What Is Generative Engine Optimisation (GEO)? A Plain Explanation

Generative engine optimisation, usually shortened to GEO, is the work of making your content easier for AI answer engines to find, use and cite, so that your company is more likely to be named in their answers. It is a young field, the term is used loosely, and a lot of what is said about it is stronger than the evidence.

This page explains where the term came from, how it differs from search engine optimisation, what the original research did and did not show, and what the engines themselves document. It is written for marketing leads and founders who have heard the term and want a plain account before they spend money. It does not promise any result. Our methodology page describes how we measure.

The Definition, Without the Hype

An answer engine is a product that writes a response to a question, usually with links, instead of returning only a list of pages. ChatGPT with search, Claude with web search, Gemini, Perplexity, and Google's AI Overviews and AI Mode all do this. GEO is the set of things you can do to your content and your presence on the web so that these products have a reason to include you.

You will also see the same idea called AI search optimisation, answer engine optimisation (AEO), or AI visibility work. The labels are not standardised. We use "AI search optimisation (GEO)" on this site so that a reader searching for either term finds the same explanation. The names matter less than the question underneath: when a buyer asks an assistant about your category, does the answer include you, and is it accurate?

Where the Term Came From

The term was popularised by an academic paper. Pranjal Aggarwal and five co-authors submitted GEO: Generative Engine Optimization to arXiv in November 2023, with the latest version dated 28 June 2024. The authors describe GEO as a black-box optimisation framework to help content creators improve their visibility in generative engine responses. They built a benchmark called GEO-bench, a large collection of user queries across several domains paired with relevant web sources, so that content changes could be compared in a controlled way.

That origin is worth remembering. GEO began as a research idea tested on a benchmark, not as a proven commercial method. The agencies and tools that now sell it have built on the idea, and some of them are careful about the limits. Others are not.

How GEO Differs From SEO, and How It Does Not

The two overlap heavily. Google's documentation on AI features says a page qualifies as a supporting link in AI Overviews and AI Mode if it is indexed and eligible to appear in Search with a snippet, and that there are no additional technical requirements. Being eligible does not guarantee that a page will be crawled, indexed or shown. So for Google's AI features, ordinary search fundamentals come first.

The same page says AI Overviews and AI Mode may run several related searches across subtopics and data sources while building a response. This is sometimes called query fan-out. It means the set of pages an answer draws on can be broader and more varied than a classic results page.

The differences sit in the target and in the evidence. SEO aims at a position in a ranked list. GEO aims at being named or cited inside a written answer, and answers can vary from run to run. A study by SparkToro and Gumshoe, reported by Search Engine Journal on 30 January 2026, found that repeated runs of the same prompt almost never produced the same brand list. The authors note that volunteers used their normal tool settings and the report is not peer-reviewed. Even so, it is a good reason to measure GEO with many prompts and a range, not a single screenshot. We show how in Why an AI Visibility Score Needs a Confidence Interval.

What the Original Research Shows

The paper's abstract reports that its methods can raise visibility in generative engine responses by up to 40%, and that the effectiveness of different strategies varies by domain. Both parts matter. "Up to 40%" is the best case in a controlled benchmark, not an expected gain for your site. And "varies by domain" is the authors' own warning that a tactic that helps in one subject area may do little in another.

Three limits are worth stating plainly. The benchmark tests content changes against particular engines at a particular time, and engines change without notice. It measures visibility within responses, not enquiries or revenue. And it is a research result, which can inform your tests but cannot tell you what will happen on your site.

In short, the paper supports a modest claim: how content is written and presented can be associated with how often it appears in generated answers, and the effect differs by subject. It does not support a promise that a given set of changes will lift your company by any set amount.

What the Engines Themselves Document

The most reliable GEO guidance is what the product owners say about their own systems, because it is checkable and dated.

OpenAI's ChatGPT search help page says a site can be included in ChatGPT search if it allows OAI-SearchBot to crawl it and its host or CDN permits traffic from OpenAI's published searchbot IP addresses. It adds that inclusion does not guarantee a particular ranking, because ChatGPT weighs several factors. It also says answers that use web search may include citations you can open, and that you should check the cited pages because results can be outdated or wrong.

