Sauror AIWhat is GEO (generative engine optimization)?
GEO, or generative engine optimization, is the work of getting ChatGPT to recommend your product: being named, and preferably recommended, in the answers AI assistants write when a buyer asks what to use.
A short definition
Generative engine optimization (GEO) is the practice of making a brand visible inside the answers written by AI assistants. When someone asks ChatGPT, Perplexity, Gemini or Google AI which tool to pick, the assistant writes a shortlist. GEO is the work of appearing on that shortlist.
The goal is not a blue link on a results page. It is a mention in the paragraph the assistant writes, ideally a recommendation with a reason, and when the assistant shows sources, a link to a page of yours among them.
In everyday language: GEO is getting ChatGPT to recommend your product, and doing the same on the other assistants your buyers actually open.
Where the term comes from
The name GEO comes from a 2024 research paper by Princeton et al., presented at KDD 2024 (Aggarwal and colleagues, "GEO: Generative Engine Optimization"). The paper needed a word for a new problem: once people ask a generative engine for an answer instead of scanning a list of links, a brand has to be present inside that answer, not only ranked on a page of results.
The term spread because it names the job clearly. SEO is still the work of being found in a search index. GEO is the work of being named in a generated answer. You will also see AEO (answer engine optimization) and LLMO (large language model optimization). They point at the same shift. On this site we use GEO, because that is the name the paper introduced and the name most teams now search for.
How a generative engine builds an answer
An assistant does not "rank pages" the way a search engine shows ten blue links. It writes a paragraph. That paragraph is built from two kinds of knowledge, and GEO has to deal with both.
Training versus retrieval
Training is what the model learned from a large snapshot of text. Well-known brands can appear from memory this way. That knowledge has a cut-off date, and the model cannot point to a page that "proves" a given sentence.
Retrieval is live reading. For questions about products, prices and recent changes, assistants such as ChatGPT (with search), Perplexity, Gemini and Google AI Overviews / AI Mode fetch pages, then write from what they just read. Those pages often appear as citations under the answer.
You do not control the mix. The same question can lean on memory one day and on retrieved pages the next. That is why a single screenshot is a weak measure, and why GEO tracks a rate across many answers.
This is also why "we were named once in ChatGPT" is not a programme. The next run, or the next assistant, can drop you. The work is to be present in the pages and third-party sources those runs keep retrieving.
Mentions versus citations
A mention is your brand name appearing in the answer. A citation is a source link the assistant shows, which may or may not be your own site.
You can be mentioned without being cited (the assistant names you from memory or from a third-party page). You can be cited without being recommended (a source is listed, but the paragraph prefers someone else). GEO watches both. Being named is the first job. Being cited with a clear, accurate description is the next one.
GEO versus SEO versus AEO and LLMO
These labels overlap. The useful distinction is what you measure and where the evidence lives, not which acronym you print on a slide.
| SEO | GEO | AEO / LLMO | |
|---|---|---|---|
| What you want | A click from a results page | A mention or recommendation in an AI answer | Same job as GEO, other names for it |
| Where it happens | Search results and your own pages | ChatGPT, Perplexity, Gemini, Google AI Overviews / AI Mode, and similar assistants | Answer engines and language models |
| Unit of success | Rankings, clicks, pages visited | How often, and how, you are named across many answers | Presence inside generated answers |
| What you publish | Pages that match queries and can be indexed | Clear pages plus accurate mentions on other sites | Content a model can quote without guessing |
| How stable it is | A position can hold for days | The same prompt can name different brands on the next run | Same variability as GEO |
Why it matters now
Buyers still use search. Many also start by asking an assistant. The assistant reads, summarises, and hands back two or three names. If you are not in that shortlist, the buyer may never open a results page where your ranking would have helped.
The answer is a single voice. A results page shows ten options side by side. An assistant often picks a handful and explains why. Being named first, with a reason that matches what you actually sell, carries weight in that format.
This is not an argument that websites stopped mattering. Assistants that search still need crawlable, trusted pages. Google AI Overviews sit on Google's own index. GEO builds on SEO. It adds a second scoreboard: mentions in answers, not only clicks from links.
It also changes who you compete with. On a results page you compete with whoever ranked. In an answer you compete with whoever the model is willing to name in a short paragraph. A smaller, clearer product can appear next to a larger one if the pages and third-party mentions make the match obvious.
