Quick answer
What is generative engine optimization (GEO)?
Generative engine optimization (GEO) is the practice of making a brand easy for AI assistants such as ChatGPT, Gemini and Perplexity to find, understand, trust and cite. Instead of competing for a position in a list of links, GEO aims to have your brand named — accurately — inside the answer an AI writes for the user.
Why generative engine optimization matters now
For twenty years, getting found online meant ranking in a list of ten blue links. That model is being joined by another. Ask an AI assistant “who is a good tax accountant for freelancers?” and you do not get ten links. You get a short answer that names three or four options and explains why.
If your brand is one of those names, you have been recommended by something the user trusts. If it is not, you were never in the running — and there is no page two to scroll to.
This is the shift generative engine optimization responds to. Google has added AI-generated summaries to its own results, and assistants like ChatGPT, Gemini, Claude and Perplexity are used every day for research that used to start in a search box. The change does not replace search; it adds a new place where buying decisions begin.
Where the term comes from
The phrase was introduced in a 2023 research paper, “GEO: Generative Engine Optimization”, by researchers from Princeton University and other institutions. They tested ways of rewriting web content and measured how often it then appeared in AI-generated responses.
Their finding was encouraging for publishers: content could be made measurably more visible. Methods such as adding citations, quotations from relevant sources and statistics improved visibility in generative engine responses by up to 40% in their tests. Keyword stuffing, the old SEO shortcut, did not help.
That study is a controlled experiment, not a guarantee. AI products have changed since, and no company publishes how its assistant chooses sources. Treat every GEO tactic as informed practice rather than a formula.
How AI assistants decide who to mention
An assistant builds its answer from two kinds of knowledge, and GEO has to address both.
What the model learned in training
Models are trained on huge amounts of text. Brands that are discussed often and consistently across the web are “known” to the model before any search happens.
What it retrieves live
Many assistants now search the web while answering, read a handful of pages and cite them. Here, being crawlable and clearly written decides whether you are picked.
Across both, a few patterns show up again and again:
- Clarity beats cleverness. Plain statements of what you do, for whom and where are far easier to extract than brand slogans.
- Consistency builds confidence. When your site, profiles and listings all say the same thing, the model has no reason to hedge.
- Third parties carry weight. Reviews, directories, industry lists and press mentions tell the assistant that others vouch for you.
- Specifics get quoted. Named services, numbers, steps and definitions are citable. Vague claims are not.
- Access is a prerequisite. If AI crawlers are blocked or the content only appears after scripts run, the assistant may never see it.
GEO vs SEO: what actually changes
| SEO | GEO | |
|---|---|---|
| Goal | Rank in the list of results | Be named or cited in the generated answer |
| Unit of success | Position and clicks | Mentions, citations and accuracy |
| Main levers | Technical health, content, links | Clear facts, structured data, third-party mentions, crawler access |
| How it is measured | Rankings, impressions, traffic | Repeated prompt tests and AI referral traffic |
| Certainty | Well documented by Google | No official rulebook; evidence is still emerging |
The two are not rivals. Google states that its AI features rely on the same foundations as Search — helpful content and sound technical basics — in its guidance on AI features and your website. Assistants that browse the web also lean on pages that already rank well. In practice, GEO is a layer on top of good SEO, not a replacement for it. For a side-by-side view that includes answer engines, see SEO vs AEO vs GEO.
How to get your brand recommended by ChatGPT: 7 steps
Test what AI says about you today
Write down ten questions a buyer would ask — “best [service] for [audience]”, “who offers [service] in [market]?” Ask them in ChatGPT, Gemini and Perplexity. Record who is named, which sources are cited and how you are described. This is your baseline.
Fix your facts
Make your name, services, markets and credentials identical on your website, social profiles and listings. Contradictions are one of the main reasons assistants describe a business wrongly.
Let the crawlers in
Check that robots.txt does not block AI crawlers such as OpenAI’s GPTBot and OAI-SearchBot, and that your key content is in the HTML rather than loaded by scripts.
Write pages that can be quoted
Open each important page with a direct answer of 40–60 words. Follow with specifics: what is included, how it works, who it is for. Add an FAQ that mirrors real questions.
Add structured data
Mark up your organization, people, services, FAQs and reviews with schema.org so machines do not have to infer who you are.
Earn mentions where assistants look
Note which sites were cited in step one. Get listed, reviewed or featured on the relevant ones: industry directories, review platforms, respected publications and active communities.
Re-test on a schedule
Repeat the same prompts monthly. Answers vary, so look at trends across many prompts rather than a single response.
What about llms.txt?
llms.txt is a proposed standard, described at llmstxt.org: a markdown file at the root of your site that gives language models a short, clean summary of who you are and links to your key pages. Some sites also publish an llms-full.txt containing their main content in one file.
It is worth being honest about its status. Adoption by AI companies is uneven, and there is no confirmation that it influences answers. It is, however, quick to create and harmless, and it forces you to write the plain summary of your business that GEO needs anyway. This site publishes both files.
Common GEO mistakes
- Chasing guarantees. No one can promise a place in an AI answer. Be wary of anyone who does.
- Blocking AI crawlers by accident. A security plugin or an old robots.txt rule is often the culprit.
- Publishing volume instead of substance. Hundreds of thin, AI-written pages do not make a brand more citable.
- Ignoring off-site reputation. Your own website is only one of the sources an assistant reads.
- Measuring once. A single prompt on a single day tells you very little.
If you would rather have this done for you, that is what my GEO services cover — starting with an audit of what the assistants say about your brand today.
FAQ
Frequently asked questions
Is GEO replacing SEO?
No. GEO builds on SEO. AI features in Google draw on its search index, and assistants that browse the web rely heavily on pages that already rank. Without solid SEO there is little for GEO to work with.
How long does generative engine optimization take?
On-site changes can be reflected within weeks by assistants that search the live web. Changes that depend on third-party mentions, or on a model being retrained, take months.
Can a small business benefit from GEO?
Yes. Assistants often answer narrow questions — a specific service in a specific market — where a focused small business can be the clearest, best-documented option.
How do I measure GEO?
Track mentions and citations across a fixed set of prompts, check how accurately your brand is described, and watch referral traffic from AI assistants in your analytics.
Do I need special tools?
Not to begin. A spreadsheet of prompts and results is enough for a baseline. Dedicated tracking tools become useful once you monitor many prompts across several assistants.