Glossary
Generative Engine Optimization (GEO)
Generative engine optimization (GEO) is the practice of getting a brand named or cited inside AI-generated answers from engines such as ChatGPT, Perplexity, Gemini and Google AI Overviews. It targets the content structure and entity signals those engines read when they choose which sources to quote.
GEO and traditional search optimization aim at different outcomes. Ranking puts a page high in the list of blue links. GEO gets the page mentioned or quoted inside a synthesized answer, where an engine names only a few sources and a user may never scan a full results page. The unit of success moves from position to citation.
The work runs on structure and trust. Question-led headings with a direct answer in the first sentence, comparison tables, and pages with clear Organization and author signals are easier for an engine to lift and attribute. Schema markup and an llms.txt file help engines parse a page, but neither decides a citation on its own.
Common questions
How is GEO different from SEO?
SEO works to rank a page among the blue links. GEO works to get the page named or quoted inside an AI answer, where the engine cites only a handful of sources. They share a base of content quality and authority, but GEO weights extractable structure and entity clarity more heavily.
How do you measure GEO?
You track how often a brand appears in answers across a set of prompts, which engines include it, and which pages those engines cite. CiteSurge runs that check across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews and reports a share-of-answer figure for each.