Not sure where to start? Take a guided tour.
AI Site Grader
AI Query Scanner
llms.txt GeneratorBenchmark profile of AI-cited pages
The benchmark pattern indicates that AI systems preferentially cite pages demonstrating high structural integrity and content depth. Specifically, cited pages exhibit near universal canonicalization at 91.4 percent and strong social metadata presence at 89.2 percent. Content depth is a defining characteristic, with 78.4 percent of pages exceeding 1,000 words and an average word count of 2,289.6 words. Furthermore, 67.8 percent of these pages utilize schema markup, reinforcing the trend that structured, metadata-complete, and long-form documents dominate AI citations.
Benchmark profile of AI-cited pages from the study The Anatomy of an AI Citation.
The key numbers.
- Pages with schema
- Share of cited pages with schema markup.
- 67.8%
- Most-cited pages with schema
- Schema prevalence among the highest-cited subset.
- 80%
- Average word count
- Average word count of cited pages.
- 2,289.6
- Pages above 1,000 words
- Most cited pages are long-form.
- 78.4%
The ranked view.
- 191.4%
Pages with canonical tags
Canonicalization is nearly universal across cited pages.
- 289.2%
Pages with Open Graph tags
Social metadata is also highly prevalent.
- 367.8%
Pages with schema
Structured data is common in the cited-page profile.
- 478.4%
Pages above 1,000 words
Long-form depth is the norm.
- 52,289.6
Average word count
Typical cited pages are dense and fully built out.
What changed
Metadata and Canonicalization Prevalence
Canonicalization is nearly universal across cited pages at 91.4 percent. Social metadata is also highly prevalent, with Open Graph tags present on 89.2 percent of cited pages.
Content Depth and Word Count Metrics
Long-form depth is the norm for AI citations. Pages above 1,000 words account for 78.4 percent of the dataset, and typical cited pages are dense and fully built out with an average word count of 2,289.6.
Structured Data Adoption
Structured data is common in the cited-page profile, with schema markup present on 67.8 percent of the analyzed pages.
| Measure | Result |
|---|---|
| Pages with schema Share of cited pages with schema markup. | 67.8% |
| Average word count Average word count of cited pages. | 2,289.6 |
| Pages above 1,000 words Most cited pages are long-form. | 78.4% |
| Canonical tag rate Share of cited pages with a canonical tag. | 91.4% |
| OG tag rate Share of cited pages with Open Graph tags. | 89.2% |
Population and method
Built from 1,465 AI-cited pages across 950 domains, using 28,033 citation opportunities and page-level crawl analysis.
Where the evidence stops
Most findings are correlational. Overrepresented traits are not the same as proven causal lifts.
Some subgroups, especially FAQ Schema + FAQ Content, are relatively small and should be read carefully.
The study looks at cited pages rather than all uncited pages in the open web, so it is best used as a benchmark profile.
Cite this tracker.
Source study: Anatomy of a Citation“The benchmark pattern indicates that AI systems preferentially cite pages demonstrating high structural integrity and content depth. Specifically, cited pages exhibit near universal canonicalization at 91.4 percent and strong social metadata presence at 89.2 percent. Content depth is a defining characteristic, with 78.4 percent of pages exceeding 1,000 words and an average word count of 2,289.6 words. Furthermore, 67.8 percent of these pages utilize schema markup, reinforcing the trend that structured, metadata-complete, and long-form documents dominate AI citations.”
Mack Grenfell · Benchmark profile of AI-cited pages
The Anatomy of an AI Citation · Trakkr Research · Updated 30 March 2026