MODELING CUSTOMER LIFETIME VALUE WITH MACHINE LEARNING: TECHNIQUES FOR IMPROVED MARKETING STRATEGY FORMULATION

Abstract

This paper examines the interaction between Customer Lifetime Value (CLV), strategic marketing practices, and their impact on organizational economic overall performance. Through a mixed-methods approach, combining quantitative information from client transactions and qualitative insights from a customized questionnaire, the study finds a strong effective relationship among CLV elements—inclusive of product alignment, repeat purchases, and loyalty rewards—and economic outcomes, drastically marketplace valuation (P/E ratio). Additionally, the paper explores the position of gadget getting to know (ML) in improving advertising techniques, such as predictive analytics, personalised pointers, and patron segmentation. ML's software facilitates optimize campaigns, enhance purchaser engagement, and force commercial enterprise boom. The examine offers suggestions for improving customer support, refining advertising techniques, and maintaining financial balance to reinforce customer accept as true with and enterprise success.