AI-Powered Competitive Advertising: Multimodal Personalization for Digital Markets
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The rapid evolution of AI-driven advertising has transformed how businesses engage with consumers in competitive markets. This study presents an agentic, multimodal framework that leverages foundation models to enable hyper-personalized, real-time ad targeting across B2B and B2C sectors. By integrating retrieval-augmented generation (RAG), multimodal reasoning, and persona-based adaptation, our approach enhances engagement while optimizing Return on Ad Spend (ROAS). Experimental validation through real-world and synthetic market simulations demonstrates the framework’s effectiveness in adaptive, privacy-compliant, and scalable advertising strategies.
