GEO (Generative Engine Optimization)

GEO (Generative Engine Optimization) is the practice of optimizing a brand and its content so that generative engines —ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews— mention, cite and recommend it when a user asks a question in its category. It is the equivalent of SEO for the AI-answer era: instead of competing for a spot on Google's first page, you compete to be part of the answer the model generates.

Why does GEO matter?

More and more people discover products and services by asking an AI assistant directly instead of searching Google. If the model does not know your brand, it does not name it —and there is no second result for the user to scroll to. AI visibility becomes binary: you are in the answer, or you do not exist for that buyer.

How do you do GEO?

• Structure content as clear question-and-answer pairs (FAQ) the model can quote verbatim.
• Build entity signals: a consistent profile across Wikidata, LinkedIn, directories and press.
• Publish an llms.txt file that summarizes what the brand is and what it does.
• Earn mentions and citations on the domains LLMs already treat as authorities in your sector.
• Monitor how often and in what position each engine names you, and close the gaps.

GEO, AEO and SEO

GEO overlaps with AEO (Answer Engine Optimization) —many teams use the terms interchangeably— and builds on technical SEO fundamentals, but it optimizes for a different target: the generated answer, not the blue link. See GEO vs SEO for the full comparison.