What is the smallest useful first step?

Make sure the assistant can actually fetch the page. Retrieval-based assistants read live pages through named crawlers, and a page blocked in robots.txt, or carrying a nosnippet rule, is removed from the pool before any of the writing matters.

Generative engine optimization (GEO) - AI SEO & GEO Glossary

Q: What does the 40% figure actually measure?

It is the headline result of the 2023 paper: applying its methods boosted visibility by up to 40% in generative engine responses, measured on GEO-bench, the benchmark the same authors built. It is a research result on one benchmark, not a promise for any particular site.

Q: How do you measure GEO when there is no ranking?

By sampling. A generated answer has no position you can look up, so measurement means running a set of representative prompts repeatedly, recording which sources the answer names, and watching that distribution move. It is a sampling problem rather than a reporting one, which is why the numbers carry a margin of error rather than a rank.

Generative engine optimization is the practice of getting your material reproduced inside an answer that a model generates, rather than getting a link ranked on a page of results. The term is not marketing shorthand: it was introduced in a 2023 arXiv paper by Aggarwal and colleagues, which describes GEO as the first novel paradigm to aid content creators in improving their content visibility in generative engine responses, and reports that its methods boosted visibility by up to 40% on GEO-bench, a benchmark of user queries and their relevant web sources that the same paper introduced.

The distinction that makes the term worth having is the unit of success. Search engine optimization succeeds when a person clicks through from a results page. Generative engine optimization succeeds when a model reproduces your sentence, names your organisation, or lists your URL among its supporting links — whether or not anyone clicks anything at all.

Why it matters

Two things changed at once. Answers began appearing above the links, and a large share of question-shaped traffic moved into assistants that never present a list of links in the first place. In a Pew Research Center analysis of 68,879 Google searches performed by 900 US adults in March 2025, 18% of searches produced an AI summary, and users who saw one clicked a traditional search result in 8% of visits against 15% for visits without one.

That is the commercial pressure. The technical pressure is different and more tractable: an assistant that answers from retrieval has to fetch a page, and it fetches under a named user agent that you can allow or refuse. What you publish and what you allow are both inputs to the same outcome.

How it differs from SEO, and from AEO

Generative engine optimization is often used interchangeably with answer engine optimization and with SEO. They are not the same claim.

SEO is Google's own term for helping search engines understand your content and helping users decide whether to visit your site. Its output is a ranked link.
GEO targets the generated passage. Its output is a sentence in someone else's prose, sometimes with a citation attached, sometimes not.
AEO, answer engine optimization, is the older and looser label, generally used for direct answers of any kind including featured snippets. GEO is narrower: it is specifically about text a model composes.

The practical overlap is largest on Google, which states plainly that there are no additional requirements to appear in AI Overviews or AI Mode and no other special optimizations necessary, and that a page must be indexed and eligible to be shown with a snippet to appear as a supporting link. It is smallest on assistants that maintain their own index and their own crawler. The full argument is laid out in GEO vs SEO.

How to act on it

Check access before writing. Decide deliberately which crawlers may fetch you. The training crawler and the search crawler are usually different bots with different consequences — see GPTBot vs OAI-SearchBot and AI training vs AI retrieval.
Check your snippet rules. A nosnippet rule removes a page from Google's AI experiences as well as from ordinary snippets. noindex vs nosnippet sets out what each one costs you.
Write things that can be quoted. A generated answer reproduces specific sentences. Numbers with sources, named mechanisms, explicit comparisons and direct statements survive that process; positioning adjectives do not.
Measure by sampling, not by rank. Fix a prompt set, run it on a schedule, record which sources appear. Treat movement as a distribution shifting, not as a position changing.

Attensira exists at step four and the follow-through: it samples prompts across assistants, reports where you are and are not cited, and opens a pull request against your repository with the suggested change for you to review.

Frequently asked questions

Where does the term generative engine optimization come from?

From a paper published on arXiv in November 2023 and revised in June 2024, which introduced GEO as the first novel paradigm to aid content creators in improving their content visibility in generative engine responses. It is an academic coinage, not a vendor one.

Is GEO a rebrand of SEO?

No, though on Google's own surfaces the work overlaps almost entirely. On assistants that do not run Google's index, the overlap is much smaller.

What does the 40% figure actually measure?

It is the headline result of the 2023 paper, measured on GEO-bench, the benchmark the same authors built. It is a research result on one benchmark, not a promise for any particular site.

How do you measure GEO when there is no ranking?

By sampling a fixed prompt set repeatedly and recording which sources each answer names.

Generative engine optimization (GEO)