You worked for months to get your page into Google’s top 10. But when Google generates an AI Overview, it cites a website outside the top 20.
Frustrating, right? But it’s more common than you might think.
According to seoClarity’s analysis of 362,000 Google searches, 44% of AI Overview citations came from URLs outside the top 20 organic results.
seoClarity
That’s nearly 1 in every 2 citations.
So, does ranking on Google matter less now? Or is AI search looking beyond the pages that rank highest for a query?
In this article, we’ll explore what the research reveals about AI citations, how topical coverage affects AI search visibility, and what SEO teams can do to find new opportunities beyond traditional rankings.
Where Does That 44% Actually Come From?
seoClarity analyzed approximately 5.1 million citations across 362,000 Google AI Overviews, using US desktop search results collected on October 12, 2025. And they found:
- 56% of citations came from URLs ranking in Google’s top 20.
- 44% came from outside the top 20.
- 94% of AI Overviews cited at least one URL from the top 20.
- URLs ranking at position #1 were cited in the corresponding AI Overview 43% of the time, compared with just 7% for position #20.
The numbers tell us two things.
Higher organic rankings still provide a significant advantage. But being outside the top 20 doesn’t necessarily exclude a URL from an AI Overview.
That raises a more specific question.
Could a website’s visibility across related topics be connected to its chances of earning citations, even when it doesn’t rank for the exact query?
A second study offers useful evidence.
How Does Topical Coverage Affect AI Search Visibility?
In September 2026, Floyi published The Topical Authority Report 2026, analyzing 42 topical maps, 29,319 topics, and over 354,000 AI citations across Google AI Overviews, AI Mode, ChatGPT, and Gemini.
For Google AI Overviews, citations fell into three groups.
- 59.8% of citations went to websites ranking in the top 20 for the exact query.
- 27.5% went to websites ranking elsewhere in the same topical map, but not for the exact query.
- 12.7% went to websites with no top-20 rankings within the studied map.
That middle group is particularly interesting. Floyi calls these off-query citations.
These off-query citations went to websites with ranking visibility elsewhere in the same topical map, even though they didn’t rank in the top 20 for the original query.
Importantly, this measures website-level visibility, not whether the cited page itself ranked for another topic.
While the study uses a different dataset and methodology from seoClarity’s research, both point to the same question.
Are we missing part of the AI visibility picture by tracking individual keyword rankings alone?
Does Broader Topical Coverage Correlate With AI Citations?
The data suggests a connection.
Websites ranking in Google’s top 20 for at least half of the topics in a studied map appeared in 30.8% of citing AI Overviews, compared with just 0.14% for websites ranking for fewer than 5% of topics.
The study also found a positive correlation of 0.51 between ranked topical coverage and AI citation presence.
So, broader topical visibility is associated with more AI citations. But correlation doesn’t mean causation.
The question is whether topical coverage offers any additional advantage beyond ranking position itself.
What This Means for Your SEO Strategy
At Miraiyo, we believe AI search visibility shouldn’t be measured by keyword rankings alone. It’s also worth understanding where a website earns citations, which related topics it ranks for, and what information AI systems choose to reference.
If your page already ranks in Google’s top 20, improving its relevance, answer quality, and organic performance should remain a priority.
But what about queries where your website doesn’t rank? That’s where we’d look beyond the individual keyword.
- Check related-topic visibility: Does your website rank for other questions within the same topical map?
- Analyze cited sources: What specific information are lower-ranking pages contributing to AI answers?
- Find information gaps: Are competitors providing useful details, comparisons, or evidence your content lacks?
We wouldn’t recommend expanding a topical map simply to increase the number of published pages.
Our approach is to identify where a website already has meaningful visibility, where its information is incomplete, and which improvements could create additional value for users and search systems.
AI citations aren’t guaranteed. But this gives SEO teams a more informed way to prioritize content opportunities rather than chasing individual keywords.
Where Semantic SEO Comes In
We’ve discussed why looking beyond individual keyword rankings can reveal additional AI search opportunities. But how do you identify those opportunities systematically?
That’s where semantic SEO comes in.
Let’s say someone searches for “best CRM for small businesses.”
The main intent is to compare CRM products. But the decision involves several related questions.
- How much does each CRM cost per user?
- Which tools integrate with accounting software?
- How difficult is customer data migration?
- Which features does a five-person sales team need?
- How secure is customer information?
Semantic SEO helps connect these information needs through entities, attributes, and relationships, rather than treating each keyword separately.
