Advancing Hyperpersonalization in Marketing: Integrating Customer Digital Twins, Multi-Agent Intelligence, and Predictive Personalization
Advancing Hyperpersonalization in Marketing: Integrating Customer Digital Twins, Multi-Agent Intelligence, and Predictive Personalization

Summary/Abstract: The rapid development of artificial intelligence in all domains is radically changing all fields of activity. The transformation of marketing practices has been driven by unprecedented levels of personalization. This paper explores three of the most cutting-edge technological trends in the field of marketing. Primarily the application of Customer Digital Twins (CDTs), hierarchical multi-agent systems (MAS) with sub-agents and Predictive Personalization (PP). Due to establishing hyper-personalized marketing strategies, CDTs enable insights to be gained by models that are driven by data about individual consumer behavior, allowing brands to simulate and gain insights into expected interactions. Multi-agent intelligence enables hierarchical multi- agent systems and large language models to model complex scenarios, simulate interactions, and optimize decision-making processes. In this structure, PP has the role of using AI-driven analytics to predict the consumer's preferences and react accordingly before a decision is made. By acting in accordance with new tendencies, combining these approaches enables the creation of adaptive marketing strategies that are primarily extremely individual, contextually enriched, thus establishing improved consumer involvement and value creation. This study highlights both theoretical and practical implications, pointing to new potentials of AI-driven hyper-personalization in modern marketing ecosystems, which have not been addressed in this way so far. The theoretical model and conceptual basis presented in this paper provide an elaborate model of adaptive, context aware, and individualized marketing strategies.

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