What Are AEO and GEO? How to Get Cited by ChatGPT, Claude, and Perplexity

Defined Without the Jargon

Two acronyms have arrived to describe the same shift. AEO is Answer Engine Optimization: making a page easy to lift a correct, self-contained answer out of. GEO is Generative Engine Optimization: the wider job of making your organisation a source that generated answers draw on at all.

The distinction is narrow enough that most people can treat them as one practice. AEO is about the passage. GEO is about the entity — whether a model has enough corroborating evidence to describe your company confidently in the first place.

Neither replaces search engine optimisation. A page that cannot be crawled cannot be cited either, and the technical groundwork is identical. What changes is the unit of competition: classic SEO competes for a position in a list, AEO competes to be the sentence that gets quoted.

SEO vs AEO vs GEO

Held side by side, the three differ less in tactics than in what success looks like and how long it takes to see it.

How an Answer Engine Picks Its Sources

Nobody outside these companies can see the ranking logic, and anyone who claims otherwise is guessing. What is observable is the shape of the pipeline, and that is enough to work with.

An answer engine retrieves a set of candidate documents, selects passages from them, synthesises an answer, and attributes some of it. Every stage rewards different things. Retrieval rewards the same relevance and crawlability that search always has. Passage selection rewards self-contained writing — a paragraph that still makes sense with the page removed. Synthesis rewards clarity and internal consistency, because contradictory sources get dropped rather than reconciled. Attribution tends to favour sources that state something specific and checkable.

The practical consequence is that page-level optimisation is no longer enough. A page can rank well and never be quoted, because every useful sentence in it depends on the three paragraphs above it.

The Six Properties of a Quotable Page

These are the properties we look for when auditing a page for answer visibility. None of them require new technology.

• —The answer comes first. Sixty words at the top that answer the title question completely, before any context or history. If the first paragraph is a warm-up, the quotable passage is on page two and someone else will be quoted instead.
• —One question per page. Pages that answer twelve questions adequately lose to six pages that answer one question properly, because retrieval matches a question to a document.
• —Passages stand alone. Each section should survive being read in isolation. Repeat the subject instead of relying on it — this instead of it — because the engine may only take the paragraph.
• —Entities are named explicitly. Say the product, the standard, the version, the company. A model cannot resolve the thing you have carefully avoided naming.
• —Structured data mirrors what is visible. Google's structured-data guidelines require markup to describe content actually present on the page, and marking up an answer a reader cannot see works against you rather than for you.
• —Specifics are checkable and dated. A named source, a documented threshold, a stated last-reviewed date. Vague confidence is the easiest thing for a synthesis step to discard.

What Structured Data Actually Does

Structured data does not make you rank, and it does not guarantee a rich result. What it does is remove ambiguity. It states in machine-readable form what a page is, who wrote it, which organisation published it, and how the entities on it relate to one another.

That matters most for questions about your organisation and your people. A name in a paragraph is text; the same name declared as a Person who works for a named Organization, with links to the profiles that corroborate it, is a claim a knowledge graph can hold. That is the difference between a model knowing your company exists and a model being able to describe who does what there.

The building blocks are unremarkable and well documented: Organization, WebSite, Article with a real author, BreadcrumbList, FAQPage where the questions genuinely appear on the page, and Service for what you sell. Getting these right is the least glamorous and most reliable part of technical SEO and answer optimisation.

How to Measure Something Analytics Cannot See

This is where the field is honest or it is nothing. There is no rank tracker for AI answers. Answers vary between users, between sessions, and between model versions, and most of them are read without anyone clicking through to you.

What you can do is sample deliberately and consistently. None of the following is a ranking; all of them are directional, and that is still useful when you re-run them the same way each month.

• —Keep a fixed list of twenty prompts a real buyer would type, and run them monthly across the assistants your market uses. Record which sources get cited, including when you are absent.
• —Watch the referrer report in your analytics for traffic from AI products. It undercounts badly, because the answer is often the end of the journey, but the trend line is real.
• —Track branded search in Search Console. When people start searching your company name after encountering it in an answer, that shows up here — and it is the signal that survives a model update.
• —Use Search Console query data to check that the questions you have answered are questions people actually ask, rather than the ones you assumed they would.

What Does Not Work

The tactics that show up in AEO checklists are mostly recycled from the worst decade of SEO.

• —Bolting an FAQ block onto every page. Marking up questions nobody asked adds nothing, and marking up answers that are not visible on the page contradicts the guidelines you are trying to satisfy.
• —Writing to a word count. Length is not a signal. A complete, self-contained answer is, and it is often shorter than the guide it replaces.
• —Burying the answer under an introduction to protect time-on-page. This trades the citation for a metric that does not pay you.
• —Publishing an ultimate guide that answers twelve questions badly. Retrieval matches one question to one document, so the guide competes with itself.
• —Claiming numbers you cannot source. A synthesis step compares sources against each other, and an unsupported figure is a reason to prefer someone else.

When AEO Should Not Be Your Priority

If your money pages have thin content, if the site is not reliably crawlable, or if your own name does not return your own site, answer optimisation is the wrong work for this quarter. Fix the foundation first — it is the same foundation either way, and none of the AEO advice above functions without it.

It is also the wrong priority when you have no informational content at all. Answer engines quote explanations, and a site consisting entirely of sales pages gives them nothing to lift. That is the honest reason to build a guide section before worrying about how AI systems read it.

And if your buyers do not research before they buy — pure local urgency, pure referral, pure repeat business — then the entire category matters less to you than reviews and response time do. Deciding that deliberately is a strategy. Discovering it after a year of publishing is not.