Customer churn prediction in Telecom Sector

Abstract

In the telecom industry, many customers use services every day, and companies collect a lot of data about them. Keeping current customers is easier than getting new ones, so businesses want to understand why people leave. Customer churn happens when users switch from one telecom provider to another. When companies know the reasons behind customer churn, they can take steps to improve their services and retain more customers. Machine learning techniques like Random Forest, K-Nearest Neighbors (KNN), and Decision Trees can help analyze customer behavior and predict who might switch to another provider. The objective is to help businesses identify customers who are at risk of leaving (churning) and implement strategies to retain them. By using these techniques, businesses can reduce customer loss, prevent revenue drop, and improve customer service. These insights can also help other industries keep their customers happy and loyal, ensuring long-term business success.