Fundamentals
What Is Generative Engine Optimization (GEO)?
SEO optimizes for a list of ten blue links. GEO optimizes for a single synthesized answer. Here's what actually changes.
5 min read
The shift from ranking to citation
Classical SEO's unit of success is a ranking position: where does your page land on a results page a human then scans and clicks through. Generative Engine Optimization (GEO) — sometimes called AEO, Answer Engine Optimization — has a different unit of success: whether your brand, product, or page gets named inside the single synthesized answer an AI model gives, often with no click required at all. A page can rank #1 in classic search and still never be mentioned in ChatGPT's answer to the exact same question, because the two systems select and present information in fundamentally different ways.
Retrieval, then synthesis
Most AI answer engines — ChatGPT with browsing, Perplexity, Google's AI Overviews — work in two stages. First, retrieval: the system runs a search (often a real web search) to gather a handful of candidate sources for the query. Second, synthesis: a language model reads those retrieved sources and writes a single answer, choosing which sources to name, quote, or link. Winning at GEO means winning both stages — first getting retrieved as a candidate source at all, then being the source the model actually chooses to cite in its synthesis.
What actually influences citation
Being retrieved depends on the same fundamentals search engines have always rewarded — real content depth, topical relevance, and enough authority signals that a search index surfaces the page as a plausible source. Being cited once retrieved is the newer, less-understood layer: models tend to favor sources that answer the question directly and unambiguously near the top of the page, that are corroborated by other independent sources saying similar things (a claim repeated across several trusted pages is safer for a model to cite than a claim appearing on only one page), and that are structured in a way that's easy to extract a clean answer from — direct statements, clear headings, defined terms, and comparison tables read more easily by an extraction step than long unstructured narrative prose.
Why this needs its own measurement
Because GEO's unit of success (being named inside an answer) isn't visible in any classic SEO tool, it has to be measured directly: running your actual customer questions against the actual engines your customers use, and checking whether your brand gets named, how often, and against which competitors. That's the entire premise of Anovox's core loop — see the free check at /check or the full methodology in "How AI Search Engines Decide What to Cite."