What Is Query Fan-Out?
AI search doesn't run your query. It runs a dozen related ones in the background and builds the answer from all of them. Here is how that changes what content wins.
What you’ll learn
- What query fan-out is and which AI search engines use it
- The seven kinds of sub-queries and what each one looks for
- Why pages that don't rank for a query can still be cited for it
- How to plan content around sub-queries
Query fan-out is a technique where an AI search system rewrites one user question into many related searches, retrieves results for each one, and combines them into a single answer. Google described it publicly when it launched AI Mode in 2025, and the same idea is behind AI Overviews, ChatGPT search and Perplexity.
An example
Someone asks: best CRM for a small business. A classic search engine ranks pages for that phrase. An AI search system might quietly run:
- crm pricing per user 2026
- hubspot vs pipedrive for small teams
- crm with gmail integration
- free crm for 3 users
- how hard is it to switch crm
It reads the best passages from each result set and writes one answer that covers price, comparisons, integrations and switching costs, with sources from all of them.
Why it matters for SEO
Fan-out breaks the link between ranking for a query and being cited for it:
- A page that ranks tenth for “best crm” can be the top source for “crm with gmail integration” and get cited in the answer.
- A page that ranks first for “best crm” but never mentions pricing can lose the pricing part of the answer to someone else.
Coverage of the sub-questions matters as much as relevance to the main question.
Seven kinds of sub-queries
| Type | What it looks for | Example |
|---|---|---|
| Related | Neighbouring topics | sales pipeline software |
| Implicit | Needs the user didn’t state | crm that works with gmail |
| Comparative | X vs Y, alternatives | hubspot vs zoho |
| Reformulation | Same intent, other words | customer management tool for startups |
| Entity | Specific brands and products | pipedrive pricing |
| Follow-up | The next likely question | how to migrate contacts |
| Personalized | The user’s context | crm for a 5-person agency |
Our Query Fan-out Generator predicts sub-queries for any query, grouped by these types.
How to optimize for fan-out
- List the sub-queries for your main topics. Use the generator, “People also ask”, and the questions your customers ask in sales calls.
- Check coverage. Add your page URL in the generator to see which sub-queries the page covers, partly covers or misses.
- Give each important sub-query its own section with a heading that matches it and a first sentence that answers it. Sections are retrieved separately, so one clear section beats a mention buried in a paragraph.
- Build comparison and alternative pages for comparative sub-queries. They are among the most cited page types.
- Link the cluster. Sub-queries better served by another page should be linked from this one.
Limits
Search engines don’t publish their real sub-queries, and they vary by user, location and conversation history. Any tool, including ours, predicts likely ones with a language model. Use the list for planning, not as measured data.