You type “red phone case” into an AI search engine. Behind the scenes that one question is split into ten others: which model, which material, does it discolour, which shop is trustworthy. That’s called query fan-out, and it changes how you get found. Ranking for one keyword is no longer enough.
What is query fan-out?
Query fan-out is the process by which an AI search engine automatically expands one query into multiple sub-queries, to give a more complete answer. One query is thus expanded into many, to give the model enough context. Where traditional search engines worked one-to-one (one query, one result list), fan-out flips that: one question triggers dozens of searches at once.
How it works, in six steps
- Analysis: the LLM determines the intent and complexity of your question in milliseconds.
- Decomposition: the question is split into sub-questions from different angles.
- Parallel retrieval: all sub-questions search simultaneously in web indexes, knowledge graphs and databases.
- Synthesis: the results are combined, with sources that appear in multiple lists counting more heavily.
- Scoring: each document gets a relevance score based on its position across those lists.
- Re-ranking: everything is reordered by total score into one answer.
Many of those searches are never typed by a person
This is where it gets interesting. The LLM invents these sub-questions itself, often about topics the user never explicitly mentioned. So they’re not keywords people search for; you can’t target them directly with a keyword list. The LLM can fire dozens of those searches at once on a single question, and also infers context from behaviour and history, not just your literal search terms. Google uses this fan-out technical SEO in its AI Mode.
Which sub-questions does an LLM ask?
- Disambiguation: vague questions are sharpened (“red case” becomes iPhone, Samsung or Pixel).
- Attributes: all dimensions of something, such as colour, material, features and compatibility.
- Customer journey stages: from orientation to comparison to purchase.
- Trust: for sensitive topics the LLM searches for reviews, proof and sources.
- Comparison criteria: what you judge something on, not just what the specifications are.
- Action and risk: is it feasible, what are the consequences, is the transaction sound.
From keyword to topic
This turns classic SEO logic on its head. Ranking for that one keyword is no longer enough; your content competes across a whole topic area. Whoever covers the topic fully and deeply gets included across more sub-questions. That’s exactly why topical authority becomes more important than individual keywords. A online shop with only a product page “red phone case” misses out as soon as the LLM asks about material, compatibility or anti-yellowing. A brand that also answers those sub-questions, with specifications, guides, reviews and structured data, gets cited across multiple sub-questions. The same goes for B2B: for “reliable IT partner for healthcare” the LLM fans out to certifications, sector experience and references.
One search becomes a whole conversation. Whoever focuses only on keywords misses half the questions the LLM asks on a potential customer’s behalf.
Giacomo Perticara, founder and SEO strategist at GRP Digital
What you can do now
- Map which sub-questions belong to your topic, not just your main keyword.
- Cover the topic fully with clusters: a strong hub page plus supporting pieces (topical authority).
- Fill your entity data completely: specifications, attributes, compatibility, with structured data.
- Place E-E-A-T signals prominently for sensitive topics: reviews, sources, expertise.
- Measure differently: track your visibility and citations at topic level, not just individual keyword positions.
Depth beats breadth
Query fan-out rewards the same thing we’ve long focused on: full, reliable coverage of a topic. That calls for a coherent whole that answers every logical sub-question.
Curious which sub-questions your brand is and isn’t included in right now? At GRP Digital we map it and close the gaps.
Sources: Google’s query fan-out technical SEO (Search Engine Journal) and Aleyda Solis.
