Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predicting customer churn: A systematic literature review Subject The topic of the resource Customer churn; Machine learning; Primary 68T35; Systematic literature review Description An account of the resource Churn prediction is an active topic for research and machine learning approaches have made significant contributions in this domain. Models built to address customer churn, aim to identify customers who are at a high risk of terminating services offered by a company. Hence, an effective machine learning model indirectly contributes to the revenue growth of an organization, by identifying at risk customers, well in advance. This improves the success rate of retention campaigns and reduces costs associated with churn. The aim of this study is to explore the state-of-the-art machine learning techniques used in churn prediction. A systematic literature review, that is driven by 5 research questions and rigorous quality assessment criteria, is presented. There are 38 primary studies that are selected out of 420 studies published between 2018 and 2021. The review identifies popular machine learning techniques used in churn prediction and provides directions for future research. Firstly, the study finds that churn models lack generalization capability across industry domains. Hence, it identifies a need for researchers to explore techniques that extend beyond model experimentation, to improve efficiency of classifiers across domains. Secondly, it is observed that the traditional approaches to churn prediction depend significantly on demographic, product-usage, and revenue features alone. However, recent papers have integrated social network analysis-related features in churn models and achieved satisfactory results. Furthermore, there is a lack of scientific work that utilizes information-rich content of customer-company-interaction instances via email, chat conversations and other means. This area is the least explored. Thirdly, there is scope to investigate the effect of hybrid sampling strategies on model performance. This has not been extensively evaluated in literature. Lastly, there is no formal guideline on correct evaluation parameters to be used for models applied on imbalanced churn datasets. This is a grey area that requires greater attention. 2022 Taru Publications. Creator An entity primarily responsible for making the resource De S.; Prabu P. Source A related resource from which the described resource is derived Journal of Discrete Mathematical Sciences and Cryptography, Vol-25, No. 7, pp. 1965-1985. Publisher An entity responsible for making the resource available Taylor and Francis Ltd. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/09720529.2022.2133238" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/09720529.2022.2133238</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143532848&amp;doi=10.1080%2F09720529.2022.2133238&amp;partnerID=40&amp;md5=c0276528be8aa19f4631f63c1b78a62f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143532848&amp;doi=10.1080%2f09720529.2022.2133238&amp;partnerID=40&amp;md5=c0276528be8aa19f4631f63c1b78a62f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9720529 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant De S., Department of Data Science, CHRIST (Deemed to be University), Central Campus, Karnataka, Bangalore, 560029, India; Prabu P., Department of Data Science, CHRIST (Deemed to be University), Central Campus, Karnataka, Bangalore, 560029, India