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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 Effective ML Techniques to Predict Customer Churn Subject The topic of the resource Class imbalance; Customer churn; Ensemble model; Hybrid model; Machine learning Description An account of the resource Customer churn is one of the most challenging problems that affects revenue and growth strategy of a company. According to a recent Gartner Tech Marketing survey, 91% of C-level respondents rate customer churn as one of their top concerns. However, only 43% have invested in additional resources to support customer expansion. Hence, retaining existing customers is of paramount importance to a company's growth. Many authors in the past have presented different versions of models to predict customer churn using machine learning techniques. The aim of this paper is to study some of the most important machine learning techniques used by researchers in the recent years. The paper also summarizes the prediction techniques, datasets used and performance achieved in these studies for a deeper understanding of the domain. The analysis shows that although hybrid and ensemble methods have been widely successful in improving model performance, there is a need for well-defined guidelines on appropriate model evaluation measures. While most approaches used are quantitative in nature, there is lack of research that focuses on information-rich content in customer company interaction instances, like emails, phone calls or customer support chat records. The information presented in the paper will not only help to increase awareness in industry about emerging trends in machine learning algorithms used in churn prediction, but also help new or existing researchers position their research activity appropriately. 2021 IEEE. Creator An entity primarily responsible for making the resource De S.; Prabu P.; Paulose J. Source A related resource from which the described resource is derived Proceedings of the 3rd International Conference on Inventive Research in Computing Applications, ICIRCA 2021, pp. 895-902. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICIRCA51532.2021.9544785" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICIRCA51532.2021.9544785</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116941177&amp;doi=10.1109%2FICIRCA51532.2021.9544785&amp;partnerID=40&amp;md5=5f6afd4ea9a86a891e926d03a9cae8d3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116941177&amp;doi=10.1109%2fICIRCA51532.2021.9544785&amp;partnerID=40&amp;md5=5f6afd4ea9a86a891e926d03a9cae8d3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-073814627-0 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 Conference paper 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., Christ (Deemed to Be University), Department of Computer Science, Bangalore, India; Prabu P., Christ (Deemed to Be University), Department of Computer Science, Bangalore, India; Paulose J., Christ (Deemed to Be University), Department of Computer Science, Bangalore, India