This project aims to analyze customer churn data to identify key drivers and suggest actionable strategies to improve retention.

The dataset contains 5880 records with features related to customer demographics, services, and churn status.

We performed clustering, feature importance analysis, customer segmentation, and survival analysis to uncover insights.

Key findings include the identification of four customer segments and the main factors influencing churn.

To reproduce the analysis, follow these steps:

1. Clone the repository.
2. Install required packages.
3. Run the analysis script.

The data was sourced from kaggle