CUSTOMER-CHURN-PREDICTION

INSAIDINSTRUCTIONS:You are required to come up with the solution of the given business case.Business Context:This case requires trainees to develop a model for predicting customer churn at a fictitious wireless telecom company and use insights from the model to develop an incentive plan for enticing would-be churners to remain with company.Data for the case are available in csv format. The data are a scaled down version of the full database generously donated by an anonymous wireless telephone company. There are still 7043 customers in the database, and 20 potential predictors. Candidates can use whatever method they wish to develop their machine learning model. The data are available inone data file with 7043 rows that combines the calibration and validation customers. “calibration” database consisting of 4000customers and a “validation” database consisting of 3043customers. Each database contained (1) a “churn” variable signifying whether the customer had left the company two months after observation, and (2) a set of 20 potential predictor variables that could be used in a predictive churn model. Following usual model development procedures, the model would be estimated on the calibration data and tested on the validation data.