GEO vs SEO: what actually differs, and what does not

What actually separates GEO from SEO

The two terms optimise for different definitions of a win. SEO is Google's own word for helping search engines understand your content and helping users find your site and decide whether to visit it. GEO was coined in a 2023 research paper for improving how often your material appears inside a generated response. One ends in a click. The other can end without one.

That is the whole distinction, and most of what is written about this pairing is either an elaboration of it or a confusion about it.

Where each term comes from

GEO has an unusually precise origin for a marketing term. It was introduced in the paper "GEO: Generative Engine Optimization", submitted to arXiv in November 2023 by Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande, and last revised in June 2024. The paper describes GEO as the first novel paradigm to aid content creators in improving their content visibility in generative engine responses through a flexible black-box optimisation framework. It also ships a benchmark, GEO-bench, so that the claims in it can be checked by somebody else.

The canonical definition of SEO is not academic. It comes from the party that operates the largest search engine: Google's own SEO starter guide. That difference in provenance matters more than it looks. A definition written by a platform tells you what the platform wants you to do. A definition written by researchers tells you what they measured. Neither is neutral, and they are not neutral in the same direction.

The evidence bases are not comparable

The single number everyone quotes about GEO, a visibility boost of up to 40%, is a benchmark result rather than a market statistic. The abstract says the methods can boost visibility by up to 40% in generative engine responses, measured on GEO-bench. It is real, dated and checkable, and it is also domain-dependent: the same paper reports that the efficacy of these strategies varies across domains, underscoring the need for domain-specific optimisation methods.

SEO has no equivalent headline figure, because nobody publishes a controlled benchmark for it. What Google publishes instead is a warning about latency: some changes might take effect in a few hours, others could take several months. That is the honest shape of SEO evidence, a long and noisy feedback loop in which attribution is genuinely hard.

So when a blog post sets a GEO number beside an SEO number, it is usually comparing a benchmark result with an anecdote. Both can be true. Neither is the other's control group.

Where the distinction collapses: Google's own surfaces

This is the part most treatments of these two terms get wrong, and it is checkable in a single document.

Google's guidance on AI features states plainly that there are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimisations necessary. It goes further: while specific optimisation is not required for AI Overviews and AI Mode, all existing SEO fundamentals continue to be worthwhile. And it names the prerequisite, which is that a page must be indexed and eligible to be shown in Google Search with a snippet.

Read together, that is a platform saying that on its surfaces GEO is SEO. If your page is not indexed it cannot appear in an AI Overview. If it is indexed and snippet-eligible, there is no separate lever Google is willing to name.

Treat that statement as what it is: a platform's public position, not a law of nature. It tells you what Google will commit to in writing. It does not tell you what its ranking systems weigh, and it says nothing at all about the assistants that do not run Google's index.

Where the distinction is real: everywhere else

An assistant that fetches pages on demand, or answers from a model's parameters, or retrieves from an index nobody outside the company has seen, is not bound by Google's documentation. Three things change once you leave Google's surfaces.

There is no rank. A results page has ten positions and you occupy one of them. An answer has a set of sources it drew on and a body of text it produced. Being in position four is not a state that exists.

There is no guaranteed click. The outcome you are optimising for may be a sentence that describes your product accurately to somebody who never visits your site. That is a real commercial outcome and it is invisible to any tool that counts sessions.

Observation becomes sampling rather than reporting. Because the engines are, in the paper's own words, black-box, you cannot query a console for your visibility. You ask the question many times and record what comes back. That is a statistical exercise with a sample size and an error bar, and any tool presenting it as a single precise percentage is over-claiming.

What the work looks like in practice

The technical floor is shared and non-negotiable: be crawlable, be indexable, be fetchable, do not hide the content behind a login or a paywall, and do not block the crawlers whose answers you want to appear in. Every item in that list is SEO work by any definition, and it is also the precondition for every generative surface.

Above that floor the emphasis genuinely diverges. Optimising for a click rewards a compelling title and a reason to leave the results page. Optimising to be quoted rewards sentences that survive extraction on their own: a specific claim, with a number, attributed to a source, that still means the same thing outside its paragraph. A page written to tease the click and a page written to be quoted are not the same page, and this is the one place where your choice of frame changes what you actually type.

Measuring each one honestly

For SEO the instruments exist and they are boring: impressions, positions, clicks, and the acceptance that a change may take months to surface.

For GEO there is no console. You assemble a set of prompts that represent how your buyers actually ask, you run them repeatedly across the assistants you care about, and you record whether your material appears and how it is described. Repeated sampling is the method because the systems are non-deterministic, and a single run tells you close to nothing. The metrics that fall out of it, such as citation probability, reference rate and AI brand mentions, are estimates from a sample and should be reported with the sample size attached.

Three claims about this pairing that are usually wrong

"GEO is a rebrand invented by tool vendors." The term predates the tooling market. It was introduced in a peer-reviewed-style research submission in November 2023, with a benchmark attached, by academics with no product to sell. You can disagree with the paper's methods. You cannot honestly call the term marketing invention.

"Google has confirmed GEO is real and separate." It has confirmed the opposite, in writing, for its own surfaces. The documentation says there are no additional requirements to appear in AI Overviews or AI Mode and no other special optimisations necessary. Anyone citing Google as an endorsement of a distinct GEO discipline is citing a document that says the reverse.

"SEO is dying, so the comparison settles itself." Google's guidance ties its AI features to the same index, the same crawl, the same snippet eligibility. The pipeline that decides whether you are eligible for a generated answer on Google is the SEO pipeline. A discipline whose output is the precondition for the successor surface is not dying; it is being repriced, because the click it used to deliver is no longer guaranteed.

Where the two disciplines disagree about the same page

Take a pricing page as the test case. The SEO reading asks whether it ranks for category-plus-pricing queries, whether the title earns the click, and whether the internal links funnel authority to it. The GEO reading asks a narrower and harder question: if a model is asked what this product costs, is there a sentence on the page it can lift that answers it correctly and unambiguously?

Those two readings routinely produce opposite verdicts. A pricing page with a tiered slider and no plain-text numbers can rank perfectly and be entirely unquotable, because there is no sentence to extract. A modest FAQ entry that says the price in words, with the plan name and the currency, is nearly useless for ranking and extremely useful for being quoted.

That is the practical payoff of holding both frames at once. They audit different failure modes of the same page.

Which frame to argue for internally

If your team already runs an SEO programme, do not rename it. Add a second scoreboard beside the first one, because the two scoreboards disagree in a useful way. A page can rank third and never be quoted. A page can rank nowhere and be the source an assistant reaches for, because it happened to contain the one concrete sentence that answered the question. Watching both numbers on the same page is how you learn which of your pages are extractable and which are merely rankable.

If your team has no SEO programme at all, start with the floor. Nothing above it compounds until crawling and indexing work.

The honest verdict

If you are paid for clicks, keep calling it SEO and keep doing it, because Google says the fundamentals still apply to its AI features and because an unindexed page is invisible everywhere. If your buyers have stopped clicking and started asking, the GEO frame is the more useful one, because it points at the thing you actually need, which is appearing inside the answer, rather than at a rank that no longer determines whether you are seen.

And if your material has nothing specific in it, neither frame will help. Models reproduce sentences. Give them a sentence worth reproducing.