Two people in the same meeting use the terms AEO and GEO, and most of the time they mean different things. One is thinking of the answer box at the top of Google's results page, the other of the paragraph ChatGPT writes from scratch. The confusion is understandable, because both terms ask the same question about different surfaces: when a system gives the user a single answer, who becomes the source of that answer?
AEO (Answer Engine Optimization) is the practice of getting content used as a direct answer source by an answer engine. An answer engine is any surface that gives the user one clear answer instead of ten blue links: featured snippets, the People Also Ask block, voice assistant responses and AI summaries all fall under this definition.
The acronym itself is ambiguous. In Türkiye, most searches for AEO lead to the Ankara Chamber of Pharmacists (Ankara Eczacı Odası) or to the Authorized Economic Operator certificate used in customs. In the context of search and content, AEO means only Answer Engine Optimization.
Are AEO and GEO the same thing?
They are not the same, but the line between them is getting thinner in practice. AEO targets surfaces where the answer is selected as a ready-made passage; the system takes your sentence and shows it to the user. GEO targets responses in which the model reads multiple sources and builds its own sentence; there, it is your information that gets carried over, not your sentence.
The two terms also differ in age. AEO came from inside the search industry during the featured snippet era. GEO entered the literature with a 2023 study by researchers from Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi, and it has an academic definition. For the detailed framework, our GEO guide covers that side on its own.
In practice, both ask for the same thing: a passage that can be understood on its own, without the paragraphs around it. The industry's umbrella term is slowly shifting to GEO, because most answer surfaces now generate a synthesis instead of selecting a ready-made passage. You do not need to treat your choice of term as a separate strategy.
Answer engine surfaces and click behavior
An answer engine is not an abstract category; it is a countable list of surfaces. The most important difference between these surfaces is whether visibility turns into clicks.
| Surface | Where it appears | Click behavior |
|---|---|---|
| Featured snippet | A box at the top of the results page that shows the descriptive text first | A click automatically takes the user to the relevant section of the page |
| People Also Ask | An expandable question block on the results page | The source link appears when the block is expanded |
| AI summaries (AI Overviews and AI Mode) | A synthesized answer above the results, with supporting links | Links are shown, but the expected click rate is lower than for an organic result |
| Voice assistant | A spoken answer on a device with no screen or a small screen | In most cases no visual link is offered |
Featured snippets and the People Also Ask block are not independent of each other either: according to Google's documentation, a featured snippet can also appear inside a People Also Ask group. For Turkish, AI summaries launched in February 2026, so this surface has a very short history on Turkish queries compared with English.
Can you mark up a page for the answer box?
No. Google's own documentation asks this exact question, and the answer is short: you can't. Google's systems decide whether a page would make a good featured snippet for the user's query, and if they find it suitable, they promote it. There is no special schema type, HTML tag or markup that triggers it.
What is interesting is that you have full control in the opposite direction. You can turn off all snippets for a page with the nosnippet rule, keep a single block of text out with the data-nosnippet attribute, or lower the max-snippet value to reduce the chance of being selected as a featured snippet. Google presents only the nosnippet rule as a guaranteed solution; a short max-snippet value lowers the probability but does not eliminate it.
This asymmetry defines the character of AEO. You can technically guarantee that you will not appear, but you cannot guarantee that you will. The only lever you have left is the content itself, not a markup layer.
AEO does not replace classic SEO
Answer surfaces do not run on separate infrastructure. Google writes that to appear as a supporting link in AI Overviews and AI Mode, a page must be indexed and eligible to be shown with a snippet, and that there are no additional technical requirements beyond that. The same document states that regular search best practices apply to these surfaces as well.
The practical consequence is this: if a page is not indexed, if its canonical points to another URL or if snippets are disabled, AEO work has not even started. The technical foundation of search engine optimization is a prerequisite for AEO, not an alternative to it. The most common reason a brand does not appear on answer surfaces is not that its content fails to answer the question, but that the page never entered the candidate pool for that query in the first place.
AEO tactics that did not hold up when measured
Some of the advice circulating under the AEO label has been measured and did not deliver the expected results. Filtering these out saves more time than adding new tactics.
- FAQ schema. Google first restricted FAQ rich results to well-known government and health sites, then removed them entirely. This result type is no longer shown in search results, and the related documentation has been taken down.
