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Predictive Analytics for Increased Loyalty and Customer Retention in Telecommunication Industry

by Oladapo K. A., Omotosho O. J., Adeduro O. A.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 32
Year of Publication: 2018
Authors: Oladapo K. A., Omotosho O. J., Adeduro O. A.
10.5120/ijca2018916734

Oladapo K. A., Omotosho O. J., Adeduro O. A. . Predictive Analytics for Increased Loyalty and Customer Retention in Telecommunication Industry. International Journal of Computer Applications. 179, 32 ( Apr 2018), 43-47. DOI=10.5120/ijca2018916734

@article{ 10.5120/ijca2018916734,
author = { Oladapo K. A., Omotosho O. J., Adeduro O. A. },
title = { Predictive Analytics for Increased Loyalty and Customer Retention in Telecommunication Industry },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2018 },
volume = { 179 },
number = { 32 },
month = { Apr },
year = { 2018 },
issn = { 0975-8887 },
pages = { 43-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number32/29206-2018916734/ },
doi = { 10.5120/ijca2018916734 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:57:15.906191+05:30
%A Oladapo K. A.
%A Omotosho O. J.
%A Adeduro O. A.
%T Predictive Analytics for Increased Loyalty and Customer Retention in Telecommunication Industry
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 32
%P 43-47
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Literature has indicated that to engage a new customer cost at least 6 – 10 times higher than retaining the existing ones. The competitive nature of the telecommunication industry has made customer retention to be a crucial responsibility for telephone services provider. Since customer retention is a vital element for every establishment to be conscious of in retaining loyal customers, so also is the ability to perfectly predict customer retention is very necessary. Customer retention prediction models are highly needed by the telecommunication industry to efficiently manage the retention of existing customers. This paper proposes a logistic regression model to predict customer retention in the telecommunication industry. The results indicate that logistic regression can predict customer retention with the accuracy of 95.5%. Furthermore, it was observed that when billing issues are resolved it is more likely to retain customer while value-added service and short message service issues are associated with the likelihood of exhibiting customer retention.

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Index Terms

Computer Science
Information Sciences

Keywords

Prediction Predictive Analytics Loyalty Customer Retention

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