Customer Churn Prediction by Using Machine Learning

Customer Churn Prediction by Using Machine Learning

Guide: - Prof S.V. Bodake

Associate Professor, Department of Computer Engineering, Sinhgad College of Engineering, Vadgaon bk, Pune, Maharashatra, India.

Students: -

1)Harshal Takade

2)Shreeyash Kotgiri

3)Kartikeyan Charkupalli

4)Vinayak Swami

Student at Sinhgad College of Engineering, Vadgaon bk, Pune, Maharashatra, India

Abstract:-

It becomes a significant challenge to predict customer behaviour and retain an existing customer with the rapid growth of digitization which opens up more opportunities for customers to choose from subscription-based products and services model. Since the cost of acquiring a new customer is five-times higher than retaining an existing customer, henceforth, there is a need to address the customer churn problem which is a major threat across the industries. Considering direct impact on revenues, companies identify the factors that increases the customer churn rate. Here, key objective of the paper is to develop a unique Customer churn prediction model which can help to predict potential customers who are most likely to churn. Here, we evaluated and analysed the performance of various machine learning algorithms and identified the most suitable algorithm for telecommunication dataset .The selection of algorithm changes as per dataset provided, working of telecommunication dataset is considered here .To deal with such real-world problems, Paper emphasizes the Model interpretability which is an important metric to help customers to understand how Churn Prediction Model is making predictions.(accuracy measurement techniques).