Abstract
Loyalty programs have long served as valuable tools for customer engagement and retention. Today, with the increasing availability of customer data, new methods for analysis and program optimization are becoming a necessity. Artificial Intelligence (AI) has also been a topic of high relevance in recent years, and its connection with loyalty programs has not been researched and discussed enough to date. In this paper we aim to explore the emerging topic of AI data analysis in the context of loyalty programs. We examine various applications of AI data analysis in loyalty programs, including personalized rewards and incentives, customer segmentation and targeting and fraud detection and risk management. Covering these possible applications of AI data analysis provides a general understanding of AI data analysis functioning and its integration into loyalty programs. The provided information also serves as a good basis for understanding how AI data analysis functions and may be applied in various fields. In our paper we look at the outcomes of AI data analysis applications in loyalty programs from the point of view of a customer who is using those programs as well as from the point of view of the brand who manages them. By analyzing the identified points, we then highlight the benefits and challenges of using AI data analysis in loyalty programs. Key research gaps are also presented, emphasizing the need for further research on the topic, with particular attention given to problems such as ethical considerations, data privacy concerns, and the transparency of AI models. The main goal of our article is to provide readers with complex information on the topic of AI data analysis usage in loyalty programs and the ways this technology may benefit customers and the brand in the selected context. The article is theoretical-empirical and is based on external information from trustworthy sources, both digital and printed, completed with our own research outcomes.
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More From: European Conference on Research Methodology for Business and Management Studies
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