What is Answer Engine Optimization?

Answer Engine Optimization, or AEO, is the practice of getting your brand mentioned and cited inside the answers that AI systems generate. When someone asks ChatGPT which project management tool suits a small agency, three or four brands get named. AEO is the work of being one of them.

You will also see this called GEO, for Generative Engine Optimization. The terms are used interchangeably. Nothing hangs on the distinction.

Why a new term at all

Search used to end with a list. You optimised to appear on that list, and the user chose from it. The user did the comparison.

An answer engine does the comparison for the user. It reads a set of sources, synthesises them, and returns a recommendation. There is no list to appear on. There is one paragraph, and either your name is in it or it is not.

That single structural change breaks most of the measurement layer marketers rely on:

• There is no position one. There is a first brand mentioned, which is related but not the same thing.
• There is no stable result. Ask the same engine the same question twice and you can get two different answers naming two different brands.
• There is no single engine. ChatGPT, Google AI Overviews, Gemini, Perplexity and Claude all retrieve differently and cite differently.
• Impressions are invisible. Nobody reports how many times your brand was named. You have to measure it yourself.

What carries over from SEO

More than the "SEO is dead" crowd will tell you. Answer engines do not invent recommendations. They retrieve pages, read them, and summarise. The mechanism that decides which pages get retrieved is recognisably a search index.

So the fundamentals survive:

• Crawlable, renderable pages still matter, and now they matter to a new set of bots.
• Topical authority still matters. Sites that cover a subject thoroughly get retrieved more.
• Being cited on trusted third-party domains still matters, and in AEO it matters more than it ever did in SEO.

What is genuinely different

Three things.

Retrieval is question-shaped. People type keywords into a search box and full sentences into a chat box. "best CRM small business" and "we're a 12 person agency, what CRM should we use" are not the same query and do not return the same sources.

Third-party sources carry disproportionate weight. Look at what actually gets cited in most commercial categories and you find G2, Reddit, Capterra, industry publications and YouTube far more often than vendor websites. Engines are wary of a brand describing itself. In a lot of categories, AEO is closer to digital PR than to on-page SEO.

The engine's own searches change the target. Ask a complex question and the engine quietly generates several narrower searches, retrieves for each, and merges the results. You are not optimising for the question the user asked. You are optimising for the questions the engine asked itself.

How to actually do it

The loop is not complicated. It is just difficult to run without data.

1. Decide which questions matter. Not keywords. The actual questions your buyers ask, phrased the way they phrase them.
2. Find out where you stand. Run those questions across every engine, repeatedly, and record whether you were named, where in the answer, in what tone, and who was named instead.
3. Find out why. Look at the sources cited in the answers you lose. Almost always, a competitor is present on two or three pages that you are absent from.
4. Close the gap. Sometimes that means writing a page. Often it means getting a profile on a review site, or correcting something wrong on a page you do not own.
5. Measure whether it worked. Compare visibility on the affected questions before and after.

Step two is where most teams stall, because doing it by hand is unbearable. Forty prompts across five engines is two hundred answers to read per scan, and one scan tells you very little. That is the part worth automating.

The mistake to avoid

The most common failure is treating AEO as a content volume problem. Publishing thirty thin articles targeting question-shaped headlines does not work, for the same reason it stopped working in SEO around 2013. Engines are picky about what they cite, and a page that exists only to be cited reads exactly like one.

The teams that win tend to do less, more deliberately. They find the eight questions that actually drive revenue, they figure out precisely which sources decide those questions, and then they go and earn a place in those sources.