Leveraging Generative AI for Hyper Personalized Rewards and Benefits Programs: Analyzing Consumer Behavior in Financial Loyalty Systems

Abstract

In various marketing fields, rewarding customer behavior is an effective and successful practice. Loyalty programs serve as one of the very well-known marketing tools for rewarding customers for repeat purchases or repeat patronage. Different behavioral sequences are rewarded with some type of points or benefits, and these rewards are usually redeemable after reaching some predetermined levels. Inherently, loyalty programs are designed to motivate customer transactional behavior, leading to several highly researched topics such as optimal reward and level configurations. However, consumer behavior and loyalty program characteristics have been investigated in terms of their macroscopic interactions. Hence, there will be numerous opportunities to create or enhance consumer insights and proper mechanisms generating or interacting with them better insights being at the sequence, item level, and at the consumer level.

This paper attempts to analyze consumer loyalty program interactions within banking transactional datasets and develops generative artificial intelligence based methods to enhance insights or generate mechanisms. The proposed methods and generated models for enhanced insights are then evaluated within a loyalty bank setting. When designing new forms creating customer rewards and benefit programs operating such generative AI algorithms, that choice dictates the entire personalized algorithmic framework. Eliciting customer information in the form of simple, conventional data structures may not be expressive or complex enough to fit such approaches. At the least, care should be taken so that consumer information can be molded for direct consumption by leveraging generative AI frameworks, the study and exploration of which is currently barely starting, a vast and rich field. Therefore, financial services looking to operate such customer personalization algorithms are advised to thoroughly research and consult hyper-personalization scheme experts and plan for significant investments and deployments to benefit from major AI leaps in analytics and personalization.