What GEO work covers
In practice the work splits into four streams. None of them is a trick. All four are repeatable.
- Measurement: write the questions your buyers ask, run them on each assistant, and record who is named, who is cited, and which other brands appear.
- Your own pages: pricing, integrations, comparisons, use cases, docs and security pages written so an assistant can quote a fact without inventing one.
- Third-party presence: reviews, roundups, communities and directories that already describe several options, because those pages are what a recommendation question needs.
- Technical access: robots.txt and firewalls that let AI search and user-request crawlers read you, HTML that does not hide the facts behind a script, and structured data that states who you are.
An example prompt
Take a made-up category so nobody reads this as a measured result. A buyer types: "What is the best invoicing tool for a ten-person studio in France?"
The assistant will usually name a short list, give a reason for each, and sometimes show the pages it used. GEO for that studio is not "rank for invoicing tool". It is: appear in answers to that question, and to the sister questions ("X vs Y", "alternatives to X", "what does it cost"), on each assistant the studio's buyers open.
A useful baseline writes twenty to thirty of those questions, mostly without the brand's own name, then counts mentions, citations and competitors per assistant. That is the start of GEO for SaaS.
The same prompt asked twice can name different brands. Country, language and whether the user is signed in also change the answer. Treat one run as a snapshot. The figure that matters is how often you appear across the set, on each assistant separately.
Is GEO replacing SEO?
No. GEO does not replace SEO. Pages that cannot be crawled, indexed or trusted still fail both jobs. Google AI Overviews are built on Google's index. Assistants that search the web still pull from pages that SEO already cares about.
What changes is the unit of success. SEO asks whether you earned a click. GEO asks whether you were named in the answer the buyer read instead of a click. You still need the page. You also need the mention on other sites, because retrieval often prefers a comparison or a review over a vendor homepage.
Treat GEO as a layer on top of SEO, not a replacement programme. If you drop technical hygiene to chase mentions, assistants that search will read someone else.
How to check whether AI names you
The honest first check is simple: enter your site and see who gets named when buyer questions are asked for real. Sauror publishes a free AI visibility checker. You give a work email and a website. The check reads a public page, writes buyer questions from what it finds, asks the first few on one assistant surface, and counts who is named.
Read it as a snapshot, not a verdict. Answers change from one run to the next. The free check is one surface and one pass. Ongoing tracking repeats the same questions, on each assistant, on a schedule.
If you already know the term and want the SaaS playbook (which prompts to track, which pages to fix, how to read share of voice), continue with GEO for SaaS.
A check that never names you is still useful. It tells you the questions, the other brands that took the shortlist, and whether your home page is readable. That is enough to decide what to fix first. It is not enough to declare that "AI does not know us" forever.
GEO for SaaS
A SaaS buyer does not type your homepage title. They type "best X for Y", "X vs Y", "alternatives to X", and "what does it cost". The pages assistants quote for those prompts are usually pricing, integrations, comparisons, docs or use cases, and security, plus third-party reviews and roundups.
That is a product problem as much as a content problem. The full walkthrough, including a checklist and what to look for in a GEO tool, is in GEO for SaaS: how to get your product named by AI.
If you only have time for one next step after this page: write the ten questions your last inbound deals asked before they booked a call, run them in the free checker, and open the SaaS guide with that list in hand.
Questions
- What does GEO stand for?
- Generative engine optimization. It is the work of being named in the answers AI assistants write, not only ranked on a search results page.
- Is GEO the same as SEO?
- No. SEO measures rankings and clicks. GEO measures how often you are named in AI answers. GEO still needs crawlable, trusted pages, so it builds on SEO rather than replacing it.
- Which assistants does GEO apply to?
- The ones your buyers open. In practice that usually means ChatGPT, Gemini, Perplexity and Google AI (AI Overviews and AI Mode). Some teams also watch DeepSeek, and optionally Claude or Grok.
- How do I know if ChatGPT names my brand?
- Ask the questions your buyers type and record who appears. You can run a first pass with the free AI visibility checker. One run is a snapshot; answers vary.
- What should a SaaS team do first?
- Read GEO for SaaS, write a baseline of buyer prompts, and fix the pages assistants actually quote: pricing, integrations, comparisons, docs and security.
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