Definition
What is generative engine optimization (GEO)?
Generative engine optimization (GEO): Generative engine optimization (GEO) is the practice of making a business accurately findable and citable by AI answer systems (Google AI Overviews and AI Mode, ChatGPT search, Perplexity, Copilot, Claude) by publishing precise, well-structured, machine-readable content on a fast, crawlable website.
Also called: GEO, AI search optimization, answer engine optimization, AEO, LLM SEO.
Published
How GEO differs from SEO
Google’s own guidance says AI-search optimization is not a separate discipline: the fundamentals that earn a ranking also earn a citation, and there is no special file, tag, or trick that substitutes for them. The differences are of emphasis:
| Aspect | Classic SEO | Generative engine optimization |
|---|---|---|
| Unit of competition | The page | The passage: a heading plus an answer-first sentence, a table, a definition |
| Who fetches | Googlebot, Bingbot (render JavaScript) | The same, plus retrieval bots (OAI-SearchBot, Claude-SearchBot, PerplexityBot) that read raw HTML only |
| What is rewarded | Relevance, authority, experience | Precision, first-party facts, extractable structure, entity clarity |
| How it is measured | Rankings and clicks | Impressions in AI reports, citation presence across sampled prompts |
What actually works
Server-rendered HTML with the answer in the first screenful; one truthful schema graph per page; a consistent entity register so your name, hours, and services are stated once, everywhere; fragment-anchored sections; fast pages; and content that contains information a model cannot get elsewhere: your prices, your process, your data.
What does not
llms.txt files (no platform consumes them), markdown mirrors of your site, invented schema types, synthetic Q&A pages, and anything aimed at manipulating a model rather than informing it. See the SEO & AI search service for how Hyrizen applies this.