Key takeaways
- AI search splits one question into many related background searches, then cites the pages that answer them best.
- In Surfer SEO’s study, pages that ranked for the main keyword and at least one fan-out query were 161% more likely to be cited in AI Overviews.
- The most reliable route to AI search visibility is clearly answering the questions buyers ask next, not chasing every possible fan-out query.
When someone asks Google’s AI Mode a question, it doesn’t run one search. It breaks the question into smaller ones, searches for each in the background, then builds its answer from whichever pages best answer those sub-questions. This is query fan-out, and it’s why ranking first for your main keyword no longer guarantees you’ll be cited in AI search.
What is query fan-out?
Query fan-out is the extra step AI search adds between a question and its answer: the AI splits one question into several related searches, then builds its response from the pages that answer them. It’s a bigger change than it sounds.
In traditional search, one query returned one set of results. You chose a target keyword, built a page around it and worked on getting into the top few positions.
With query fan-out, Google’s model works out the intent behind a question and runs a series of related searches, often covering angles the user never typed. It then pulls passages from the pages that answer those searches. Google says Deep Search, its research mode, can run hundreds of these background searches for a single question
Which searches trigger query fan-out?
Query fan-out mostly kicks in for complex, multi-part questions. A simple factual query rarely triggers it, but the considered, pre-purchase questions most Perth businesses care about usually do.
Query fan-out isn’t just a Google feature, either. Google coined the term, but ChatGPT and Perplexity take a similar approach, so this affects how you show up across AI search generally. With OpenAI now letting businesses claim profiles in ChatGPT, that visibility is only becoming more important.
Why do pages that answer follow-up questions get cited more often?
Pages that answer follow-up questions tend to get cited more often, most likely because they match the searches AI is actually running.
Surfer SEO’s study of 10,000 keywords found that pages ranking for the main keyword and at least one fan-out query were 161% more likely to be cited in AI Overviews than pages ranking for the main keyword alone. Surfer is clear that this shows a correlation rather than proof of cause, but the pattern is hard to ignore.
The study also looked at pages that didn’t rank for the main keyword at all. Those ranking only for fan-out queries still earned citations more often than pages ranking only for the main keyword.
For us, that changes how we plan content. Ranking for “SEO agency Perth” still matters for traditional search, but on its own it’s a weak route into AI answers. The pages getting picked up also cover what a buyer asks next.
What does query fan-out look like in practice?
Take a search like “SEO agency Perth”. The searcher wants more than a list of agencies, so an AI tool is likely to break the question into sub-questions such as:
- How much does an SEO agency in Perth cost per month?
- How long does SEO take to show results?
- What’s included in an SEO retainer?
- Is a local Perth agency better than a national one?
- How do I compare SEO agencies before signing a contract?
- What red flags should I look out for?=
- Do I need SEO, Google Ads or both?
- Can an agency help with AI search as well as Google rankings?
These are illustrative, since real fan-outs change from search to search, but the pattern holds. A typical agency service page answers one or two of them. The page more likely to be cited answers most of them, either directly or through clear links to supporting content such as a pricing guide or a page on GEO services.
How do you build a query fan-out strategy into your content plan?
The good news is that most of this builds on work you’re probably already doing. The difference is starting from the questions behind a keyword rather than the keyword itself. Here’s how to approach it:
1. Map the sub-questions for each priority topic
For every core service or product, list what a buyer needs to know before acting on it. Cost and timeframes are obvious starting points, along with eligibility, alternatives and the risks of getting it wrong. Your Search Console data and the questions your sales team hears every week are the best places to find them.
2. Put each answer under its own heading
AI tools pull passages, not whole pages. A heading that reflects the question, followed by a direct answer in the first sentence or two, gives them a clean section to use.
3. Split content sensibly across your topic cluster
Some sub-questions belong on the service page. Others, like a detailed pricing guide or a comparison between two options, work better as supporting articles that link back to the main page. Good SEO copywriting helps each one rank in its own right.
4. Keep your traditional SEO in shape
Fan-out queries are still searches, so a page has to rank somewhere before it can be cited. Solid technical SEO and fast load times still matter.
Should you target every fan-out query?
No. Trying to target every fan-out query is where it’s easy to get caught out.
Fan-outs shift with context and personalisation. Surfer found only about 27% stayed the same when a query was run again, so building content around a fixed list of them means chasing a moving target.
Research on ChatGPT points the same way. AirOps’ analysis of ChatGPT citations found that covering lots of fan-out subtopics barely registered. Pages were more likely to be cited when they ranked well and their headings closely matched the question.
We’d rather see a page answer five questions properly than skim over twenty. Thorough, well-organised coverage of the topics you know well, built around the questions customers actually ask, will hold up far better than a long page with the answers buried in it.
Need a hand planning content for AI search?
How should query fan-out change your GEO content strategy?
Query fan-out shifts the starting point of content planning from keywords to questions. Instead of planning one page per keyword, you plan around the questions a customer asks on the way to buying, then decide where each one is best answered.
That changes how you review existing content, too. When we review priority pages for our Perth clients, we ask one thing of each: if the AI broke this customer’s question into ten smaller ones, how many could this page answer clearly? Pages that only cover the main keyword become candidates for expanding, or for supporting articles that fill the gaps.
A GEO content strategy built this way also holds up as AI search changes, because it’s based on what customers need to know rather than how a particular tool works today.
For more background, read our guides to optimising for Google’s AI Mode in Australia and how AI Overviews work in Australia.
Why partner with White Chalk Road?
As Perth’s longest-running search agency, White Chalk Road has been helping businesses get found online since 1999. Our team maps the questions behind your priority keywords and fills the gaps in your existing content with structured, human-written pages built for both traditional and AI search.
You’ll work with a dedicated marketing manager who explains what’s changing and what it means for your results, in plain English.
Get in touch to talk about building a GEO content strategy for your business
FAQ
Not quite. Long-tail keywords are phrases real people type. Fan-out queries are generated by the AI and change from search to search. There's overlap, but you can't download a list of them the way you can with long-tail terms.
To measure AI search visibility, look beyond rankings for your main keyword. Google Search Console shows which related queries a page appears for, and AI visibility tools such as Ahrefs Brand Radar or Surfer's AI Tracker can monitor mentions and citations in AI Overviews, AI Mode and ChatGPT.
No. Fan-out queries are still searches, and AI tools draw on the same search results to find content. A page has to rank somewhere before it can be cited, so the fundamentals, like site speed, crawlability and quality content, matter as much as ever.