76% of 10,000 keywords triggered AI overviews in a large analysis that mapped how search answers pull from many pages. The scale of the data makes the shift hard to ignore: 173,902 URLs, 33,000 fan-out queries and clear patterns in which pages get cited.
Researchers used Gemini to generate follow-up queries and scraped top results to see which pages appear in overviews. Pages that rank for both a main query and at least one related fan-out were far more likely to be referenced. That change affects how sites win visibility in search, especially in Italy.
The work reports a Spearman correlation of 0.77 between fan-out breadth and citation likelihood, and it shows many cited sources don’t even sit in the top 10 results. This tells marketers that broader topical coverage can matter as much as classic ranking signals for being included in overviews.
Key Takeaways
- The analysis used 10,000 keywords and hundreds of thousands of URLs to map citation patterns.
- Ranking for both a main query and fan-out queries raised the odds of being cited significantly.
- Topical breadth matters: many cited pages did not rank in the top 10.
- A Spearman 0.77 correlation shows the effect is measurable, not anecdotal.
- Search visibility strategies should balance core ranking work with wider topic coverage.
Breaking: AI Overviews favor pages spanning fan-out queries, reshaping SEO visibility
When a page ranks for several related queries, it earns a clear edge in overview selections. The analysis shows a large lift for pages that appear for both a main query and at least one fan-out query. That pattern reshapes how brands should think about search and organic visibility in Italy.
Key data: pages ranking only for fan-out queries were cited 29.2% of the time versus 19.6% for main-only pages. Pages covering both types were substantially more likely to receive citations, indicating systems favor broader topical context when building summaries.
This means a single top ranking for a main term is less decisive now. Teams should focus on content that answers follow-up questions and ties subtopics together.
What this means for search, rankings, and organic visibility right now
- Breadth matters: diversified coverage across related queries increases the chance a page is referenced in overviews.
- Content clusters: build pages that address multiple FAQs and subtopics to improve citation potential and results exposure.
- Track citations: add citation tracking to traditional SEO metrics to capture this alternate pathway to visibility.
Inside the data: How the study measured AI Overview citations and query coverage
Researchers built a broad dataset to measure how often system summaries reference specific pages. The work examined the top 10 rankings for 10,000 keywords and found that 76% triggered overview summaries. In total, the dataset included 173,902 URLs.
Scope and sources
The team used a mix of main keywords and generated follow-ups. Google’s Gemini produced 33,000 fan-out queries, and the top 10 organic results for each follow-up were scraped.
Method
The analysis aligned which URLs appeared in overviews with their organic positions for both main and fan-out queries. This created a consistent baseline for comparing coverage and inclusion.
Why this matters
Key metric: a Spearman correlation of 0.77 shows a clear link between how many related queries a URL ranks for and its chance to be shown in summaries. That link helps teams prioritize topical breadth in search strategies.
- Scale: 10,000 keywords and 173,902 URLs give the data weight.
- Process: fan-out queries and top-10 mapping create repeatable measurement.
- Actionable: coverage across related queries increases visibility in system-generated answers.
AI Boosts Citation Odds by 161%: Study
The analysis found a sharp lift in how often pages get referenced when they cover both main terms and related follow-ups.
The lens: pages that rank for a main query and at least one fan-out query were 161% more likely to appear as citations in overviews. This result comes from cross-referencing overview citations with organic positions across 173,902 URLs.
The 161% lift when ranking for both main and fan-out queries
This lift shows broader topical coverage pays off. Teams in Italy should see it as a practical route to better search visibility without chasing single-term dominance.
Spearman 0.77 correlation between fan-out coverage and overview citations
The analysis also reports a Spearman correlation of 0.77. That strong link ties the number of fan-out queries a URL ranks for to its chance of being cited.
- Central finding: wider coverage improves chances of appearing in citations.
- Actionable insight: map pages to related queries, not just one keyword.
- Result: measure visibility via inclusion in overviews as well as rankings.
Fan-out vs. main query: Which ranking matters more for AI citations?
Pages that capture multiple follow-up queries often earn more references than single-term leaders. The dataset shows pages ranking only for fan-out queries were cited 29.2% of the time, while main-only pages reached 19.6%.
This gap equals a 49% relative advantage for fan-out coverage. That suggests search systems favor topical breadth and context when choosing sources for overviews.
What the numbers mean in practice
Practical takeaway: a page that answers multiple follow-ups can increase its likelihood of appearing in system summaries even without top main-term placement.
“Cover the common follow-ups and you increase the chance a page will be selected as a source.”
| Type of ranking | Inclusion rate | Relative advantage |
|---|---|---|
| Fan-out only | 29.2% | +49% vs. main-only |
| Main query only | 19.6% | Baseline |
| Both main and fan-out | Higher (dataset peak) | Best overall |
- Action: map target queries into clusters of related topics.
- Use on-page FAQs and supporting pages to cover follow-up intent.
- Prioritize easier fan-out queries to build topical authority in Italy.
Organic rankings aren’t everything: Where AI Overviews pull citations
Overview selections often draw from a wide pool of pages, not just the top listings. The dataset shows most referenced sources sit outside the first page of results.
Key data: 67.82% of citations came from URLs that did not rank in the top 10 for either the main query or any fan-outs. That means system summaries often tap into lower-ranked material for context and nuance.
