Definition: answer engine optimisation (AEO) is the practice of structuring a business's online presence so that AI assistants and AI search features name and recommend it inside a generated answer, rather than merely listing it among search results.
Why this became a separate discipline
For twenty-five years the goal of search marketing was a position on a page. Rank first, get roughly a third of the clicks. Rank tenth, get a trickle. The page had ten slots and the economics followed from that.
An AI-generated answer has no slots. It names two or three businesses in a sentence and the interaction ends. There is no second page, and ranking fourth is not a worse result — it is no result, because nobody reads a fourth place that was never displayed.
That is the whole reason AEO exists as a distinct practice. The target changed from being listed to being named, and the two require overlapping but genuinely different work.
What an answer engine is
An answer engine is any system that responds to a question with a composed answer instead of a list of links. In practice that means:
- ChatGPT and its search mode
- Google AI Overviews, the generated block above the traditional results
- Google Gemini
- Perplexity
- Microsoft Copilot
- Voice assistants, which have worked this way for years
How a model decides who to name
Nobody outside the labs knows the precise weighting, and anyone claiming otherwise is guessing. But the mechanics are observable, and four factors come up consistently.
Entity clarity
A model has to be able to identify your business as a distinct thing before it can recommend it. That means a consistent name, address and phone number everywhere, explicit structured data, and no ambiguity with similarly named businesses. This is the most common failure, and it is unglamorous to fix.
Corroboration across sources
Models weight claims that appear in several independent places. A business described the same way on its own site, its Google Business Profile, a directory and a local news mention is far more likely to be named than one that only describes itself.
Extractable answers
Content phrased as a question with the answer immediately underneath is easier to lift than the same information buried in a paragraph of marketing copy. This is why FAQ sections punch above their weight: they match the shape of the thing being generated.
Reviews and recency
For local services, review volume and how recent those reviews are correlate strongly with being named. A model summarising “best plumber in Sydney” is leaning on the same public signals a human would skim.
What AEO work actually involves
- Baseline measurement. Run a fixed set of real customer questions against each assistant and record verbatim who gets named.
- Structured data. Implement schema.org markup —
Organization,LocalBusiness,Service,FAQPage— so machines can parse the business without inference. - Entity reconciliation. Make every public mention of the business agree with every other one.
- Answer-shaped content. Write the questions customers ask, and answer each one in the first sentence.
- Review generation. Build a repeatable way to ask happy customers for a review, because the signal decays.
- Re-measurement. Re-run the exact prompts from step one on a schedule and compare.
Does AEO replace SEO?
No, and treating it as a replacement is a mistake. Most of the sources a model draws on are the same pages that rank in conventional search. Strong SEO is a precondition for AEO rather than a competitor to it. What changes is the goal you optimise those pages toward: extractability and entity clarity, rather than click-through rate alone.
If you want the distinction between AEO, GEO and conventional SEO laid out side by side, we have written that comparison separately.