But which questions belong on the main comparison page, and which deserve supporting content?
Tools like SemanticOS by Miraiyo can help structure this process through entity and attribute analysis, semantic field development, topical mapping, and content planning.
The goal is to identify what information matters, where it belongs, and how it connects. A well-structured topical map makes those relationships easier to visualize.
One Search Query Can Lead to an Entire Topical Map
Look at the topical map above.
One main topic connects to several related areas, including pricing, integrations, data migration, security, industry-specific needs, and product comparisons.
Each branch represents a question someone might have before choosing a CRM.
Now, imagine you’re auditing a SaaS website.
You find a detailed “best CRM” article. It compares features and pricing, but barely explains integrations. There’s no guide to migrating customer data, either.
These are content gaps that a keyword-by-keyword approach might overlook.
Published Coverage Isn’t the Same as Ranked Coverage
There’s another important distinction when evaluating your topical map.
- Published coverage tells you which topics your website has created content for.
- Ranked coverage tells you which topics your website actually ranks for in Google’s organic results.
Imagine your topical map contains 100 distinct topics. You’ve published relevant content for 70, but your website ranks in the top 20 for only 18.
Your published coverage is 70%, while your ranked coverage is just 18%. That gap deserves investigation.
Perhaps some pages don’t satisfy search intent. Others might compete with existing pages, lack sufficient detail, or face technical problems.
Rather than immediately publishing more content, investigate why your existing pages aren’t earning visibility.
But there’s another side to this. While we organize content around related questions, AI search can also explore related questions when generating answers.
That connection is worth understanding.
How Does AI Search Find Relevant Sources?
Google has explained that AI Mode uses a technique called query fan-out.
Instead of relying on a single query, AI Mode can explore related subtopics and retrieve information from multiple sources.
Think about our CRM example. Someone asks which CRM is best for a small service business. AI Mode might explore pricing, integrations, implementation difficulty, and industry-specific needs.
Notice how these questions overlap with our topical map.
A detailed integration guide could contribute useful information to an AI-generated answer, even if it doesn’t rank for the original query.
However, AI Mode and AI Overviews aren’t identical, and we can’t assume they follow the same retrieval process.
Still, query fan-out shows why looking beyond the original keyword matters.
For SEO teams, the takeaway is to analyze not just where a cited page ranks, but what specific information it contributes to the AI-generated answer.
How to Audit Your Content Using a Topical Map
Your website already has a page targeting “best CRM for small businesses.” Before publishing additional content, review your existing coverage.
| Topic | Current Coverage | Recommended Action |
|---|---|---|
| CRM comparison | Main landing page | Improve product comparisons |
| Pricing | Brief paragraph | Add detailed pricing information |
| Integrations | Limited information | Expand or create a supporting guide |
| Data migration | Missing | Evaluate a dedicated guide |
| Security | Existing documentation | Add relevant contextual links |
| Industry use cases | Two existing pages | Check for overlapping search intent |
This identifies content gaps. But an experienced SEO team shouldn’t stop there. The next step is to connect the content audit with actual search performance.
Add Ranking and AI Citation Data
For each important topic, track the representative search query, relevant URL, organic ranking position, and whether the website appears as an AI citation.
Here’s an example.
| Topic | Google Position | AI Citation | Next Action |
|---|---|---|---|
| CRM comparison | 4 | Yes | Maintain and improve |
| CRM pricing | 12 | No | Investigate ranking and content gaps |
| CRM integrations | 28 | Yes | Analyze the off-query citation |
| Data migration | Outside top 20 | No | Validate demand and search intent |
| CRM security | 8 | No | Review content usefulness and competing sources |
Now the audit becomes more effective.
A page ranking at position #4 and receiving citations may reveal what information AI search finds useful.
A page ranking at position #12 without citations deserves investigation, but citation absence alone doesn’t prove the page is poorly optimized.
A page ranking at position #28 while earning citations is particularly worth examining.
What information did the AI answer reference? Did it cite a specific comparison, integration detail, or factual explanation? Does the website rank for related queries?
These questions can help identify information gaps and optimization opportunities that an ordinary keyword report might miss.
How to Measure AI Search Visibility Beyond Rankings
Once your topical map is organized, you need a consistent way to measure progress. Below is a framework SEO teams can adapt.
1. Define Your Topical Scope
Start with a manageable set of commercially relevant topics. Group keywords that serve the same intent rather than treating every variation as a separate topic.