FAQPagemarkup produces no visible gain today. - The general effect of structured data. In an experiment comparing 1,885 pages, adding schema markup did not increase AI visibility. Because this is a single comparative study, generalization is limited. Structured data is still useful for classic search features and semantic consistency; presenting it as a lever that earns citations, however, is not proven.
- The llms.txt file. None of the major engines read this file for citations. Google has said so explicitly, and a review covering 515 million bot requests found no meaningful trace of the file being fetched.
- Turning a set percentage of headings into questions. There are suggestive findings that question-style headings are cited more often, but that finding does not translate into a ratio rule. Pages with question headings are already pages targeting question queries, so what is being measured may be the match with the query rather than the format of the heading. If users really ask that question, a question heading is natural; forcing half of your headings into questions is not a method.
How do answer engines choose their sources?
The strongest data we have on source selection is observational, meaning it shows correlation and does not prove causation. Keeping that distinction is exactly what makes the data usable.
The most striking finding is that your own site is not the only lever. In a study that examined more than 25 million citations, about 84% of citations came from earned media that the brand did not own. What is written about a brand elsewhere appears to be as decisive as what you write on your own pages.
Position matters too. In a study of 18,000 citations across 1.2 million ChatGPT responses, about 44% of citations were taken from the first third of the content. The rule that follows is not a percentage target but a simple architectural choice: do not hide your most valuable answer and evidence in the later sections of the article. Our article on how to write content that gets cited by AI walks through how to build this at the passage level, step by step.
In a correlation study covering 75,000 brands, the strongest relationships with AI visibility were YouTube presence (0.737) and brand mentions across the web (0.664); the relationship with backlink count was much weaker (0.218). These are correlation coefficients. They do not mean that opening a YouTube channel will increase AI visibility; there is a real possibility of a common explanatory variable, such as large brands having both more video content and more mentions.
Platforms do not choose the same sources either. In an analysis covering 3.25 billion citations, the source overlap between ChatGPT and Perplexity was only 11%. Being a source on one platform does not mean you will be one on another, so measurement cannot rely on a single engine.
How do you measure AEO results?
The most common measurement mistake is treating citations and brand mentions as a single metric. Your page may be shown as a source without your brand name appearing anywhere in the answer, or, conversely, your brand may be mentioned without any link. They need to be counted separately, because they do different jobs.
The second issue is that responses are stochastic. The same query can return different sets of sources at different times, so drawing conclusions from a single run is misleading. Run critical queries more than once and test them with different phrasings. Seobaz's AI Visibility work handles this tracking by rerunning a fixed set of queries.
On the click side, the limit is clear: clicks from a featured snippet appear in Search Console as regular organic clicks, and today it is not possible to track traffic from AI surfaces as a separate line item. That is why the result of AEO work cannot be evaluated by looking at the traffic chart alone.
Who should prioritize AEO, and who shouldn't
Answer surfaces carry more weight in areas where users want to understand something before they buy. B2B services, technical products, software and consulting, where definition, comparison, suitability and how-it-works queries are common, fit this description. In these areas, users learn the concept first and choose the supplier later.
There are also areas where it drops down the priority list. In local services, where demand is determined by physical proximity, users go to the map, not to the answer box. Where brand awareness already brings in the demand, and for queries where the user goes straight to a transaction, the answer surface changes the decision very little.
The real trade-off to factor into the decision is this: appearing on an answer surface does not always bring clicks. AEO is an awareness and trust channel; if it is modeled like a direct traffic channel, it will be both mismeasured and misbudgeted.
If you are thinking of outsourcing this work, we cover the service components, the factors that drive cost and what to look for in a proposal separately in our article on AEO agencies.
Frequently Asked Questions
Do I need to remove the FAQ schema from my site?
No. Google states that unused structured data does not cause problems for search, so there is no need to proactively remove existing markup. However, since it produces no visible gain either, there is no longer a reason to keep it on your priority list for new pages.
Should I create separate content for AEO?
In most cases, no. Because answer surfaces use the same indexed page, building a separate AEO content pipeline means producing a second page on the same topic and making your own pages compete with each other. The more efficient route is to refine the passage structure and answer clarity of your existing content.
Are Turkish queries any different from English ones?
Yes, in terms of the observation window. Google opened AI summaries to Turkish queries in February 2026, so there is far less accumulated data for Turkish than for English. For that reason, it is not safe to transfer citation behavior observed on English queries directly to Turkish; measurement needs to be repeated in the target language.
