Generative engine optimization (GEO) is one of the names given to the practice of structuring digital content and managing online presence to improve visibility in responses generated by generative artificial intelligence (AI) systems. The practice influences the way large language models (LLMs), such as ChatGPT, Google Gemini, Claude, and Perplexity AI, retrieve, summarize, and present information in response to user queries. Related terms include answer engine optimization (AEO) and artificial intelligence optimization (AIO).
The concept of GEO first appeared in response to generative AI technologies being integrated into mainstream search and information retrieval systems.
Tools such as Ahrefs, Otterly.ai, Peec AI, Profound, Semrush, Scrunch, Similarweb, and Writesonic are used to monitor how websites and brands are cited, referenced, or incorporated into responses produced by large language models.
Practitioners also measure how often a brand is mentioned in AI-generated answers, which URLs or domains are cited in those answers, and a brandâÂÂs share of voice relative to competitors.
Nick Fox, Vice President of Google product recently stated that geo is really just SEO in a different guise. In an interview he said, âÂÂoptimizing for AI search is the same as optimizing for traditional search (SEO)âÂÂ.