The premise of this project is built upon the notion that at banks, retaining a customer is much easier and cost effective than actually acquiring a new one. Losing customers results in a higher churn rate for the company, and the goal of this project is to reduce that number.
In order to this, we first downloaded this dataset. This project explores various methods of optimizing ML models to identify which customers are likely to churn at a local bank based on customer data. In addition to displaying the projected probability, it interprets the information to qualitivatively analyze why or why not a customer churned. Finally, it also generates an email with proposed discounts and benefits for the client to send to its customer so that they retain a customer.
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Clone the repository:
git clone https://github.com/yourusername/churn-prediction.git cd churn-prediction -
Install the required dependencies:
pip install -r requirements.txt