Generative Engine Optimization (GEO)
Also known as: GEO
Generative Engine Optimization (GEO) is the practice of getting a brand named or cited in AI-generated answers from ChatGPT, Claude, Perplexity, and Gemini.
GEO emerged in 2024–2025 as buyers began routing the discovery phase of their journey through conversational AI rather than traditional search. The discipline targets four primary surfaces: ChatGPT, Claude, Perplexity, and Gemini, along with the AI Overviews layered on Google and Bing. Where SEO scores rank in a list of links, GEO scores being the brand named in the synthesized answer.
The core metrics are mention rate (how often your brand is named), citation rate (how often your domain is linked as a source), and share of voice (mention rate relative to direct competitors). Improving them requires a custom prompt universe, multi-surface sampling, content shaped for direct extraction, and structured data that reduces parsing cost.
GEO overlaps heavily with traditional SEO at the foundational level — both reward specific claims, authority signals, and clean structured data. The 30% of work specific to GEO is what defines the discipline: prompt-universe definition, weekly sampling, share-of-voice tracking against named competitors, and source-grounded content generation.
FAQ
What is generative engine optimization in simple terms?
GEO is making your brand the brand that AI assistants name when buyers ask category-relevant questions. It's the AI-era analog of getting a Google ranking, but the reward is binary: named or not.
How does GEO differ from SEO?
SEO scores rank in a list of ten links. GEO scores being the brand named in a single generated answer. The fundamentals overlap; the discipline-specific work — prompt universes, multi-surface sampling, mention-rate tracking — is what makes GEO distinct.
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