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Case Study on Customer Churn Predication in Telecom
Subject area: Science,Engineering and Technology · Area of research: Computer Science
Abstract
The Telecommunication Sector has risen to become one of the world?s fastest-growing industries. It?s an organization where the customer comes first, and as a result, client satisfaction is important to the success of businesses in this area. Because of this industry?s global nature, consumers now have a plethora of options when it comes to receiving services. Consumer?s decision to use a certain service provider is influenced by the pricing, flexibility, and customizability of the service. To address these demands, telecom companies work hard to establish policies and services that will entice customers and assist them acquire market position, however in current world, customer churn is a problem in telecom business, so it is vital for telecommunication companies to monitor the behaviors of different customers in order to predict which customers are going to terminate their subscriptions.Customers who are changing their service from current ones are termed as churners. Their could be many reasons for the churning. Researchers have been interested in predicting telecom churners, and several have worked on various algorithms to forecast telecom customer churn. Churn prediction is a crucial determinant of an organization?s ultimate success or failure. As a result, There is an ever-increasing demand to forecast possible churners before they actually leave a service so that retention measures may be tailored to them and the company can grow by maximizing overall income.
Keywords
Churn, Exploratory data analysis, univariate, biavariate, Random Forest, Decision tree
How to cite this paper
@article{1703366,
author = {Renuka Kurle, Prajakta Rane, Kranti Jadhav, Nutan Rane},
title = {Case Study on Customer Churn Predication in Telecom},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {10},
pages = {164-168},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1703366.pdf},
abstract = {The Telecommunication Sector has risen to become one of the world?s fastest-growing industries. It?s an organization where the customer comes first, and as a result, client satisfaction is important to the success of businesses in this area. Because of this industry?s global nature, consumers now have a plethora of options when it comes to receiving services. Consumer?s decision to use a certain service provider is influenced by the pricing, flexibility, and customizability of the service. To address these demands, telecom companies work hard to establish policies and services that will entice customers and assist them acquire market position, however in current world, customer churn is a problem in telecom business, so it is vital for telecommunication companies to monitor the behaviors of different customers in order to predict which customers are going to terminate their subscriptions.Customers who are changing their service from current ones are termed as churners. Their could be many reasons for the churning. Researchers have been interested in predicting telecom churners, and several have worked on various algorithms to forecast telecom customer churn. Churn prediction is a crucial determinant of an organization?s ultimate success or failure. As a result, There is an ever-increasing demand to forecast possible churners before they actually leave a service so that retention measures may be tailored to them and the company can grow by maximizing overall income.},
keywords = {Churn, Exploratory data analysis, univariate, biavariate, Random Forest, Decision tree},
month = {April},
}