What the numbers reveal
Still, the most visible entries behave differently. For the top three citations shown by default, 54.14% did rank in the top 10. In short, stronger organic positions help secure the most prominent spots.
- A majority of citations originate outside the top 10 organic results, so ranking position isn’t the sole path to inclusion in overviews.
- The top three visible citations are more likely tied to higher rankings, linking classic SEO work to visibility.
- Teams should track citations as a complement to ranking reports to measure full search impact.
- High-quality, well-structured pages can be surfaced as references even before breaking into page one.
Strategy shift: From keyword targets to topical authority and content clusters
Build for topics, not isolated terms. Teams in Italy should prioritize hubs that map the full spectrum of related queries. This reduces wasted effort chasing fleeting follow-ups and creates durable gains in search presence.
Build clusters that map to fan-out intent without chasing every query
Only about 27% of fan-out queries stay consistent across repeated runs. That makes exhaustive scraping less useful.
Plan topic-driven architectures that group FAQs, comparisons, and how-tos around core pages. This approach is more scalable than pursuing every variant.
Start with lower-difficulty fan-out topics to grow authority over time
Begin with easier fan-out areas to gain traction. As authority grows, ladder into tougher queries.
This stepwise tactic helps your marketing teams show steady gains in visibility and in-cite placement for key pages.
Align content depth, semantic coverage, and seo services for sustained visibility
Combine solid seo fundamentals—internal linking, schema, and clear hierarchies—with semantic content development.
Integrate specialized services such as entity mapping and topical gap analysis to support repeated selection in system summaries.
- Shift from single-keyword plans to topic clusters that anticipate related queries.
- Prioritize durable topical authority over chasing every follow-up variant.
- Measure success by rankings and by citations in generated answers.
| Step | Focus | Expected outcome |
|---|---|---|
| Cluster design | Core topic + subtopics | Broader topical authority |
| Initial targets | Lower-difficulty fan-outs | Early traction in search |
| Ongoing work | Semantic depth & services | Sustained visibility and citations |
Conclusion
The data and analysis show topical breadth is the clearest predictor of being likely cited in overviews. Pages that rank for both main and fan-out queries were far more likely to be referenced, and a Spearman correlation of 0.77 ties broader coverage to inclusion.
Key numbers matter: the dual-coverage lift is large, 67.82% of cited pages sit outside the top 10, and 54.14% of the top three citations do rank in the top 10. Fan-out-only pages reached 29.2% inclusion versus 19.6% for main-only.
Action: build content clusters, start with lower-difficulty fan-outs, and align SEO with marketing services. Track where pages are cited over time and refine clusters to improve the chance of being likely cited in search summaries.
FAQ
What does the study mean by “fan-out” queries?
Fan-out queries are related search intents that expand on a main keyword. The study generated thousands of these queries to map how pages cover a topic beyond a single query. Pages that serve both the main query and many fan-out queries show broader topical coverage, which increases their chances of being referenced in AI overviews and other response features.
How large was the dataset behind the findings?
Researchers analyzed 10,000 seed keywords and 173,902 URLs. They identified that roughly 76% of keywords triggered overview features. The method used tens of thousands of fan-out queries and mapped top-10 results to measure citation patterns and reach.
What method was used to produce fan-out queries?
The team used a large language model to generate about 33,000 fan-out queries from the original seeds, then recorded which pages ranked in the top 10 for those queries. This mapping showed how coverage across many related queries ties to being cited in overviews and other answer surfaces.
Why does ranking for fan-outs matter more than a single main keyword?
Pages that cover many related intents demonstrate topical authority. The study found pages ranking only for fan-out queries were cited more often than pages ranking only for the main keyword. In practice, breadth of coverage helps systems select a page as an authoritative source.
Do top organic positions still influence which pages are cited?
Yes, but not exclusively. A large share of references come from pages outside the traditional top results. While the top three positions get many citations, over half of citations reference pages that are not in the top 10, showing that systems look beyond classic blue links.
How strong is the link between fan-out coverage and being cited?
The analysis reported a high correlation between the number of fan-out queries a page covers and its likelihood of being referenced. This suggests that covering more related queries reliably increases the chance of selection by overview systems.
What practical SEO changes should publishers make?
Shift from targeting single keywords to building content clusters that map to fan-out intents. Focus on semantic depth and topical breadth, prioritize lower-difficulty related topics to scale authority, and coordinate with AI SEO services to optimize content for both search and overview features.
How can teams measure progress on fan-out coverage?
Track rankings across a set of fan-out queries, monitor how often a page appears in answer features, and analyze changes in referral and organic traffic from related queries. Use query mapping and coverage dashboards to spot gaps and prioritize content updates.
Are there quick wins for getting referenced in overviews?
Yes. Start by adding clear, concise sections that answer common related questions, use structured headings to match fan-out intent, and expand FAQs or how-to steps. Target lower-competition fan-out topics first to build topical signals that attract more citations.
Which tools or services help implement this strategy?
Content research platforms, rank trackers that support custom query sets, and specialized AI SEO tools can generate fan-out lists and measure coverage. Many agencies and platforms offer semantic clustering and content-gap analysis to support this approach.
