What Is GEO? Generative Engine Optimisation vs SEO

The short answer

Generative engine optimisation (GEO) is the practice of making your content more likely to be used and cited inside AI-generated answers. Examples include ChatGPT search, Google AI Overviews and AI Mode, Perplexity and Gemini.

SEO aims to get your page ranked in a list of links. GEO aims to get your content into the answer itself. You don't have to choose between them. GEO builds on SEO, and the foundations are the same.

The rest of this article covers where the term comes from, what the research actually found, how GEO and SEO compare, and what it means for your website in practice.

Where the term comes from

"Generative engine optimisation" was named in a 2023 research paper. It is GEO: Generative Engine Optimization by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, first published on arXiv in November 2023 and presented at KDD 2024.

The authors called AI search tools generative engines: systems that fetch sources for a question, then use a language model to write one combined answer. Their concern was website owners, who have little control over when and how their content appears in those answers.

To study it, they built GEO-bench, a set of 10,000 queries across many domains, each paired with web sources. They tested nine ways of rewriting source content, measured how visible each source became in the generated answer, and repeated the experiments on Perplexity.

What the research found

• Some changes helped a lot. The best methods raised a source's visibility in the generated answer by up to 40%. That is a best case, not an average.
• Evidence helped most. The strongest methods were adding relevant statistics, adding quotations from credible sources, and citing reliable sources. All three are small edits.
• Keyword stuffing didn't work. It is a classic SEO shortcut, and it performed poorly.
• Results varied by topic. What worked best depended on the domain, so there is no single GEO checklist.
• Lower-ranked pages gained most. In their tests, GEO methods especially helped sources that ranked lower in traditional search.

Two cautions. This was a research setting with rewritten content, not a study of live business websites. And AI search tools have changed a lot since 2023. Treat the findings as direction, not a guarantee.

GEO vs SEO at a glance

• Goal. SEO: rank a page in search results. GEO: be used and cited inside an AI answer.
• What success looks like. SEO: a high position and a click. GEO: your business named, quoted or linked in the answer.
• How it's measured. SEO: rankings, impressions and clicks. GEO: mentions and citations across AI tools, and your share of answers.
• What the system reads. SEO: pages, links and relevance signals. GEO: passages it can extract, check and combine with other sources.
• Content that works. SEO: relevant, in-depth pages that match intent. GEO: clear, direct answers backed by evidence and sources.
• Technical basis. SEO: crawlable, indexable, fast pages. GEO: the same, plus clear entities and machine-readable structure.

Why SEO is still the foundation

AI answers are built from web pages that a system can find, fetch and trust. If a page can't be crawled or indexed, it can't be cited.

Google is direct about this for its own AI features. Its guidance on AI features and your website says, "There are no additional requirements to appear in AI Overviews or AI Mode." It also says the usual SEO fundamentals still apply. These include allowing crawling, making important content available as text, and linking pages internally.

So GEO is not a replacement for SEO. It's what you add once the basics are sound: content and structure that make your information easy to extract, verify and attribute.

GEO, AEO, LLMO: are they different?

You will see several names for overlapping ideas:

• GEO (generative engine optimisation): the research term, about visibility inside AI-generated answers.
• AEO (answer engine optimisation): an older industry term for optimising to be the answer, first for featured snippets and voice assistants, now for AI answers too.
• LLMO (large language model optimisation): another industry label for the same goal.

The names matter less than the work, which is largely the same under all three. We look at how AI systems choose which businesses to recommend in our AEO guide.

What GEO means for your website

In our work, the businesses that show up in AI answers are rarely the ones with the most content. They are the ones whose information is easiest to understand and verify. In practice, that comes down to five things.

1. Be a clear entity. AI systems need to know who you are before they can recommend you. Use the same name, services, location and contact details on your site and across the web, and connect them with structured data. Our article on keyword SEO vs entity-based SEO explains the shift.

2. Answer the question first. Put a direct answer near the top of each page, then the detail. A passage that answers a question on its own is easier to lift into a generated answer.

3. Back claims with evidence. This is the clearest lesson from the GEO research. Use real figures, cite credible sources, and quote people who can be checked. Don't pad pages with keywords.

4. Use structured data that matches the page. Schema.org markup doesn't guarantee a citation. But it removes doubt about what a page is, who wrote it and what it offers, provided it matches what the page actually says. See how structured data supports SEO and AI visibility.

5. Be mentioned elsewhere. AI answers often draw on third-party sources: directories, reviews, press and industry sites. Consistent mentions beyond your own site help systems confirm what you say about yourself.

On our own site, we apply the same approach:

• every page carries schema.org JSON-LD
• our robots.txt allows AI crawlers, except on the contact page
• we publish a plain-text summary at /llms.txt and compact JSON data through our AIDI endpoints

We call the overall discipline machine legibility: making a website easy for machines to read, interpret and reuse correctly. Our article on what an AI interpretation layer is goes further.

How to tell if you are visible in AI answers

Start simple. Write down 10–20 questions a customer might ask before choosing a business like yours. Put them to ChatGPT, Google (AI Overviews and AI Mode), Perplexity and Gemini. Note which businesses are named and which sources are linked. Repeat every month or two, because answers change.

If you are missing, or a competitor is named instead, the cause is usually one of the five areas above. Our article on why competitors show up in AI answers covers the common reasons.

For a full assessment, our AI Visibility Audit covers entity clarity, structured data, content architecture and prompt testing across those four assistants. It ends in a prioritised report and a walkthrough call.