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Reseach Article

Customer Churn Prediction Analysis

by Jainam D. Shah, Fenil D. Shah, Mrugendra Rahevar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 29
Year of Publication: 2018
Authors: Jainam D. Shah, Fenil D. Shah, Mrugendra Rahevar
10.5120/ijca2018918145

Jainam D. Shah, Fenil D. Shah, Mrugendra Rahevar . Customer Churn Prediction Analysis. International Journal of Computer Applications. 182, 29 ( Nov 2018), 15-17. DOI=10.5120/ijca2018918145

@article{ 10.5120/ijca2018918145,
author = { Jainam D. Shah, Fenil D. Shah, Mrugendra Rahevar },
title = { Customer Churn Prediction Analysis },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2018 },
volume = { 182 },
number = { 29 },
month = { Nov },
year = { 2018 },
issn = { 0975-8887 },
pages = { 15-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number29/30163-2018918145/ },
doi = { 10.5120/ijca2018918145 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:12:48.962552+05:30
%A Jainam D. Shah
%A Fenil D. Shah
%A Mrugendra Rahevar
%T Customer Churn Prediction Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 29
%P 15-17
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper depicts that customer churn prediction has settled as a major research issue with the development of market advancement. The assignment of stir expectation is to distinguish the clients who are professing to move starting with one organization then onto the next. More contenders, new and imaginative plans of action and better administrations are expanding the expense of client securing. In this condition specialist co-ops have understood the significance of the maintenance of existing clients. In this way, suppliers are compelled to put more endeavors for expectation and avoidance of stir. The main intention of this paper is to specify the process of designing the churn prediction model, its application and causes, challenges and problems for designing the model and subsequently, the ways through which the churn rate can be ameliorated.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Customer Churn Data Mining Prediction Model Business Analytics Machine Learning Algorithms.