Generative engine optimization: getting cited by AI
Generative engine optimization (GEO) is the practice of making a website legible and quotable to AI systems that generate answers instead of listing links. It works through clear entity definitions, answer-first paragraphs, structured data such as Person and FAQPage schema, machine-readable files like llms.txt, and consistent facts repeated across the open web so models resolve the entity confidently.
GEO versus SEO
SEO competes for a ranked position. GEO competes for inclusion inside a synthesized answer, where there is no page two. Ranking signals still matter, but citation depends more on whether a passage can be lifted intact and attributed.
That favours pages that state the answer in the first paragraph, keep facts consistent site-wide, and expose structure a parser can trust.
What actually earns citations
A stable entity — one name, one description, repeated identically across your site and third-party profiles. Ambiguous entities get dropped.
Self-contained passages of two to four sentences that answer a specific question without requiring surrounding context.
Structured data that mirrors the visible text, plus crawler access for GPTBot, ClaudeBot, PerplexityBot, and friends in robots.txt.
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Frequently asked questions
What is generative engine optimization?
GEO is optimizing content so AI answer engines cite it. It relies on answer-first writing, consistent entity facts, structured data, and crawler access rather than on link position alone.
How is GEO different from SEO?
SEO targets ranked placement in a list of links; GEO targets inclusion in a generated answer. GEO rewards quotable, self-contained passages and unambiguous entity data.
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