Predicting Churners from the User Base of a Business - A Review
Abstract
Abstract
Customer churn prediction and management is a foremost job aimed by enterprises to maintain cost-effective customers and thus many customer churn prediction models are developed which aim to categorize consumers as non-churners or churners & then retention actions are taken to prevent churners from churning. The data from different companies like Telecommunication Company, financial company, Retail Company etc. can be used to discover valuable patterns which predict the customers’ relationship with the company. From this data customers behavior can be used to predict his loyalty with the company. In this paper different techniques & approaches are discussed given by different researchers to predict churners, so as to apply retention strategies on them. This paper also presents the results that were recorded by various researchers in their research.
Keywords: churn prediction, Data mining, Customer lifetime value, customer relationship management.
Cite this Article
Saima Jan, Afaq Alam Khan. Predicting Churners from the User Base of a Business: A Review. Journal of Artificial Intelligence Research & Advances. 2019; 6(2): 8–16p.
Downloads
Published
Issue
Section
License
Declaration and Copyright Transfer Form
(to be completed by authors)
I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.
- I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
- I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
- I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
- I/We also agree to the authorship of the article in the following order:
Author’s name
1. ________________
2. ________________
3. ________________
4. ________________
| We Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal. |
