Data and Research Reports
Stay ahead of the curve with our curated collection of foundational and cutting-edge research in Generative Engine Optimization and AI Search.
GEO: Generative Engine Optimization (Aggarwal et al., ACM SIGKDD 2024)
The seminal academic paper that established GEO as a formal field. Introduces GEO-bench benchmark and 40% visibility improvements.
Generative Engine Optimization: How to Dominate AI Search" (Chen et al., 2025)
Comprehensive comparative analysis of AI Search vs. traditional search across multiple verticals, languages, and query paraphrases.
E-GEO: A Testbed for Generative Engine Optimization in E-Commerce
Research on GEO applications in e-commerce contexts, examining how product descriptions can be optimized for LLM visibility.
Retrieval-Augmented Generation for Large Language Models: A Survey (Gao et al., 2023)
Comprehensive technical survey of RAG systems—the core technology powering AI search. Explains retrieval and generation techniques.