and model comparison, plus a Streamlit dashboard with risk analysis, individual prediction and batch scoring.