What is generative engine optimization (GEO)? Definition and scope

Semrush states the difference from ordinary SEO in one clause: "you aren't competing to rank at the top of search results in GEO, you're competing to be part of the final output."

The other "geo" in SEO

Half the people typing "what is geo in SEO" mean something else entirely: geography. In that sense geo covers geo-targeting an ad or a landing page, local SEO for a business with a service area, and country or language targeting through hreflang and Search Console settings. It is an older, unrelated use of the same three letters, and it is not what the rest of this page is about.

Where the term came from

GEO is one of the few AI-search coinages with a paper behind it rather than a vendor. "GEO: Generative Engine Optimization", by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, was submitted to arXiv in November 2023 — researchers from Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi. It framed GEO as "a novel paradigm to aid content creators in improving the visibility of their content in Generative Engine responses through a black-box optimization framework", and introduced GEO-bench, a benchmark of queries used to test nine optimisation tactics.

The headline finding — that GEO "can boost visibility by up to 40% in generative engine responses", with adding citations, quotations and statistics the tactics that helped most — is the number everyone repeats, and it deserves its caveats. The tests ran on a simulated generative engine across roughly 10,000 queries, not on ChatGPT or Google. Search Engine Land, covering the paper at the time, said it plainly: following the framework "won't guarantee success or greater visibility in Google's AI experience."

What the paper genuinely established is narrower and more durable than the percentage: content that is specific, sourced and quotable gets pulled into generated answers more often than content that is not. That is the whole of GEO, and everything below is an implementation detail.

What GEO covers, and what it does not

In scope. Being named, quoted or linked inside a generated answer. The unit of success is a citation or a mention, not a position.

Out of scope. Ranking in the ten blue links — that is ordinary SEO, and it remains the route by which most generative engines find you at all. Also out of scope: paid placement in AI products, and using AI tools to do SEO work. The last one causes most of the confusion, because "AI SEO" gets sold as both.

Adjacent and often confused. GEO, LLM SEO, answer engine optimization and AI search optimization name one practice from different angles, and Search Engine Land's hierarchy is the cleanest sorting of them: "AI search is the environment; AI SEO is the practice; AI visibility is the outcome. GEO sits inside AI SEO as one way to improve visibility within generative systems." GEO's angle is the engine's — what makes a passage worth assembling into an answer. AI search optimization covers how those engines retrieve, LLM SEO the passage-level craft, AI visibility the measurement. Nobody should sell you four services.

What a GEO effort actually consists of

For a small business it is three unglamorous workstreams.

On the page. Answer the question in the first paragraph, in a sentence that survives being lifted out of context — Search Engine Land's phrasing is self-contained paragraphs that "retain meaning when read in isolation", under clear descriptive headings, with the main point front-loaded. Support claims with specifics and cite the sources. This is the part the original paper actually tested.

Off the page. Describe your business the same way everywhere — site, directories, profiles, review platforms — because a model assembles its picture of you from all of them and averages the differences into vagueness. Semrush notes that unlinked brand mentions appear to carry weight for these systems even without a link, which makes being discussed in the places your buyers read a genuine input rather than a vanity metric.

Measurement, such as it is. There is no rank to check. You sample: run a set of prompts a customer might ask, record whether you appear and in what terms, and repeat monthly. Semrush's own index puts the volatility bluntly — between 40 and 60 per cent of cited sources change month to month — so read the trend, never a single run.

The limits follow from that last point. No agency can guarantee a citation, because nobody outside the model's operator can see the selection, answers differ between users and sessions, and the same prompt asked twice can produce different sources. GEO is a set of odds-improving practices, not a lever.

How Structura handles this

Structura works the on-page column and nothing else. Each post opens with a direct answer to the query it targets, keeps a sequential heading structure, cites external sources from authority domains — each URL checked before publishing, so nothing quotes a dead page — and ships Article and FAQ structured data. Because posts come off a keyword bank on a cadence, a subject gets covered across many related queries rather than in one page, which is what gives a generative engine something to retrieve whichever way it phrases its sub-questions.

That is deliberately the narrow half. Structura does not track whether models cite you: there is no prompt set, no share-of-voice report, no AI mention monitor. It connects to Google Search Console and reports classic performance, which is the half you can act on. For citation tracking you need a separate tool.

Nor can it do the off-page work — consistent brand descriptions across the web, being talked about in communities, first-hand experience only your business has. That is PR and product, not publishing, and a tool claiming otherwise is describing spam. The AI SEO page sets out which parts are actually in the product.

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