A Decade of Churn Prediction Techniques in the TelCo Domain: A Survey

A. Barsotti; G. Gianini; C. Mio; Jianyi Lin; H. Babbar; A. Singh; F. Taher; E. Damiani

doi:10.1007/s42979-024-02722-7

A Decade of Churn Prediction Techniques in the TelCo Domain: A Survey

A. Barsotti^*
, G. Gianini
, C. Mio
, Jianyi Lin
, H. Babbar
, A. Singh
, F. Taher
, E. Damiani

^*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivista › Articolo › peer review

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.

Lingua originale	Inglese
pagine (da-a)	N/A-N/A
Numero di pagine	15
Rivista	SN Computer Science
Volume	5
Numero di pubblicazione	4
DOI	https://doi.org/10.1007/s42979-024-02722-7
Stato di pubblicazione	Pubblicato - 2024

All Science Journal Classification (ASJC) codes

Informatica Generale
Informatica Applicata
Reti e Comunicazioni Informatiche
Computer Grafica e Progettazione Assistita da Computer
Teoria Computazionale e Matematica
Intelligenza Artificiale

Keywords

Causal inference
Churn prediction
Machine learning techniques
Telecom customer churn

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10.1007/s42979-024-02722-7

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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.",

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AU - Barsotti, A.

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AU - Babbar, H.

AU - Singh, A.

AU - Taher, F.

AU - Damiani, E.

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AB - 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.

KW - Causal inference

KW - Churn prediction

KW - Machine learning techniques

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KW - Churn prediction

KW - Machine learning techniques

KW - Telecom customer churn

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A Decade of Churn Prediction Techniques in the TelCo Domain: A Survey

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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