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SEO vs AEO vs GEO: What Each One Actually Optimizes For
by the AEO GEO Labs team3 min read
SEO asks where you rank. AEO asks whether you are the answer. GEO asks whether you are recommended. They are not competing philosophies; they are three questions a buyer's journey now passes through, often in a single session.
The buyer's new path
A founder needs payroll software. Five years ago she searched, scanned ten links, opened four tabs, and formed a shortlist herself. Today she asks an assistant. It names three products and explains each in a sentence. She might then search one of those names to confirm, land on a review site, and book a demo. Your brand had three chances to appear: in the recommendation, in the cited sources, and in the confirming search. Each chance is governed by a different discipline.
SEO: where you rank
Search engine optimization is still the foundation, because most AI tools search the same web Google does. If your pages are not indexed, not crawlable, or not clearly about the topic, nothing downstream works. SEO also still wins the confirming search, the moment a buyer types your name after an AI mentioned it.
What changed is the ceiling. A #1 ranking under an AI answer box is worth a fraction of what it was, because the buyer who got her answer never scrolls.
AEO: whether you are the answer
Answer engine optimization is about the specific page an assistant reads and quotes. It rewards pages built like good reference material: the answer up front, facts a model can lift, headings that match the question, FAQ and product schema, and consistency with what the rest of the web says. AEO is mostly on-page work, and it is where most companies have the fastest wins, because the bar is low. Many category leaders have no page that directly answers the question buyers actually ask.
GEO: whether you are recommended
Generative engine optimization is about the shortlist. When a model names three products, it is drawing on review platforms, forums, lists, press, and its own training, not just your site. GEO is therefore mostly off-page work: getting into the sources models read for your category, and making sure every source carries the same correct facts about you. It is slower than AEO and compounds longer.
How they fit together
| Question | Discipline | Mostly where | Typical first win |
|---|---|---|---|
| Can engines find and read you? | SEO | Technical, on-page | Fix rendering and crawl blocks |
| Will an assistant quote you? | AEO | On-page | Rewrite one page to answer directly |
| Will an assistant recommend you? | GEO | Off-page | Get listed on the review site it cites |
The mistake we see most is treating these as a sequence to complete in order. They run in parallel, and the measurement that ties them together is share of answer: on a fixed set of buyer questions, across every engine, how often are you named, how often are you cited, and who has the spot when you are not.
A worked example
At AEO GEO Labs we recently audited a B2B tool that ranked top three for its main category keyword. Its share of answer was under 20 percent. ChatGPT never named it; Perplexity cited a competitor's comparison page; Gemini quoted pricing that was two years old from a directory listing nobody had updated. None of that was an SEO problem. The fixes were an AEO page, a GEO correction campaign across six third-party sources, and a schema and llms.txt pass so the engines could confirm the facts. Rankings did not move. Share of answer did.
Which to start with
If you have never measured it, start with the measurement. Everything else depends on knowing where you are missing and why. AEO GEO Labs runs that audit live and shows you, engine by engine, who gets recommended instead of you.