What Is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the practice of shaping your content so that AI systems that write answers, such as ChatGPT, Perplexity, Gemini, Claude and Google’s AI Overviews, can find it, understand it and cite it. Where classic SEO tries to win a position in a list of links, GEO tries to win a mention inside a written answer. The two overlap a lot, and GEO does not replace SEO.

What is a generative engine?

A generative engine is a search or answer system that retrieves information from the web and then writes a response in natural language, usually with links to the sources it used. ChatGPT search, Perplexity and Google’s AI Overviews are examples. Users read one composed answer instead of scanning ten links. So the site owner’s question shifts from “do I rank?” to “is my page one of the sources behind that answer?”

Where does the term GEO come from?

The term comes from research. In November 2023, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande posted “GEO: Generative Engine Optimization” to arXiv. The paper was accepted to KDD 2024. It defines GEO as a framework for helping content creators improve their visibility in generative engine responses, and it introduces GEO-bench, a benchmark of 10,000 queries drawn from nine sources.

The authors tested nine ways of rewriting content. Quotation addition, statistics addition and cite-sources performed best. The abstract says GEO can boost visibility by up to 40%, and the paper reports relative gains of about 30 to 40% on one of its measures for the top methods. Keyword stuffing, a traditional SEO tactic, offered little to no improvement. The paper also reports that lower-ranked websites benefited more than top-ranked ones.

Read those numbers with care. They come from the authors’ own benchmark and an engine they built for the study, plus a smaller test on Perplexity. They show that content changes can sway what an AI answer cites. They do not show that a given change will lift your visibility in any product you use today.

How do AI answers choose their sources?

Nobody outside the AI companies knows exactly, and the companies do not publish full rules. A few things are documented:

1. Access comes first. OpenAI documents separate crawlers: OAI-SearchBot for surfacing sites in ChatGPT search, and GPTBot for content that may be used to train its models. OpenAI says sites opted out of OAI-SearchBot are not shown in ChatGPT search answers (they can still appear as navigational links), so a robots.txt rule can quietly remove you from one engine.
2. Eligibility looks like SEO. Google states that to appear in its AI features a page must be indexed and eligible to appear in Search with a snippet, and that SEO best practices remain relevant.
3. There is no magic markup. Google says there is no special schema.org markup, AI text file or other special optimization required for AI Overviews or AI Mode. It also says these features may use a “query fan-out” technique, running several related searches across subtopics, so covering a topic’s sub-questions can matter.

What should you do first?

The evidence is thin, so start with steps that pay off in classic search and in AI answers:

1. Check that crawlers can reach you. Review robots.txt and make sure you have not blocked the crawlers of the engines you want to appear in. Decide deliberately about training bots versus search bots.
2. Make sure key pages are indexable and return normal status codes.
3. Answer questions directly. Put a plain two-to-three sentence answer at the top of a page, then support it. Self-contained sentences are easier to quote.
4. Back claims with sources and specifics. In the paper, the best changes were adding citations, statistics and quotations. Add real ones. An invented statistic is worse than none.
5. Cover the sub-questions of your topic, in line with how Google describes query fan-out.
6. Keep the structure plain. Descriptive headings, sensible internal links, and definitions written as full sentences.
7. Consider an llms.txt file, knowing it is a proposal with unproven effect. Our llms.txt guide explains what it is and its status.

What GEO does not do

GEO cannot guarantee a citation or control what an AI says, and keyword stuffing does not help. There is also no single agreed metric: the paper used its own visibility measures and commercial tools use others. If a vendor promises a fixed uplift, ask to see the method.

How is GEO different from SEO and AEO?

In short: SEO targets rankings in a results list, AEO (answer engine optimization) is an informal label for winning direct answers, and GEO targets citations in AI-written answers. Our comparison, SEO vs AEO vs GEO in plain words, sets them side by side. For quick definitions of related terms, see the GEO glossary.

How can you see where you stand?

GraphoRank crawls your site, respecting robots.txt, and scores how ready it is for AI answers, including checks for llms.txt, sitemap, AI crawlability and how directly pages answer questions. You can see how the process works on How it works, and the free audit covers the first 10 pages of one site with no credit card. Paid plans are listed on Pricing. Run a free scan to see your starting point.