Generative engine optimization (GEO) is the work of making your website and brand show up in answers from ChatGPT, Perplexity, Google AI Overviews and other AI systems, as a cited source, a link or a recommended company. It builds on SEO, but it also covers how those systems understand your business and which facts about it they trust.
Buyers no longer look for a vendor only in a search box. Someone can ask ChatGPT or Perplexity "Who can help my company with GEO?" and get a ready answer with a few names in it. If your company is not among them, that person may never scroll to the regular search results at all.
What has changed in search by 2026?
Classic search sends a person to a list of pages. Search with a generated answer first pulls information from several sources, writes a conclusion and only then shows links. The path to a website got shorter, and sometimes the site does not make it onto the first screen at all.
For a business, visibility used to come down to one question: "Where do we rank?" Now there are two more: "Does the AI name us?" and "Does it describe our services, prices, locations and strengths correctly?" Rankings still matter, but they no longer show the whole picture.
The most harmful mistake in 2026 is to treat GEO as a separate, magic channel. No single dashboard or report covers it, and no button adds your company to every AI model. I think of GEO as a layer on top of SEO that carries your expertise into AI answers: the foundation is the same, and what changes is where a buyer first meets you.
What is GEO?
GEO stands for generative engine optimization: improving how a business appears in search systems that generate answers. The term spread after a 2023 research paper by Aggarwal and colleagues (published at KDD 2024), which tested how changes to content affect its visibility in generative answers. Since then GEO has moved from a lab experiment to a practical marketing task.
The goal is simple to state: when a potential client asks a question in your field, the system should recognize your company, connect it to the right service and find enough evidence to cite it or include it in the answer.
No one can guarantee a mention. The answer depends on how the question is worded, where the user is, which model and search mode they use, and which sources are available at that moment. So GEO work rests on observation and repeatable checks. If a vendor promises to "get you to the top of ChatGPT," I would treat that as a warning sign.
SEO, AEO and GEO: where is the line?
The three overlap. One strong page can rank in search, supply a short answer for a featured snippet and serve as a source for an AI answer, all at once. They differ in what the person ends up seeing and in what gets measured.
| SEO | AEO | GEO | |
|---|---|---|---|
| Main goal | Get a page into regular search results | Give the system a ready, accurate answer to a question | Get into a synthesized answer as a source or a recommended company |
| Where you see the result | Links in Google and Bing | Featured snippets, People Also Ask, voice assistants | Answers in ChatGPT, Perplexity, Google AI Overviews and AI Mode, Microsoft Copilot and other systems with web search |
| What matters most | Indexing, relevance, links, site usability | Clear wording, structure, factual accuracy | A clear brand entity, evidence, outside mentions and sources the system can access |
| What to measure | Rankings, impressions, clicks, leads | Answers won and clicks on them | Share of mentions, citations, factual accuracy, visits and leads from AI systems |
The industry has no fixed boundary between AEO and GEO. I use a simple split: AEO is about the form and accuracy of the answer on a page, and GEO is about your brand being present in an answer the system assembles from several sources. It is a working definition, and on some projects the two will overlap.
Why does GEO depend on SEO?
Google says plainly that the usual SEO fundamentals apply to its AI features, because they are rooted in its core ranking and quality systems. You do not need special markup to appear in AI Overviews or AI Mode. The page has to be indexed, load fast, work on mobile and contain useful material.
Other systems have their own mechanics, but the logic is similar. Perplexity runs its own crawler, PerplexityBot, to find and link sources for its answers, and says that crawler is not used to train models. OpenAI separates its bots too: OAI-SearchBot powers search in ChatGPT, while GPTBot collects data for training. OpenAI states that sites which block OAI-SearchBot will not be shown in ChatGPT search answers, though they can still appear as navigational links. Allowing the bot, on the other hand, guarantees nothing by itself.
In practice, a site with technical problems, duplicate pages and vague service descriptions is a weak candidate for both regular and generative search. A GEO audit should start with the technical foundation, and publishing articles comes after that.
