SEO vs AEO vs GEO: What Each Means and What Actually Works

SEO, AEO and GEO are not three different jobs. They are the same foundation, crawlable pages with clear, accurate, well-structured information, aimed at three ways people now find answers: search results, direct answers and AI-generated summaries. Most of what is sold as AEO or GEO is good SEO with a new name. The parts that are genuinely new are about measurement and crawler access, and those are also the parts with the least certainty.

Definitions

SEO (search engine optimization) is making a website easy for search engines to crawl, index and understand, and worth ranking for the queries its audience uses. It covers technical foundations, content and the signals that make a site trustworthy.

AEO (answer engine optimization) is making content easy for answer engines and AI assistants to find, understand and quote as a direct answer: a plain definition near the top, questions answered in full sentences, consistent facts and structured data that matches the visible text. Interest in the term is real: Serpstat estimates roughly 2,400 monthly US searches for "answer engine optimization" (a provider estimate, not Google data).

GEO (generative engine optimization) applies the same ideas to generative AI tools that compose an answer from several sources, such as AI summaries in search and chat assistants with web access. The aim is to be one of the sources used, and ideally cited.

In the UK the word is spelled optimisation. The ideas are the same.

How they overlap

In practice the overlap is most of the work. A page that is crawlable, answers the question in its first paragraph, uses clear headings, states facts consistently and carries accurate structured data serves all three. There is no separate AEO version of a good page.

What is evidenced and what is speculative

It helps to sort advice by how much support it has.

Evidenced: documented by the search operators themselves

• Crawl and index access. A page that crawlers cannot fetch, or that is marked noindex, cannot appear in search or in AI features built on that search index. Google's own guidance for its AI features is to follow the same fundamentals as for Search; it does not ask for special files or markup.
• Snippet controls. Search engines document controls such as nosnippet and max-snippet that limit how much of a page can be shown, and those apply to AI summaries too. Use them deliberately; they cut both ways.
• Structured data for rich results. Schema markup that matches the visible page makes it eligible for certain search features. Eligibility is not a guarantee, and markup that does not match the page can be ignored or treated as spam.
• Helpful, original content. Search engines say they reward content written for people with first-hand knowledge. That is guidance rather than a formula, but it is the operators' stated position.

Plausible but unproven

• Answer-first structure (a direct answer in the opening sentences, question-led headings) makes content easy to quote. It is sensible writing, and it fits how summaries are built, but no operator promises it leads to citation.
• Consistent entity information (the same name, description and facts across your site and reputable profiles) helps systems recognise who you are. It is reasonable and cheap; the effect is hard to isolate.
• Being mentioned on other reputable sites probably matters for AI answers as it does for search, but the mechanism is not documented.

Speculative or overstated

• llms.txt as a ranking or citation lever. It is a proposed convention for giving language models a plain-text map of a site, not a standard, and the major search operators have not documented using it to rank or cite pages.
• "AI schema" or special markup for chatbots. No such requirement is documented by the major operators.
• Guaranteed AI citations. Nobody can promise that an assistant will cite a page. Answers vary by user, location, wording and time.

Why llms.txt and schema guarantee nothing

Both are worth doing for the right reason. Structured data is a clear, machine-readable statement of facts that are already on the page; it can make a page eligible for rich results and reduces ambiguity. An llms.txt file is a cheap, harmless summary of a site's most important pages. We publish both on this site.

Neither forces anything. Search and AI systems decide what to crawl, what to trust and what to quote; markup is an input to that decision, not an instruction. If a provider sells either as a guarantee of AI visibility, ask what evidence the claim rests on.

Crawler access basics

AI answers can only draw on pages their systems can fetch. Four crawlers matter most for search-style visibility. The summaries below follow each operator's published crawler documentation; read the current version before you change robots.txt, because names and behaviour change.

Three practical points:

• Search crawlers and training crawlers are different. Several operators document separate user agents or tokens for search features and for model training. You can allow one and block the other; decide each on its merits.
• robots.txt controls crawling, not indexing. A blocked URL can still appear in results if other pages link to it. To keep a page out of search, allow crawling and use noindex.
• Check your CDN and firewall too. Bot protection can block crawlers that robots.txt allows. Test with your hosting provider's logs, not assumptions.

Measurement limits

This is the honest weak spot of AEO and GEO.

• Search Console does not report AI features as a separate line at the time of review; their clicks and impressions are counted within ordinary web search data.
• Many answers produce no click. Visibility without a visit is real but hard to count.
• Assistant referrals are partial. Some assistants pass a referrer or tracking parameter; many visits arrive with none and show as direct traffic.
• Manual prompt checks are anecdotes. Answers vary by account, location, wording and day. Record them with dates and treat them as samples, not rankings.
• Third-party AI visibility tools run sets of prompts and report how often a brand appears. They are useful for trends, but they are estimates built on the tool's own prompt choices.

What can be measured well: whether pages are crawled and indexed, organic clicks and enquiries from search, and whether your facts are stated consistently. Start there.

What actually works

1. Fix crawling and indexing first: correct status codes, one canonical URL per page, a sitemap that lists only indexable pages, and robots rules that allow the crawlers you want.
2. Make every important page answer its question in the first paragraph, then support the answer with detail, examples and limits.
3. Publish information that is yours: your process, your criteria, your worked examples. Summaries of other summaries are easy to replace.
4. State facts consistently (name, what you do, where you work) on your site and on reputable profiles you control.
5. Add structured data that matches the visible text, and nothing it does not.
6. Measure what can be measured and label the rest as estimates.

When each label fits

• Talk about SEO when the problem is foundations: pages not indexed, slow, thin or poorly linked. This is most sites.
• Talk about AEO when foundations are sound and you want content structured to be quoted: definitions, FAQs, comparison pages.
• Talk about GEO when you want to understand and improve how AI assistants describe you, accepting that measurement is partial.

When we may not be the right fit

StackEndBox offers SEO, AEO/GEO and paid search with a technical foundation first, and a focused answer engine optimization and GEO service for measuring and improving how AI assistants describe you. We are probably not the right fit if:

• You want guaranteed rankings or guaranteed AI citations. Nobody can honestly promise either.
• You need high-volume content production rather than technical and structural work.
• Your site's problems are mainly in a platform you cannot change, and the platform's own settings already cover the basics.

Decision checklist

1. Are our important pages returning 200, self-canonical and listed in the sitemap?
2. Does robots.txt allow the search crawlers we want, and does our CDN or firewall let them through?
3. Does each important page answer its main question in the first paragraph?
4. Is our name, description and service list consistent across our site and profiles?
5. Does our structured data match the visible text exactly?
6. Have we decided separately whether to allow search crawlers and training crawlers?
7. What will we measure, and which numbers are estimates?

Illustrative examples

The scenarios below are invented to show how the checklist applies. They are not clients and describe no real engagement.

None of this is a ranking of tactics. If you are deciding where AI belongs inside your operations rather than your marketing, see AI agents versus deterministic automation. For a plain overview of the company behind this guide, read what StackEndBox is.