What is Generative Engine Optimization (GEO)?
GEO is the practice of getting your brand recommended inside AI assistant answers. Here's what it is, why it's exploding, and how it differs from SEO.
5 min read
The short definition
Generative Engine Optimization (GEO) is the practice of influencing whether — and how prominently — your brand appears when people ask AI assistants like ChatGPT, Claude, Gemini and Perplexity for recommendations.
Where SEO is about ranking links on a results page, GEO is about being one of the handful of names an AI names directly in its answer. There is no page two. If you're not in the answer, you're invisible.
Why it matters now
Hundreds of millions of people now start product research inside an AI assistant instead of a search box. They ask 'what's the best CRM for a small team?' and act on the three or four names that come back.
That shifts the buying decision earlier and narrows it faster. Traditional analytics can't see any of it — there's no keyword, no click, no referrer. The first signal most brands get is a competitor quietly winning deals.
How GEO actually works
AI assistants assemble answers from what they learned in training and, increasingly, from live web results. Brands that are described clearly and consistently across the web — their own site, third-party roundups, reviews, Wikipedia, Reddit, comparison pages — are the ones models can confidently recommend.
GEO is the work of making your brand legible to those models: clear positioning, citable third-party mentions, structured comparison content, and the kind of specific, factual claims a model can repeat without hedging.
Where to start
Measure first. Run the questions your buyers actually ask across each AI engine and record whether you're mentioned, where you rank, and who beats you. That baseline tells you exactly which prompts and which engines to work on.
Then track it over time — visibility moves as competitors publish content and models update. GEO isn't a one-off project; it's a position you defend.