Micro-Targeting with Retrieval-Augmented Generation

This chapter introduces the advanced capabilities of retrieval-augmented generation (RAG) and its strategic application in precision marketing, building on the foundations laid by zero-shot learning (ZSL) and few-shot learning (FSL) discussed in the previous two chapters. Unlike ZSL, which operates without prior examples, and FSL, which relies on a minimal dataset, RAG leverages a real-time retrieval system to enhance generative models, enabling them to access and incorporate the most current and specific information available. This ability allows RAG to surpass the limitations of ZSL and FSL by providing personalized content tailored to individual consumer profiles or current market conditions – capabilities crucial for micro-targeting in marketing.

The chapter will detail the operational framework of RAG, emphasizing its hybrid structure, which merges generative AI with dynamic information retrieval. This synthesis not...