AI-Enhanced Loyalty Programs: Personalized Rewards and Their Effects on Long-Term Customer Value

Abstract

This article examines how AI-enhanced loyalty programs use personalized rewards to influence long term customer value, with a particular focus on customer lifetime value (CLV). The study conducts a systematic literature review of peer reviewed journal articles published between 2019 and 2023, addressing the question of how artificial intelligence, machine learning, and advanced analytics are applied to design, personalize, and evaluate loyalty programs. Screening and coding procedures across major databases identify empirical and conceptual studies that link AI driven personalization with outcomes such as satisfaction, loyalty, and financial value. The review finds that loyalty programs are evolving into dynamic, data intensive systems where AI supports continuous segmentation, reward optimization, and CLV based decision making, while personalization of rewards is a key driver of engagement when customers trust data practices. It also highlights important limitations, including reliance on short term metrics, limited longitudinal evidence on CLV, and insufficient integration of ethical and privacy considerations, and outlines directions for future research.