What is AEO? Answer engine optimization, explained.

Answer engine optimization (AEO) is the work of getting your business named, cited, and accurately described in the answers AI assistants give. When someone asks ChatGPT or Perplexity “who should I hire?” or “which one is best?”, the engine composes a single answer with a few names in it. AEO is how you become one of those names — and how you find out, day by day, whether you are.

Why AEO exists now

Buying research is moving from results pages into answers. Google itself now answers ahead of its own links: roughly half of searches return an AI Overview before the first organic result, and clicks fall sharply when it does.

The uncomfortable part is that a strong Google presence does not carry over. Ranking well and being recommended by AI are different contests with different rules:

That gap is the whole discipline. The businesses AI names first are not automatically the ones Google ranks first — they're the ones whose pages, structured data, and reputation the engines can read, trust, and quote. For how this plays out engine by engine, start with how ChatGPT actually picks businesses.

How answer engines decide who to name

Every major engine works from some mix of two pipelines, and the mix is what makes each one different:

• Model knowledge.What the engine learned in training: your brand's footprint across the public web as it existed months ago. This is why an engine can describe a business confidently — and describe it wrong.
• Live retrieval.What the engine looks up when asked: a web search run against an index, cited sources in Perplexity, Google's own index for AI Overviews. This pipeline is the one you can move in weeks rather than model-release cycles.

Retrieval-side answers favor sources that are easy to quote: pages that answer a specific question directly, structured data that states facts unambiguously, and third-party places where real people discuss you — reviews, directories, and community threads (Reddit most of all). And the winners are not fixed:

What the work actually is

Strip away the vendor language and AEO is five repeating jobs. (The full step-by-step lives in the AEO playbook.)

1. Measure. Ask the engines the questions your buyers ask, and record who gets named. Once is a snapshot; the answers drift, so real measurement is a cadence.
2. Diagnose. Work out why the current names win — which sources the engines cite for them, and which of those positions are genuinely contestable.
3. Build. Ship the assets engines quote: structured data (schema), FAQ and answer pages aimed at specific questions, and the page shapes each engine prefers.
4. Distribute. Get into the indexes and conversations the engines read — Bing among them, on the strength of the overlap above — plus the review sites, directories, and communities they cite.
5. Prove. Tie the work back to outcomes: did the page you shipped start getting cited? Did AI-referred visitors show up? Without this step, nobody can tell effort from progress.

What it costs to compete

The market has three price floors: monitoring tools at $29–399/month (published list prices, verified August 2026) that tell you where you stand, software that also does the building, and human agencies at $2,000–6,000/month retainers (2026 market research). The honest breakdown of all three — including when each is the right call — is in how much AEO costs in 2026 and what AEO services actually deliver.

A note on who's writing

AEO Action publishes this library, and the product runs the loop above as software: daily scans that ask the live engines your buyers' questions, an autonomous department that prepares schema, FAQ pages, landing pages, and Reddit packs, publishing after your one-click approval, Bing submission, and a dated receipt when a landing page you approved gets cited. Weigh our recommendations with that in mind — the mechanics on this page are true regardless of whose tooling runs them.