How does an AI system choose which contractor to name?
Picture a company in Columbus, Ohio that designs and installs ventilation for restaurant kitchens. A potential client asks: "Who can do a turnkey restaurant ventilation system and help get the plans through permitting?" The company has a website, but all it says is "quality engineering solutions for business." To a person that reads as an ad with nothing in it. To an AI system it is close to an empty page.
To connect the company to that question with confidence, the system needs facts it can check: the area served, the types of projects, the stages of work, the documents involved, sample projects and who does the work. It helps when these facts match across the service page, business profiles, industry directories and articles about the company, because matching facts leave less room for ambiguity.
This is where the three jobs separate clearly. SEO helps the page appear for "restaurant ventilation installation Columbus." AEO helps give a short answer on what stages the work involves and what drives the cost. GEO raises the chance that the system names the company in a shortlist and can explain why it fits the request.
The example is made up to show the mechanics and says nothing about results. On a real project the list of factors depends on the niche. For a medical service, qualifications and safety come first; for a software product, documentation and independent reviews; for a local contractor, service area, portfolio and verified contact details.
How does GEO work in practice?
A map of real buyer questions
I start with the questions buyers ask, and I do not take phrases from a single keyword tool. I collect wording from search suggestions, sales calls, inbound requests, reviews and competitor sites. The map has to include decision questions: who to hire, which option is better, how much it costs, what the risks are, how the options differ and whether a solution fits their situation.
For a first check, 20 to 30 questions that can lead to a purchase are enough. A list that is too broad blurs the conclusions, because a mention in a general question and a recommendation right before a deal are worth very different things.
A baseline measurement
The questions become a fixed set of tracked prompts. I run each one in the chosen systems and record the date, the wording, the search mode, the answer, the brands mentioned and the links. Answers change, so a single screenshot tells you little. You need a repeatable sample: the same prompts, the same conditions and the same interval between checks.
Pages with evidence
After the baseline it is usually clear which facts are missing. A service page benefits from an exact description of the result, the terms of work, limitations, a price or the factors behind it, timelines, service area, stages and authorship. Case studies should show the original task, what was done and a result someone can check. If you cannot disclose numbers, say so honestly instead of writing "we significantly improved performance."
A short answer at the start of a section helps AEO and saves the reader time. I usually keep it to 40–80 words, which is my editorial habit and not a search engine requirement. After it I cover conditions, exceptions and examples, so the page is easy to skim and still has depth.
Outside confirmation
Your own website always talks about you in the first person. A generative system also needs other reference points: industry directories, trade media, partner pages, review sites, maps and public registries. Relevance matters more than the number of links: the source should suit the topic, and your name, address, services and other core facts should not contradict each other from one place to the next.
Fake reviews, invented authors and dozens of identical guest posts create noise. Sometimes that noise buys short-term visibility, but it damages the information trail around your brand. Clean, consistent facts do more for GEO than publishing volume.
What should you measure instead of rankings?
There is no single "ranking in ChatGPT." I build a report from four groups of metrics:
- Share of mentions: the percentage of checked answers that include your brand.
- Citations: how often the system links to your site, and which pages it picks.
- Accuracy: whether your services, region, specialization, prices and other facts are stated correctly.
- Business results: visits from AI systems, branded demand, inquiries and deals, where you can attribute them properly.
Here is the math on a simple example. Say I take 30 commercial questions and check them in three systems, 90 answers in total. The brand appears in 18 of them, so the share of mentions is 20%. A link to the site appears in six answers, a citation share of 6.7%. That is the starting point for the project, and it says nothing about whether the result is good or bad for the industry. A month later I repeat the sample and compare.
A small amount of AI traffic can be worth more than a lot of informational traffic if the questions sit close to a purchase. That is why I do not judge GEO by visits alone. The context of a mention and the quality of the lead matter more than a nice traffic chart. I track these numbers the same way in AI visibility monitoring.
