Generative Engine Optimization (GEO)

Generative Engine Optimization is the practice of engineering your brand's entire digital footprint to maximize visibility within AI-generated responses. While AEO focuses on getting cited in answer-format queries, GEO encompasses the broader strategy of ensuring generative AI models — including those powering search, shopping, and conversational interfaces — consistently recommend your brand.

GEO considers how LLMs are trained, how they retrieve real-time information through RAG (Retrieval-Augmented Generation), and what signals they use to determine which brands to recommend. This includes training data optimization, retrieval optimization, and prompt response optimization.

Effective GEO requires a multi-channel approach: authoritative content creation, strategic digital PR for cross-platform corroboration, technical configurations for AI crawlers, and continuous monitoring of AI citation share across all major platforms.