What is query fan-out?
Query fan-out is when an AI engine splits one question into several related searches and builds its answer from all the results. A buyer asks one question. Before answering, the engine may search for the parts of it separately: the category, the constraints, the comparisons, the prices. The answer is then written from whatever those searches returned, which is why a page can be cited for a question it never mentions.
How does query fan-out work?
Query fan-out works by turning one question into several narrower searches, running them, and combining what comes back into one answer. Google says both AI Overviews and AI Mode may issue multiple related searches across subtopics and data sources to build a response (Google Search Central).
Engines that search the web do something similar whenever they decide a question needs fresh sources. The searches are rarely shown in full to the person asking, but they decide which pages are read, and so which brands the answer can name.
What does a fan-out look like?
Take "What is the best electric SUV for a family of five?". An engine might search separately for three-row electric SUVs, real-world range with a family load, and cargo space comparisons between specific models, then write one answer from the results. The example is illustrative; the searches an engine actually runs differ by engine and by run.
The public Tesla example (4 Oct 2026) shows the effect on sources. Google AI Overviews, which Google says may use fan-out, cited youtube.com 20 times and reddit.com 15 times across 25 buyer questions, and tesla.com once. Asked for the best home battery for whole-house backup, it did not name Tesla, while ChatGPT, Perplexity and Claude all named the Powerwall 3. The pages that answer the sub-searches are the ones that shape the shortlist.
Why does query fan-out matter for AI visibility?
It matters because the competition is for the sub-searches, not just the question. A page that answers one sub-question better than anyone else can be cited for a dozen buyer questions that share it.
- Pricing, limits and plan details are common sub-searches. A page that states them plainly is easy to use.
- Comparison sub-searches ("X vs Y", "X alternatives") pull in comparison and list pages, often written by third parties.
- Trust sub-searches (reviews, complaints, "is X legit") pull in review and forum pages, which you earn rather than write.
- Constraint sub-searches (team size, budget, integrations) reward pages that say who a product is for and who it is not for.
How can I find the searches an engine ran for my questions?
Some engines expose part of them: Perplexity shows related questions beside its answers, and for AI Overviews you can approximate the sub-searches by searching the sub-topics yourself. A tracking tool can record the follow-up searches and related questions engines return for each buyer question, so you can see which sub-searches recur across questions and engines.
Treat the recurring ones as a content brief. If several buyer questions fan out into the same pricing or comparison search, the page that answers it is worth more than a page that answers any single question. See prompt coverage for building the question set the fan-outs come from.
Where do you see query fan-out in Proofsource?
Under Prompts, Engine searches in Proofsource lists the follow-up searches and related questions the engines returned for each tracked question, how many answers suggested each one, and which engines ran them. The Prompts feature page shows the screen.
Common questions about Query fan-out
Do I need a page for every fan-out search?
No. Find the sub-searches that recur across many of your buyer questions and make sure one clear page answers each of them. A plain pricing page or an honest comparison page can serve many questions at once.
Is query fan-out only a Google thing?
Google documents it for AI Overviews and AI Mode by name. Other engines that search the web also run more than one search for some questions and show related questions, but how often and how many varies by engine and by run.
Can I optimise for fan-out with special markup?
No special markup is needed. Google says you do not need new machine-readable files or special markup to appear in AI Overviews or AI Mode. The pages that win sub-searches are indexable, readable without JavaScript, and answer the sub-question directly.
Why was my page cited for a question it never mentions?
Most likely because it answered one of the searches the engine ran while building the answer. That is fan-out at work, and it is a sign the page is useful for that sub-question.
Related terms
- Prompt coverage
Prompt coverage is how much of your set of tracked buyer questions AI engines answer with your brand named, broken down by question, topic and engine.
- Google AI Overviews
Google AI Overviews are the AI-written summaries Google shows above some search results, with links to the pages they draw on.
- Citation share
Citation share is the share of all the citations in AI answers that point at a given website.
- Answer engine optimization (AEO)
Answer engine optimization (AEO) is the work of getting your brand named, and your pages cited, in the answers AI assistants give.
Worked example: Tesla, public AI answers, 4 Oct 2026: Proofsource's first scan of Tesla, 25 buyer questions and 5 brand questions, one answer per question on each of four engines. A small sample from one brand, shown as an example, not a benchmark.
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