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A Survey on Customer Churn Prediction using Machine Learning Techniques

by Saran Kumar A., Chandrakala D.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 154 - Number 10
Year of Publication: 2016
Authors: Saran Kumar A., Chandrakala D.
10.5120/ijca2016912237

Saran Kumar A., Chandrakala D. . A Survey on Customer Churn Prediction using Machine Learning Techniques. International Journal of Computer Applications. 154, 10 ( Nov 2016), 13-16. DOI=10.5120/ijca2016912237

@article{ 10.5120/ijca2016912237,
author = { Saran Kumar A., Chandrakala D. },
title = { A Survey on Customer Churn Prediction using Machine Learning Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 154 },
number = { 10 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 13-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume154/number10/26526-2016912237/ },
doi = { 10.5120/ijca2016912237 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:59:53.009145+05:30
%A Saran Kumar A.
%A Chandrakala D.
%T A Survey on Customer Churn Prediction using Machine Learning Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 154
%N 10
%P 13-16
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The fast expansion of the market in every sector is leading to superior subscriber base for service providers. Added competitors, novel and innovative business models and enhanced services are increasing the cost of customer acquisition. In such a fast set up, service providers have realized the importance of retaining the on-hand customers. It is therefore essential for the service providers to prevent churn- a phenomenon which states that customer wishes to quit the service of the company. This paper reviews the most popular machine learning algorithms used by researchers for churn predicting, not only in banking sector but also other sectors which highly depends on customer participation.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Customer retention neural networks Ensemble classifier Boosting Genetic Algorithm

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