Feature
Query Fan-Out Analysis
See the hidden searches AI engines run before they answer — and win them.
When ChatGPT or Google AI Mode answers a buyer question, it doesn't run one search — it fans the question out into many hidden sub-searches and synthesizes the results. Those sub-queries decide which brands appear in the answer, and no classic keyword tool can see them.
Geonimo captures the actual fan-out queries engines run on your tracked prompts. The result is a keyword universe straight from the engines themselves: the exact sub-questions your content needs to cover to win the composed answer.
Real fan-out capture
When engines search the web before answering, Geonimo records the actual queries they ran — not simulations or guesses, but the engine's own retrieval behavior on your prompts.
Per-prompt breakdown
For each tracked prompt, see the sub-queries generated, how often each recurs across runs, and which ones your site currently has no content for.
Content gap mapping
Fan-out queries nobody has written a direct answer for are the cheapest visibility wins in AI search. Geonimo flags them so your next article targets a question the engine is already asking.
Cross-engine view
Fan-out behavior differs between ChatGPT and Google's AI surfaces. Geonimo shows both, so you can prioritize the sub-queries that matter on the engines your buyers use.
Why fan-out is the new keyword research
Classic keyword research optimizes for the query the user types. AI answers are composed from the queries the *engine* generates — a buyer prompt like "best CRM for consultants" can fan out into pricing comparisons, integration questions, review lookups and niche alternatives. If your content only targets the visible prompt, you're invisible to most of the retrieval that actually builds the answer. Query fan-out analysis moves your content strategy from the surface query to the retrieval layer.
From hidden queries to shipped content
Geonimo pairs each fan-out query with your current coverage: which of your pages (if any) could answer it, and which competitors' pages the engines retrieved instead. Uncovered recurring sub-queries feed directly into article generation — so the loop from "the engine asked this" to "we published the answer" closes in days. Teams using fan-out data consistently report the same surprise: the sub-queries are more specific, more commercial and less contested than anything in their keyword tool.
Frequently asked questions
What is query fan-out?
Query fan-out is how AI engines answer complex prompts: they decompose one question into many hidden sub-searches, retrieve results for each, and synthesize the answer. Google AI Mode and ChatGPT's web search both work this way. The sub-queries determine which sources and brands make it into the final answer.
How does Geonimo capture fan-out queries?
When engines expose their retrieval behavior during Geonimo's daily tracking runs, we capture the actual search queries they generated for your prompts — real engine behavior on your real prompts, not a simulation.
How do I use fan-out data in my content strategy?
Sort recurring fan-out queries by coverage: where you have no page that answers the sub-question, create one; where a competitor's page keeps being retrieved, study and beat it. Because these queries come from the engine itself, every piece of content maps directly to retrieval that already happens.
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