Query fan-out is expanding one customer question into the many phrasings an engine actually sees. Nobody asks in exactly one way, so measuring or optimizing against a single query misses most of the answers being given about your category.
Why it matters
Real customers ask the same thing a dozen ways: the category, the head-to-heads, the how-to, the alternatives, the is-it-worth-it. An engine answers each of those, and you can win some and lose others.
Test with one query and you get one data point that may not be representative. Fan the question out and you see the shape of your category as the engines actually answer it.
It also guards against flattering yourself. A single query you happen to win says little; the spread across the phrasings people really use is the honest read.
How Jinn treats it
Fama expands a brand into a set of questions from its own record: category recommendations, branded reviews, competitor head-to-heads, plus buyer-intent phrasings like alternatives, how-to, and definitional. The questions are built from the brand's category, name, and competitors, not a generic list.
It then asks those questions across six answer engines: ChatGPT, Perplexity, Claude, Gemini, Grok, and Google's AI Overviews, so the reading covers the phrasings and the engines your customers actually use.
Related terms
One question, the way everyone really asks it.
Fan a question into the phrasings engines actually see, across six of them. See how Fama does it.