Integrating Research on AI-Driven Hyper-Personalization: A Review and Framework for Scalable Social Media Campaigns

This paper introduces a novel theoretical framework for AI-driven hyper-personalization in social media marketing, addressing the critical gap in existing research that overlooks the integration of technological, strategic, and ethical dimensions at scale. The framework uniquely combines advanced user profiling, dynamic content personalization, and iterative feedback loops to optimize engagement, loyalty, and ROI. It further tackles scalability challenges through innovations like cloud computing and federated learning, while embedding ethical principles of fairness, transparency, and privacy into its design. Unlike prior studies, this paper provides a holistic roadmap for implementing scalable, cross-platform AI systems and explores the integration of emerging technologies such as AR, VR, and blockchain. By synthesizing actionable insights and proposing future research directions, it redefines the potential of hyper-personalized, user-centric marketing strategies in the digital era.