Computer Integrated Manufacturing Systems 1 Customer Churn Prediction in the Telecom Industry Using Machine Learning Algorithms

Abstract

Customer Churn Prediction in the Telecom Industry Using Machine Learning Algorithms Customer churn detection is one of the most important research topics in the telecommunications industry because the company must deal with retaining on-hand customers. Churn refers to the loss of customers as a result of competitors' exiting offers or network issues. In these cases, the customer may decide to cancel their service subscription. Churn rate has a significant impact on customer lifetime value because it affects the company's future revenue as well as the length of service. Companies are looking for a model that can predict customer churn because it has a direct impact on the industry's income. Machine learning techniques are used in the model developed in this work. We can predict which customers are likely to cancel their subscriptions by using machine learning algorithms. We can use this to provide them with better services and lower the churn rate. These models assist telecom services in becoming profitable. We used a Decision Tree, Random Forest, and XGBoost in this model.