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 Forecasting a Fast-Moving Consumer Goods (FMCG) Company's Customer Repurchase Behavior via Classification Machine Learning Models Description An account of the resource With numerous businesses offering clients equivalent products, the FMCG (Fast Moving Consumer Goods) industry is very competitive. Retaining client loyalty and encouraging them to return to make product purchases is a big concern for businesses in this sector. One of the main issues this bleak business needs to overcome is customer retention. Failure to repurchase by customers is a sign that they do not trust the brand, which will increase attrition rates and have an adverse effect on the company's revenue. These issues were addressed by attempting to predict the customer repurchase rate and approaching the target segments in accordance with that prediction, but this was done entirely from the perspective of the consumer and not from the retailer, and it ignores other factors like location, the salespeople they work with, the wholesaler they are affiliated with, and the customer programme they have chosen. The retailer's repurchase pattern must be predicted using a more accurate and effective model that considers all the variables. Retailers play a significant role in the supply chain for FMCG businesses. Different models like KNN, Nae Bayes and Logistic Regression was explored to find the best fit. By keeping them, the business can forge enduring connections that are crucial for preserving stabilityand dependability in the distribution network and having the resources necessary to serve its clients. 2023 ACM. Creator An entity primarily responsible for making the resource Helen Josephine V.L.; Joy J.; Rajan D. Source A related resource from which the described resource is derived ACM International Conference Proceeding Series Publisher An entity responsible for making the resource available Association for Computing Machinery Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1145/3647444.3647840" target="_blank" rel="noreferrer noopener">https://doi.org/10.1145/3647444.3647840</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194181096&amp;doi=10.1145%2F3647444.3647840&amp;partnerID=40&amp;md5=3d781565c676efe2ef3e76e3c3e11826" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194181096&amp;doi=10.1145%2f3647444.3647840&amp;partnerID=40&amp;md5=3d781565c676efe2ef3e76e3c3e11826</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-840070941-8 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 Helen Josephine V.L., School of Business and Management, Christ University, Bangalore, India; Joy J., School of Business and Management, Christ University, Bangalore, India; Rajan D., Department of MCA, CMR Institute of Technology, Bangalore, India