Definition°

What is generative engine optimisation (GEO)?

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What is generative engine optimisation (GEO)?

Generative engine optimisation (GEO) is the practice of getting a brand cited and accurately described in AI-generated answers. There is no ranking position to win: a model retrieves a few sources and writes prose from them.

The definition, in full

Generative engine optimisation is the work of influencing what an AI assistant says about you. A buyer asks ChatGPT or Gemini which tools they should consider, the model retrieves a small set of sources, and writes an answer from them. GEO is everything that determines whether you appear in that answer, whether you are linked, and whether what is said about you is true.

The term was coined in a 2023 academic paper and has since been adopted by the industry as the umbrella label for this work. You will also see answer engine optimisation (AEO), LLM SEO and AI visibility used to mean broadly the same thing, with differences of emphasis rather than substance.

The word doing the most work in the definition is generative. A search engine returns a list and the user chooses. A generative engine composes an answer and the user often stops there. That single difference is what makes GEO a distinct discipline rather than a rebranding of SEO.

What GEO actually covers

  • Retrieval

    Whether your pages can be fetched at all. This is crawler policy, page speed, and whether the content is reachable without executing JavaScript. Blocking a retrieval crawler removes you from answers entirely, and it is the most common self-inflicted failure in the category.

  • Extraction

    Whether a model can lift a self-contained answer from your page. Retrieval selects passages, not pages, so an answer buried in the twelfth paragraph loses to a clearer one on a weaker site.

  • Entity clarity

    Whether a model can say what you are in one clause. Categories described differently on your homepage, your G2 listing and your LinkedIn page produce answers that hedge or substitute a competitor with a clearer description.

  • Off-site citation sources

    The largest component, and the one most often left out. An analysis of 5.7 million citation links across B2B SaaS prompts found the ten most-cited domains carry over a third of all citations, and eight of the ten are sites a vendor does not own.

  • Accuracy

    Whether what the assistant says is true. Being visible and wrong is worse than being invisible, and stale third-party listings are the usual culprit.

  • Measurement

    Whether any of the above can be shown to have worked. Model outputs are non-deterministic, so this needs a frozen prompt set, repeated runs and per-platform reporting rather than a single screenshot.

How GEO differs from SEO

The most useful way to hold the difference is that SEO optimises for a ranking function and GEO optimises for a retrieval-and-synthesis pipeline. There is no position to win, no algorithm to reverse-engineer in the usual sense, and no stable results page to measure against.

Three consequences follow, and they are the ones that catch teams out.

Where the two disciplines diverge
SEOGEO
Unit of selectionThe pageThe passage
What winsAuthority plus relevanceQuestion-answer fit, often over authority
Where the content livesMostly your own domainMostly domains you do not own
Result stabilityRankings move slowly and predictablyAnswers vary between runs and change with model releases
Failure modeNot rankingBeing described wrongly
MeasurementPosition, clicks, impressionsCitation rate, mention rate, share of voice, accuracy

Our position

GEO does not replace SEO and the framing of it as a successor is mostly marketing. Strong conventional search performance is a direct input to Google's AI surfaces, and a site that cannot be crawled cannot be retrieved. GEO is an additional discipline with its own failure modes, not a migration.

What actually moves it

The honest answer is that most of the work is not on your website, which is inconvenient for everyone selling it as an on-site service.

  1. 1Get the crawler directives right. Retrieval crawlers and training crawlers are different things, and blocking the wrong one removes you from answers while blocking the other does not.
  2. 2Find out which domains own citations in your category. This is directly observable on Perplexity, where the source list is visible, and it usually redirects the entire programme.
  3. 3Fix the third-party listings you control. A stale G2 profile propagates into answers on every platform, and it is routinely the largest single accuracy failure.
  4. 4Restructure pages so the answer sits in the passage a retrieval pass would pull. Answer first, qualify second.
  5. 5Build genuine presence on the sources that get cited: review platforms, community threads, publisher round-ups and video.
  6. 6Measure against a frozen prompt set, run repeatedly, reported per platform. Anything else is a screenshot.

What does not move it

  • llms.txt

    A log analysis of 137,000 domains in May 2026 found 97% of llms.txt files received zero requests, and Google stated in the same month that the file has no effect on Search visibility. It is one of the most commonly sold GEO deliverables and the evidence says it does nothing.

  • Keyword density and volume plays

    There is no ranking function to game. More pages saying the same thing dilutes rather than compounds.

  • Schema for its own sake

    Structured data helps a machine parse a page. It does not make a weak answer into a strong one, and it will not put you in a citation set you were never retrieved for.

  • Guaranteed placements

    Model outputs are non-deterministic and change between versions without notice. Anyone offering a guarantee here is describing something that cannot exist.

Related questions

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