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Hyper-Personalised Marketing with Generative AI and Predictive Models: A Systematic Review

Hyper-Personalised Marketing with Generative AI and Predictive Models: A Systematic Review
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Author(s): Paulo Botelho Pires (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal), José Duarte Santos (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal)and Ana Isabel Torres (University of Aveiro, Portugal & INESC TEC, Portugal)
Copyright: 2026
Pages: 34
Source title: Adapting Global Communication and Marketing Strategies to Generative AI
Source Author(s)/Editor(s): Albérico Travassos Rosário (Universidade Europeia, Portugal)and Anna Carolina Boechat (Universidade Europeia, Portugal)
DOI: 10.4018/979-8-3373-2502-6.ch004

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Abstract

This chapter examines how GenAI and predictive modelling strategies affect hyper-personalised marketing. Through a comprehensive literature review and case studies, it examines hyper-personalisation's theoretical frameworks, technical infrastructures, and ethical and governance issues. Large language models, generative adversarial networks, and diffusion models combined with advanced predictive analytics allow firms to scale real-time, highly individualised customer experiences. Effective implementation requires sophisticated data architectures, algorithmic transparency, and strong privacy protections. Integration complexity and ethical accountability are major barriers to consumer engagement and conversion, according to the research. Based on these findings, the chapter proposes an integrated framework that combines technological innovation with ethics and customer focus. This research advances marketing theory and provides practical advice for companies using AI-driven hyper-personalisation while maintaining consumer trust and regulatory compliance.

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