Guides · 2026-08-28 · By VSNARY | Emmanuel Orta
GEO, AEO and LLM SEO: what the terms mean and which parts can be measured
Three names for one shift, sold as three disciplines. The distinctions are mostly marketing; the useful split is between the parts of the work that produce a checkable number and the parts that do not.
Every term in this guide belongs to one of three stages
Generative engine optimization (GEO), answer engine optimization (AEO) and LLM SEO are three names for the same shift: a growing share of questions about your business are now answered without anyone visiting your site. Practitioners will offer distinctions — AEO leaning toward featured snippets and direct answers, GEO toward generated prose, LLM SEO toward the models specifically. In practice the work overlaps almost completely, and which term someone uses tells you more about when they entered the field than about what they do.
The distinction worth drawing is different, and it cuts across all three labels.
The split that matters
| Verifiable | Inferred | |
|---|---|---|
| Question | Can the retrieval layer read you? | Are you named in answers? |
| Measured by | Fetching your site as a non-browser client | Sending prompts to model APIs |
| Result | A status, a content type, a ratio | A percentage over a chosen prompt list |
| Reproducible by you | Yes, with curl | Only approximately, and it moves |
| Who sells it | Almost nobody | Almost everybody |
Both halves are legitimate. The problem is that the second is routinely presented with the confidence of the first. A share-of-voice figure is a statistic over prompts somebody guessed at, produced by querying an API that is not the consumer product anyone actually uses, on a day the model happened to be in a particular state. Change the prompt list and the number changes. That is not a flaw in the arithmetic — it is what the arithmetic was always describing.
How it differs from SEO, honestly
Less than the branding suggests, and more than the sceptics allow.
What carries over: being crawlable, being fast, being genuinely useful, having other people reference you. None of that stopped mattering.
What is genuinely new: there is no position to hold. A ranked list has slots; an answer has a paragraph and maybe a citation. You are either used or you are not, and the binary is harsher than page two.
What is new and mostly unmeasured: the cost side. Every SEO tool measures what a page says. Almost none measure what a machine is handed when it asks for that page. The heaviest page measured here delivered 476,540 bytes carrying 2.3% visible text, and no validator had an opinion about it.
The measurable work, in order
Whatever the label on the invoice, this is the part that produces numbers you can check.
Reachable. Does the fetch succeed for that specific crawler? ANSWER_ENGINE_REFUSED fires on 3.4% of scans, and 15.0% carry an AI opt-out — much of it inherited rather than chosen, given that the eight largest opt-out groups on the web sit within 12% of each other.
Readable. Is what came back parseable? A cached challenge page at HTTP 200 reads as allow-everything. STALE_CACHE_SERVED fires on 30.9% of scans, the most common defect in the dataset.
Quotable. Is there enough text to use? 13.7% of scans return a page that is overwhelmingly code.
Resolvable. Can you be told apart from similar entities, and are the specific facts declared? Organization is detected on roughly 354,000 sites web-wide; OpeningHoursSpecification on roughly 23,000.
What the people selling it have done to their own sites
Thirty-three SEO and AI-visibility vendors were run through a supply-side scanner — the same battery they would point at a customer, on the same day, none told in advance.
| Best vendor site measured | 92 of 100 |
| Worst that completed a scan | 41 |
| Publish an llms.txt | roughly one in three |
| Publish an entity map | none |
| Median payload | under one visible word per 20 bytes |
Several were serving a cached machine file that no longer matched their own origin, meaning a crawler and a human get told two different things by a company that sells judgement about exactly that. The point is not that they are bad at their jobs — it is that these checks are not specialist requirements, and the people closest to the advice mostly have not implemented it.
The number no single audit can produce
Whatever the label, most of this is sold as an audit: a report on a day. Across 48 sites measured every day for fifteen days, 68.8% carried a defect on the final day and 93.8% carried one at least once. A 25-point gap, and twelve sites looked clean at the end that had not been clean throughout.
A one-off engagement at any budget can only ever produce the first figure. The second requires the same sites to have been watched before anyone asked the question — which is a difference in kind, not in thoroughness.
The test to apply to anyone selling any of the three
Ask what would have to be true for their number to be wrong, and how you would find out. If there is no answer, it is not a measurement — it is a label. A percentage you cannot check is a claim about something nobody measured.
Then ask which surface was queried, which model in which mode, and on what date. Grounded retrieval and generation from weights are different systems and averaging them produces a number about neither.
None of this makes the category fake. It makes most of the reporting in it softer than it is presented, while the hard, checkable half — the part where a server either answers a crawler or does not — is sitting there almost entirely unsold.
Every figure above came out of this scanner.
Point it at your own domain and see the same measurements, free.
Questions this post answers
What is the difference between GEO, AEO and LLM SEO?
Very little in practice. All three describe optimising for answers generated without a click. The more useful distinction is between work that produces a verifiable measurement, such as whether a crawler can fetch and parse your site, and work that produces an inferred one, such as a share-of-voice percentage over a chosen prompt list.
Is generative engine optimization real, or is it rebranded SEO?
The underlying shift is real: answers increasingly replace result pages, and there is no ranked position to hold. Much of the practice carries over from SEO. What is genuinely new and mostly unmeasured is the cost side, meaning what a machine is actually handed when it requests your page.
Where should I start with GEO or AEO?
With the checkable layer, in order: whether the fetch succeeds for each crawler, whether what comes back is parseable, whether enough of the payload is quotable text, and whether your entity and its specific facts are declared. Buying answer monitoring before that measures an outcome that is not yet possible.