Telecom Churn Prediction Using Machine Learni...

Telecom Churn Prediction Using Machine Learning

Author Name : Sarthak Sahane,Pratham Singh, Pooja Sonawane, Sakshi Chaudhari

ABSTRACT

Customers are the most important assets a business can have, since they generate the majority of profits. In recent years, the telecom market has been incredibly competitive. The cost of keeping customers who are already with you is usually cheaper than acquiring new ones. It's necessary for a telecom company to understand customer churn through customer relationship management (CRM). This way, CRM analyzers can detect which customers might be ready to leave or have already left. Churn is a huge problem and one of the most important concerns for many big companies. As a result, businesses are currently striving to develop methods to identify potential customers who might churn soon. In a highly competitive market, telecom operators can keep their value by building strong relationships with their subscribers and fulfilling preestablished trust levels within them. The percentage of customers that discontinue using a company's products or services at some point during a given timeframe is called customer churn (attrition) rate.

 Keywords: Machine Learning, Random Forest , Decision Tree ,XG Boost ,Prediction ,Churn.