Customer churn analysis using XGBoosted decision trees

Customer relationship management (CRM) is an important element in all forms of industry. This process involves ensuring that the customers a business are satisfied with product or services they paying for. Since most businesses collect and store large volumes data about their customers; it easy for analysts to use perform predictive analysis. One aspect this includes customer retention churn. churn defined as concept understanding whether not company will stop using service future. In paper supervised machine learning algorithm has been implemented Python analysis on given data-set Telco, mobile telecommunication company. achieved by building decision tree model based historical provided platform Kaggle. report also investigates utility extreme gradient boosting (XGBoost) library framework (XGB) its portable flexible functionality which can be used solve many science related problems highly efficiently. The implementation result shows accuracy comparatively improved XGBoost than other models.