A Bibliometric Systematic Literature Review on Machine Learning Methods for Predicting Customer Churn

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Authors

Publication Details

Journal
International Journal of Data Analysis Techniques and Strategies
Published
2026-04-22
DOI
https://doi.org/10.1504/ijdats.2027.10077898
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
0.00
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article

A Bibliometric Systematic Literature Review on Machine Learning Methods for Predicting Customer Churn

Syed Muhammad Ali Shahbaz Habib, Farzad Fallah, Irfan Saleem, Abdul Rauf
International Journal of Data Analysis Techniques and Strategies
Customer churn and segmentation
article

A Bibliometric Systematic Literature Review on Machine Learning Methods for Predicting Customer Churn

Syed Muhammad Ali Shahbaz Habib, Farzad Fallah, Irfan Saleem, Abdul Rauf
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Data Analysis Techniques and StrategiesVol. 19(1)
Life in Land
Openalex Percentile: Top 13%
Customer churn and segmentation
DOISourceOpenAlex
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A Bibliometric Systematic Literature Review on Machine Learning Methods for Predicting Customer Churn — Syed Muhammad Ali Shahbaz Habib, Farzad Fallah, et al. · International Journal of Data Analysis Techniques and Strategies (2026) | TGRS Research Map | TGRS