Assign a representative query to each topic and maintain a stable query set for reporting. Otherwise, changes in the number of topics being tracked could distort your coverage comparisons.
2. Measure Ranked Coverage
Calculate the percentage of mapped topics where your website holds at least one top-20 organic ranking.
Ranked coverage = (Topics with a top-20 ranking ÷ Total tracked topics) × 100
If your website ranks for 35 of 100 mapped topics, your ranked coverage is 35%. This is a practical measurement approach, not an official Google ranking metric.
Use Google Search Console to review queries, clicks, and impressions. For consistent position checks, supplement that data with suitable rank tracking.
3. Separate On-Query and Off-Query Citations
Don’t group all AI citations into one number. For each tracked AI answer citing your website, check whether your website ranks in the top 20 for that exact query.
- On-query citation – Your website is cited and ranks in the top 20 for the query.
- Off-query citation – Your website is cited but doesn’t rank in the top 20 for that query.
For off-query citations, check whether the website ranks elsewhere within the same topical map. Also record the cited URL separately from the URL appearing in organic results.
This matters because website-level citation analysis and page-level ranking analysis answer different questions.
4. Measure Citation Presence, Not Just Citation Counts
A raw number of citations can be misleading. Getting cited in 40 out of 100 tracked AI answers is different from getting cited in 40 out of 1,000.
Use a consistent metric.
AI citation presence rate = (Eligible AI answers citing your website ÷ Total eligible AI answers tracked) × 100
Record the platform, query, date, and cited URL. Keep Google AI Overviews, AI Mode, ChatGPT, and Gemini separate in your reporting because their interfaces, answer-generation behavior, and citation practices can differ.
5. Evaluate Changes Carefully
After improving a content cluster, review whether anything changed in
- Organic ranking positions
- Ranked topical coverage
- On-query citation presence
- Off-query citation presence
- Organic traffic and conversions
Compare similar query sets across reporting periods. Remember that AI answers can vary between runs. A citation appearing or disappearing isn’t automatically evidence that a content update worked or failed.
Where possible, compare improved topics with similar topics you haven’t changed. This won’t establish perfect causation, but it provides a more reliable basis for evaluating SEO work.
Which Content Opportunities Should You Prioritize?
Not every missing topic needs a new page. And not every page without AI citations needs rewriting.
I’d prioritize opportunities based on business relevance, existing visibility, and the information value you can provide.
| Opportunity | Recommended Approach |
|---|---|
| Important query ranking well but missing citations | Analyze AI answers and cited competing sources |
| Important query ranking in positions 11–20 | Review search intent, content quality, and ranking opportunities |
| Related query earning citations but ranking poorly | Investigate the cited information and organic performance gap |
| Relevant topic without adequate coverage | Validate intent and decide whether existing or new content is appropriate |
One opportunity deserves particular attention.
Can your website provide information that competing pages don’t?
For a CRM software company, that might include original integration documentation, implementation experience, product limitations, migration data, or real customer use cases.
Those details can make content genuinely useful. They’re also harder to replicate than another generic article summarizing the same CRM features found across dozens of websites.
What I’d Change in an SEO Strategy
I wouldn’t abandon keyword research, organic rankings, or existing SEO fundamentals. I’d add a broader measurement and decision-making layer.
- Keep tracking individual rankings, but also measure topical coverage.
- Investigate off-query citations separately.
- Prioritize information gaps over keyword gaps.
- Connect performance with business outcomes.
Google’s guidance for AI features continues to emphasize helpful, accessible content and established SEO practices. It doesn’t prescribe a special optimization trick that guarantees AI citations.
Semantic SEO isn’t a shortcut to appearing in AI search. It’s a way to make better decisions about what information a website provides, how it satisfies search intent, and how related information is organized.
Final Thoughts
The 44% statistic raises an important question about the relationship between Google rankings and AI citations.
The additional research gives us a more useful direction to investigate.
Ranking position matters for queries where your website already has visibility. But broader topical visibility may also be associated with citations for related queries where you don’t rank in the top 20.
For SEO professionals, the next step isn’t simply to publish more content around every related keyword.
It’s to measure search visibility at two levels.
- How do individual pages perform for specific queries?
- And how does the website perform across a connected subject?
Understanding both can help teams identify meaningful gaps, prioritize improvements, and evaluate AI citation opportunities more systematically.
The objective isn’t to chase citations at the expense of traditional SEO. It’s to build a content strategy that earns visibility, answers real questions, and contributes measurable value to the business.