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 Decoding Customer Lifetime Value to Unlock Business Success with Predictive Machine Learning Approach Subject The topic of the resource AutoML regression; Customer lifetime value prediction; decision tree; linear regression; random forest Description An account of the resource This study highlights how crucial customers are for a company's success who directly impacts revenue and overall business value. This study focuses on analysis of customer lifetime value, the research uses data from 5000 customers with 8 important features with the main goal of predicting customer lifetime value. Business leaders often face choices about where to invest in marketing, like loyalty programs, incentives and ads or nothing. The study suggests that customer lifetime value is a key metric for making smart decisions, which measures how much a customer spends over their time with a company. To predict this value, the research explored different machine learning models - linear regression, decision tree regressor, random forest, and AutoML regressor. Each model is checked for how well it predicts customer spending habits. The results show that AutoML regression stands out for its accuracy without overcomplicating things. This study offers insights for businesses looking to improve their customer-focused strategies and long-term success. 2024 IEEE. Creator An entity primarily responsible for making the resource Adhegaonkar V.R.; Thakur A.R.; Varghese N.; Cheriyan A. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545084" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545084</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204483124&amp;doi=10.1109%2FTQCEBT59414.2024.10545084&amp;partnerID=40&amp;md5=575e4be7e222c075c6f22d37d795a987" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204483124&amp;doi=10.1109%2fTQCEBT59414.2024.10545084&amp;partnerID=40&amp;md5=575e4be7e222c075c6f22d37d795a987</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Adhegaonkar V.R., Christ University, Dept of Business Management, Bengaluru, India; Thakur A.R., Sri Balaji University, Dept of Business Management, Pune, India; Varghese N., Christ University, Dept of Business Management, Bengaluru, India; Cheriyan A., Christ University, Dept of Business Management, Bengaluru, India