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Query Fan-Out

James Dooley discusses how to rank for and track fan-out queries, and measures Recommendation Sculpting across the variations a buyer question can fan out into.

Also known as query fan out and fan-out queries.

What is query fan-out?

Query fan-out is the technique in which an AI search system splits a question into several related sub-queries, runs them at the same time and combines the results into one answer. Google described the technique by that name when it announced AI Mode on 5 March 2025.

How does James Dooley define query fan-out?

James Dooley has discussed query fan-out with Luis Salazar Jurado and Sergey Lucktinov: how to rank for fan-out searches, how fan-out differs from query augmentation, and how to find out which fan-out queries were searched.

How does James Dooley apply query fan-out?

Query fan-out fits the way Recommendation Sculpting is measured: prompt by prompt across a matrix of competitors, attributes and locations, because one buyer question can be answered from many sub-queries. A topical map that covers those sub-queries gives a brand more chances to be drawn into the answer. For clients, the work is delivered through Be The Brand AI Recommends.

Why does James Dooley think query fan-out matters?

A business that appears only for the headline query can be missing from most of the searches an AI system runs to answer it. Covering the likely sub-queries is how a brand stays in the answer.

How does query fan-out relate to DEO, AEO and GEO?

Query fan-out is part of how answer engines and generative engines build their answers, so it matters to AEO and GEO. In Decision Engine Optimisation, the sub-queries about price, reviews and location are often where the choice between suppliers is made.

Who coined query fan-out and when?

Google described query fan-out when it announced AI Mode on 5 March 2025, in Expanding AI Overviews and introducing AI Mode by Robby Stein, and explained it further at Google I/O on 20 May 2025 in AI Mode in Google Search: Updates from Google I/O 2025 by Elizabeth Reid.

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  • Answer Engine Optimisation (AEO): Answer engine optimisation (AEO) is the practice of structuring content and brand information so that answer engines, such as featured snippets, voice assistants and AI assistants, use it in the answers they give.
  • Generative Engine Optimisation (GEO): Generative engine optimisation (GEO) is the practice of improving how content and brands appear in answers produced by generative AI search engines.
  • Recommendation Sculpting: Recommendation Sculpting is a method within Decision Engine Optimisation that turns AI recommendations of a competitor into recommendations of the client, measured prompt by prompt.
  • Topical Map: A topical map is a structured plan of the topics, subtopics and connections a website needs to cover to build topical authority.
  • Semantic SEO: Semantic SEO is the practice of optimising content around entities, their attributes and the relationships between them, so that search engines understand its meaning rather than matching keywords.

Every term James Dooley uses is defined in the James Dooley Lexicon, and the verified facts about him are in the Brand SSOT.