Pages that rank for a primary search query and at least one related fan-out query are more likely to be cited in Google AI Overviews than pages ranking only for the main query, according to new research from Surfer SEO. The finding does not prove that expanding coverage causes citations. It does, however, give website owners a practical signal for finding content gaps that may matter in AI-assisted search.
In its analysis of query fan-out and AI Overview citations, Surfer SEO examined 173,902 URLs across 10,000 keywords and identified 33,000 related fan-out queries. The central pattern was clear: 51.2% of cited pages ranked for both the main query and at least one fan-out query. That was a substantially larger share than pages that ranked for only one of those query types.
For content teams, the useful implication is not to add every adjacent keyword to a single page. It is to use related queries as evidence of questions, subtopics, and needs that existing coverage may not answer well. That can help prioritize work where broader topical coverage may improve a site's chances of being useful to both conventional search users and AI-generated results.
What the research shows about AI Overview citations
Google's query fan-out approach can be understood as the set of related searches an AI system may use to assemble an answer to a broader request. A person searching for a business software category, for example, may need definitions, setup guidance, pricing context, comparisons, limitations, or implementation details. Those are distinct information needs, even when they sit close to the original query.
Surfer SEO's study found a 0.77 correlation between fan-out coverage and citation likelihood. That is a high correlation, but it is not evidence of causation. Pages that cover related topics may also be better researched, more comprehensive, more authoritative, or more closely aligned with the information Google needs for an AI Overview. The study itself cautions against treating fan-out coverage as an automatic citation formula.
| Ranking pattern | Share of AI Overview citations in the study | What it suggests |
|---|---|---|
| Main query plus at least one fan-out query | 51.2% | Broad coverage across related searches was the most common pattern among cited pages. |
| Fan-out queries only | 29.2% | Pages can be cited even when they do not rank for the main query. |
| Main query only | 19.6% | Ranking for the headline query alone was the least common of the three patterns. |
The research also found that approximately 67.82% of AI Overview citations did not rank in the top 10 for either the main query or any fan-out query. That result is an important constraint on any simple SEO interpretation. Traditional rankings remain relevant, but AI Overviews can pull from sources beyond the most visible organic results. A content plan built solely around current top-10 positions is therefore likely to miss useful citation opportunities.
Turn fan-out findings into a content-gap process
The practical use of this research is prioritization. Start with a page or topic that already matters commercially, then review the related questions and subtopics that users may need before they can make a decision. Compare those needs with what your site actually covers, not merely with the keywords already placed on one URL.
A focused workflow can include:
- Identify a primary query connected to a product, service, or customer problem.
- Map relevant fan-out queries to the questions they represent, such as setup, alternatives, costs, use cases, or limitations.
- Audit whether existing pages answer those questions clearly and accurately.
- Decide whether the gap belongs in the existing page or warrants a separate, tightly focused resource.
- Improve the weakest high-value gaps first, then monitor citations and visibility alongside conventional search performance.
This approach helps avoid a common failure mode: turning a useful page into a long, unfocused collection of loosely related phrases. The study's broader takeaway is topical authority, not maximal keyword coverage. A strong content library can use distinct pages for distinct needs while connecting them through clear topical relationships and internal links.
What this means for content costs and AI workflows
For businesses with limited editorial capacity, citation-oriented analysis can make content investment more selective. Rather than commissioning broad updates across an entire site, a team can look for gaps around topics that already have clear demand and commercial relevance. The result may be fewer low-value articles and more complete coverage around the subjects prospective customers actually investigate.
AI-assisted drafting and research workflows can support that process, but they should not replace editorial judgment. Teams still need to verify whether a proposed fan-out topic is genuinely relevant, whether a new page would duplicate existing material, and whether the final content provides an accurate answer. Automation is most valuable when it speeds up discovery, clustering, and first-pass auditing while people retain responsibility for prioritization and quality.
For businesses trying to understand where they appear in AI-generated answers, Scalevise's AI Visibility and GEO Checker can help turn scattered citation signals into a practical content priority list. Scalevise helps teams identify visibility gaps, connect them to customer questions, and focus editorial effort on coverage that supports discoverability rather than producing more generic pages. This creates a clearer basis for spending content time and budget. Start an AI Visibility scan.
Frequently Asked Questions
What is a query fan-out in Google AI search?
A query fan-out is a set of related searches an AI system may use to gather information for a broader user request. These related searches can reflect subtopics, follow-up questions, comparisons, or practical details connected to the main query.
What did Surfer SEO find about fan-out coverage and AI Overview citations?
Surfer SEO found that 51.2% of AI Overview citations came from pages ranking for both the main query and at least one fan-out query. Pages ranking only for the main query accounted for 19.6% of citations in the study.
Does ranking for more fan-out queries guarantee an AI Overview citation?
No. The study found a 0.77 correlation between fan-out coverage and citation likelihood, not proof that one causes the other. Google AI Overviews can cite pages for reasons beyond ranking positions and query coverage.
Should one page target every related fan-out query?
No. The research cautions against blindly chasing fan-outs. The more useful approach is to build broad, relevant topical authority through content that answers distinct user needs clearly.
Why should businesses track AI Overview citations separately from rankings?
About 67.82% of citations in the study did not rank in the top 10 for the main query or any fan-out query. That indicates AI Overviews can select sources beyond the most visible conventional rankings.
Conclusion
Surfer SEO's findings make fan-out coverage a useful citation-centric signal, not a guaranteed optimization tactic. Pages that address a main query alongside relevant related needs appeared more often in Google AI Overviews citations, while many cited pages also came from outside top-10 rankings. The practical opportunity is to use those patterns to find meaningful coverage gaps, strengthen topical authority, and prioritize content work with greater discipline.
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