Generative Engine Optimisation (GEO)

Is generative engine optimisation different from AEO?

No. Generative engine optimisation (GEO) and answer engine optimisation (AEO) describe the same discipline: making a company's information retrievable and citable by systems that write an answer instead of returning a list of links. "AI search optimisation" — or optimization, in the American spelling — is the same thing again in plainer words.

The terminology diverged because two communities named the problem independently. GEO is the label that came out of research; AEO is the label that came out of practice. Neither describes a technique the other lacks. This page takes the research-side view, because the mechanics are worth understanding before you buy anything. If you want the service rather than the explanation, it is here.

Where did the term GEO actually come from?

From a 2024 paper. Pranjal Aggarwal and colleagues at IIT Delhi and Princeton University published GEO: Generative Engine Optimization, accepted to KDD 2024, which introduced both the name and GEO-Bench — a benchmark of 10,000 queries used to test whether specific writing changes altered how often a source was drawn on in a generated answer.

That matters commercially for one reason: it means the category has a public, citable, methodologically explicit starting point rather than a set of agency claims. You can read the paper and disagree with it. That is not true of most of what is written about this subject.

What did the GEO research find?

The paper tested nine optimisation methods. Its three best performers were adding quotations, adding statistics and citing sources, and it reports those producing a relative improvement of 30–40% on its Position-Adjusted Word Count metric and 15–30% on its Subjective Impression metric. The authors also note that effectiveness varies by domain, which is an argument against applying any of it as a blanket recipe.

Two cautions worth stating plainly. Position-Adjusted Word Count measures how prominently a source is drawn on inside a generated answer within a research benchmark. It is not revenue, not traffic, and not a result at any particular company. And the finding only holds if the quotations and statistics are real — engines cross-reference claims, and a figure that cannot be traced to a named source undermines the trust signal it was meant to create. The tactic is genuine sourcing, not the appearance of it.

How does a generative engine assemble an answer?

Through retrieval-augmented generation. The sequence is worth knowing, because every optimisation decision follows from one of these steps:

1. The question is embedded. It is converted into a vector — a numerical representation of meaning rather than of words — so matching is semantic, not literal keyword matching.
2. Passages are retrieved. The system searches an index for chunks of text whose vectors sit close to the question's. The unit retrieved is a passage, not a page.
3. A context window is assembled. The top-ranked passages, from several different sources, are placed in front of the model as working material.
4. An answer is generated. The model writes prose from that material and attaches citations to the passages it leaned on.

The consequence for your website is the second step. A page that only makes sense read from the top does badly, because the chunk that gets retrieved arrives without the paragraphs that set it up. A section that answers its own heading, defines its own terms and carries its own source attribution survives the trip intact.

Why does "self-contained" matter so much?

Because a retrieved passage has no context except itself. If a section opens with "this approach also helps with…", the engine has no idea what this refers to and the passage is close to useless as an answer. If a section quotes a percentage without naming the source in the same sentence, the figure arrives unattributable — and an unattributable figure is one a careful system will decline to repeat.

That is why the pages on this site are written the way they are: question-shaped headings, sections that resolve their own pronouns, every statistic naming its source inline. It is not a house style. It is the format the retrieval step rewards, and you can inspect the markup on any page here to check I actually do it.

Does any of this replace ranking in classic search?

No, it sits on top of it — see why SEO is still the floor. What has changed is that ranking no longer implies citation. Ahrefs found in March 2026 that 38% of pages cited in Google's AI Overviews also ranked in the top ten for the same query, down from 76% in July 2025. Both layers now need attention, and the second one is not a by-product of the first.

What should I ask an agency selling GEO?

The acronym on the proposal tells you very little. These four questions tell you a lot:

• How do you build the prompt set, and do I get it in writing before you start?
• What exactly counts as a citation in your reporting?
• Which engines do you check separately, rather than blending into one score?
• What is in the recurring report, and what happens to it if I stop working with you?

There is a longer version of this in the questions worth asking before hiring anyone for this.

What to do about your own situation

Before commissioning any of it, find out empirically whether the engines currently name you, and which sources they use when they name someone else.

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