Perplexity's crawler documentation says PerplexityBot exists to help websites appear and be linked in Perplexity's search results, and that it is not used to gather data for building foundation models. It recommends allowing the bot in robots.txt.

These statements agree on a simple point. If an engine cannot reach your pages, it cannot cite them. That is the most dependable piece of GEO there is, and it costs almost nothing to check.

What Is Still Unproven

Plenty of advice in circulation goes beyond what anyone has shown. Be careful with claims that a specific file, markup type or phrasing trick will make an engine recommend you. Some of these ideas may help, some may do nothing, and few have been tested in a way you can inspect. If a provider cannot show you the prompts, the number of answers, the dates and the ranges behind a claim, treat it as a hypothesis.

There is also a demand-side caution. G2's published research on 1,076 B2B software buyers in March 2026 reports that 51% start research with an AI chatbot more often than with Google, up from 29% in 2025. That is a vendor survey that covers software buyers only. It supports the idea that AI answers matter for software purchasing. It does not tell you how much they matter for your market, or what a given optimisation will return.

Six Terms You Will Meet

The vocabulary is a barrier, and some providers lean on it. Here are the terms with plain meanings.

• Mention. The assistant names your company in its answer. This is different from a citation.
• Citation. The answer links to one of your pages as a source. An answer can cite you without naming you, and name you without citing you.
• Grounding. The assistant bases its answer on pages it retrieved, not only on what it learned in training. Turning web search on is what makes most answers grounded.
• Query fan-out. The assistant splits one question into several related searches. Google describes this for AI Overviews and AI Mode.
• Crawler. The automated program that fetches your pages. Each product uses its own, with its own name in robots.txt.
• Share of voice. The share of tracked answers that name you, ideally reported with the count and a range.

When a provider reports a result, ask which of these it is. "We increased your visibility" can mean more mentions, more citations or only a nicer dashboard.

How to Read a Provider's GEO Claim

Because the field is young, the quality of claims varies a great deal. Five questions separate measurement from decoration. How many prompts and how many answers sit behind the number? Were prompts that name your company kept apart from those that do not? Is there a range, and how was it calculated? Were the same prompts used before and after the change? And what was changed, one thing or ten? If the answers to those are vague, the result may still be real, but you cannot tell.

Ask also what the provider will do if a test shows no change. A credible answer is to report it and try something else. A less credible one is to promise a result in a fixed number of weeks. Remember what the research paper says about domain differences: a tactic that worked on one kind of query may do nothing on yours.

What to Do First

1. Check access. Make sure robots.txt and your CDN allow the crawlers of the products you care about, and that your key pages return a normal response.
2. Write down the questions your buyers ask and run them on at least three assistants with web search on. Record which companies are named and which pages are cited.
3. Fix what is plainly wrong. If an answer states your price, location or service incorrectly, find the page it drew on and correct the source.
4. Make your pages easy to cite. State who the product is for, what it costs, what it does not do and how it compares on named criteria. This is good for readers regardless of any engine.
5. Measure the same prompts weekly and report a range. Change one thing at a time so you can tell what moved.

Our guide to running an AI visibility check on your company walks through the first step in detail, and how to measure AI share of voice covers the metrics. If you are weighing outside help, the buyer's guide to choosing a GEO agency lists the questions to ask and the red flags. For how buyers meet a company in AI assistants, see AI Visibility for B2B Brands.

Where ThriveFinity Fits

We run repeated, ranged measurement of how AI assistants describe a company and write up the findings, signed by a named person. That is the AI Visibility service. We do not guarantee a placement, and we state our limits on every report. Any error we find in our own pages is logged on the errata page.

Spotted something out of date or wrong on this page? Email om@thrivefinity.uk and we respond within 5 working days.

Pranav Unni

Founder · ThriveFinity Connect on LinkedIn →

Pranav Unni is the founder and lead verifier of ThriveFinity. He reads and signs every paid deliverable personally, and writes about go-to-market decisions for established B2B companies.