Predicting Customer Churn using Data Mining and Machine Learning techniques - Logistic Regression, Decision Trees and Random Forests
The Main purpose of this project is to analyze and understand the factors that influence Customer Churn and develop strategies to retain customers. To identify patterns and trends in customer behavior, and then using their information to design and implement targeted retention programs. Aiming to help the telco company develop an effective retention strategy using outcomes of our model that will help the company to keep their customers satisfied and engaged.
Supervised Machine Learning Models used: -Logistic Regression -Decision Trees -Random Forests