Generalized Churn Prediction
Abstract
Abstract: Customer churn evaluation and management are important to determine the loyalty of customers with the firm and thus to remain aware of each customer whether he will stay or leave the firm. This, in turn, will be used to determine the value of the firm and hence its place in the market. This paper includes existing literature which has been done in the field of churn analysis from time to time. It also provides a new methodology of churn prediction that will act as a general-purpose system for feature selection and hence can be used to evaluate churners of any firm.
Keywords: Churn prediction, customer retention, profitable customers, automatic attribute selector, data mining, classification
Cite this Article: Saima Jan, Afaq Alam Khan. Generalized Churn Prediction. Journal of Artificial Intelligence Research & Advances. 2019; 6(3): 19–24p.
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. |