What is Answer Engine Optimization?

Answer Engine Optimization (AEO) is the practice of making a business legible and credible enough that AI systems recommend it inside a generated answer. Not ranked in a list of links — named in a paragraph, by a system that has decided it understands you well enough to vouch for you.

You'll see the same idea called Generative Engine Optimization (GEO), LLM SEO, or AI search optimization. The labels differ; the underlying problem doesn't.

Why it needed a new name

SEO's whole model assumes an ordered list of documents and a user who picks from it. Answer engines break both halves. There's no list to be positioned in, and increasingly no click — the user reads the answer and acts on it.

That changes what the unit of optimization is. In SEO you optimize a *page* for a *query*. In AEO you make an *entity* legible for a *question*. It sounds like a semantic distinction until you watch a site with excellent rankings get skipped entirely because nothing on it says plainly what the company does.

What answer engines actually reward

Across the four major engines the same four properties keep deciding who gets named.

1. 1

   Entity clarity

   Can a machine state what you are, who you serve, and where, from your own pages? This is the single biggest differentiator and the one most sites fail.

2. 2

   Machine-readable structure

   Organization, Service, Product and FAQPage schema turn prose claims into assertions a system can use without inference.

3. 3

   Answer-shaped content

   Pages that directly address the questions buyers ask — comparisons, pricing, selection criteria — because those are what get cited.

4. 4

   Corroboration

   Independent sources describing you the same way. One domain asserting something is a claim; five agreeing is a fact.

What AEO work actually looks like

Stripped of vocabulary, a real engagement is fairly mundane:

1. 1Write down the questions your buyers actually ask, in their words.
2. 2Ask each one on each engine, signed out, and record who gets named and which pages get cited. This is your baseline.
3. 3Audit the site for the four properties above.
4. 4Fix the highest-impact gaps — usually entity definition and structured data first, because they're cheap and immediate.
5. 5Publish the content that answers questions nobody on your site currently answers.
6. 6Re-run the same prompts a month later and compare against the baseline.

Step two is the one most teams skip, and skipping it makes the rest unfalsifiable. Without a baseline you can't distinguish a change that worked from a model update that happened to help.

How to measure it

There's no Search Console for answer engines, so the metrics are ones you construct:

• Mention rate — the share of tracked questions where you're named at all. The primary number.
• Citation rate — how often an answer links to one of your pages. Moves earlier than mention rate, which makes it a useful leading indicator.
• Position within the answer — being named first reads as a recommendation; being named fifth reads as a list.
• Competitor share — who gets named instead of you, and for which questions. Often the most actionable of the four.

Who it's worth doing for

AEO pays off fastest where purchases involve research and a recommendation carries weight: B2B software, professional services, agencies, healthcare, legal, considered consumer goods. It matters less for pure brand-name navigation, where someone already knows they want you.

The honest test is whether your buyers ask *comparative* questions before choosing. If they do, an AI answer is already shaping that decision — with or without you in it.