What does a GEO plan for the first 90 days look like?
| Period | Focus | What you should have at the end |
|---|---|---|
| Weeks 1–2 | Diagnostics | A map of 20–30 questions, a baseline of AI answers, a check of indexing and crawler access |
| Weeks 3–6 | Core pages | Sharper service pages, answers to decision questions, authorship, sources, company facts and updated internal linking |
| Weeks 7–10 | Information trail | Relevant outside publications and business profiles, fixed inconsistencies in name, contacts, services and service area |
| Weeks 11–12 | Second measurement | Share of mentions and citations compared, a list of errors in AI answers, priorities for the next cycle |
In 90 days you can set up measurement and close the basic gaps. Promising steady presence in every answer within that time would be dishonest: the systems need time to recrawl sources, and your competitors keep moving too.
What should you not spend a GEO budget on?
- Hundreds of similar articles rewritten from whatever already ranks. They make the site bigger but rarely add new facts or trust.
- A "secret markup for AI." Useful structured data exists, but it has to match the visible content of the page, and it cannot replace the content itself.
- Buying random mentions on the theory that more is better. Irrelevant sites do not tell the system why your company deserves trust on a specific topic.
- Reports based on a single query. The wording and the result both change, so conclusions from one answer are unreliable.
- Guaranteed placement in answers. A vendor has no control over what a specific generation says, so the only honest promise is the scope of work and transparent measurement.
Who needs GEO right now?
First of all, companies whose clients compare options before getting in touch: B2B services, agencies, software companies, clinics, education providers, online stores with a complex catalog and local contractors with expensive services. The longer the decision and the higher the cost of a wrong choice, the more likely a person is to ask an AI several follow-up questions.
In some situations GEO should not be first in line for the budget yet. If the site is poorly indexed, service pages do not answer basic questions, there is no analytics, or nearly all sales come from personal referrals, closing those gaps pays off sooner. AI visibility will not fix a weak offer or replace normal marketing.
Frequently asked questions
Can GEO replace SEO?
No. Generative systems often rely on web search and the pages they can reach. Without indexing, clear structure and strong content, GEO hits a ceiling quickly.
What is the difference between AEO and GEO?
AEO focuses on making it easy for a system to extract an accurate answer from a page. GEO looks wider: whether your site or brand makes it into the final answer assembled from several sources, and in what context it appears.
Do I need separate content for each AI model?
Usually not. It is more useful to build one strong page with clear facts, a clear structure and sources, and then check how different systems use it. Separate landing pages make sense when the search intent differs; a different AI system is not a reason on its own. I cover ChatGPT specifically in how to get your website cited by ChatGPT.
Does an llms.txt file help?
Support depends on the system. Google says you do not need any special AI text files for its AI features and that llms.txt neither helps nor hurts in Google Search; its advice is to follow normal SEO practice. I treat llms.txt as an optional experiment and never as the basis of a strategy.
How soon will I see results?
The first repeat measurement makes sense after the updated pages and sources have been recrawled. In practice you judge progress over several cycles rather than one day. The pace depends on the state of the site, how often the sources are updated, the competition and how each system behaves.
Where do I start?
Take 20 questions your clients ask before they buy and run them in two or three AI systems. Write down whom they recommend, which sources they cite and which facts about your company they get wrong. Even this small check shows what is missing: technical access, convincing pages, outside confirmation, or all three.
If you would rather not run this check yourself, book an AI visibility audit with Izotov Agency. I check which questions get your brand named by ChatGPT, Gemini, Perplexity and Google AI Overviews, who they recommend instead and which sources they rely on. You get a log of every tested prompt with the recorded answers, a list of errors in how your brand is described, the priority pages and a 30–90 day plan. The same prompt set can be rerun later to measure what changed.
Sources
- Aggarwal et al. GEO: Generative Engine Optimization, KDD 2024 (arXiv, 2023)
- Google Search Central. Optimizing your website for generative AI features on Google Search
- Google Search Central. Featured snippets and your website
- OpenAI. Overview of OpenAI crawlers
- Perplexity. Perplexity crawlers
- Google Search Central. Creating helpful, reliable, people-first content