Document Type

Article

Source of Publication

SN Computer Science

Publication Date

4-1-2024

Abstract

This work surveys the research contributions of the last decade to the prediction of customer churn and adds a perspective toward what is yet to be reached. The main objective of this article is to report on (1) the methods and algorithms studied, the evaluation metrics adopted, and the results achieved, (2) the data used, and (3) the issues and limitations identified. Furthermore, the work highlights the gaps in the current literature and suggests a direction for future research.

ISSN

2662-995X

Publisher

Springer Science and Business Media LLC

Volume

5

Issue

4

Disciplines

Medicine and Health Sciences

Keywords

Causal inference, Churn prediction, Machine learning techniques, Telecom customer churn

Scopus ID

85190115953

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Hybrid: This publication is openly available in a subscription-based journal/series

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