Answer engine optimization consulting
Short answer
Answer engine optimization (AEO) is the work of getting a brand named and linked inside the answers AI assistants give. I run AEO programs on tooling I build myself, measured in citations and share of voice across ChatGPT, Perplexity, Gemini and Google AI Overviews, and built on 13+ years of search work.
What the work covers
Entity and schema coverage: what a model already associates with your brand, where the associations stop, and the structured data and content that close the gap. Content built for extraction: the direct answer first, the sub-questions covered, structured so an engine can lift a clean passage. The authority behind it, and the technical foundation that lets engines retrieve the pages at all. An llms.txt file where it helps.
The work targets the retrieval pipelines and fan-out queries answer engines use to decide who to cite, so the fixes land on the mechanism rather than page by page, and all of it is tracked against named competitors on a researched prompt set.
How it is measured
Citation share and share of voice on the priority queries, by engine, month over month; the queries moved into cited positions; and the AI referral sessions and conversions behind them.
Questions I get asked
What does an AEO consultant do?
Measures where a brand stands in AI answers against its competitors, finds the entity, content and technical gaps that keep it out of them, closes those gaps in a prioritized program, and reports the citations every month. The tooling and the method are mine; the program runs on your site with your team.
How is AEO different from SEO?
SEO competes for a position in a list of results. AEO competes to be the source quoted inside a single composed answer, where there is no list and usually no second place. The foundations overlap heavily, which is why I run them as one program, and optimizing for a ranking and optimizing to be cited remain two different jobs.
How long until a brand gets cited?
It depends on where the gap is. Entity and schema work changes how a model resolves the brand, so it tends to show first; content-driven citation gains follow the content as it is published and picked up. The tracking shows each step as it lands, and anyone who quotes a fixed timeline before measuring is guessing.