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llms.txt GeneratorWhat is the most useful way to interpret the schema data?
Mostly, interpret it as a benchmark profile rather than a magic lever. The schema data shows what cited pages tend to have in common, which helps teams design better page templates even when it does not prove strict causality.
The key numbers.
- Pages with schema
- Share of cited pages with schema markup.
- 67.8%
- Person schema lift
- Person schema over-indexes heavily on cited pages.
- 9.4x
- FAQPage lift
- FAQPage is overrepresented relative to the web average.
- 2.4x
The safest practical application is to replicate the structural profile of cited pages, such as the 67.8% of cited pages using schema, and test the effect on your own corpus.
The evidence.
| Measure | Result |
|---|---|
| Pages with schema Share of cited pages with schema markup. | 67.8% |
| Person schema lift Person schema over-indexes heavily on cited pages. | 9.4x |
| FAQPage lift FAQPage is overrepresented relative to the web average. | 2.4x |
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.
What to do with this
- Make answer pages denser, more structured, and more explicit about authorship and freshness.
- Use schema where it helps machine readability, but avoid treating markup as a substitute for strong content.
- Design pages to be extractable using concise answers, tables, lists, authors, and clearly marked evidence.
This approach turns correlation data into an operating rule that teams can use to prioritize template updates, content refreshes, and measurement frameworks.
Questions about this answer.
Cite this answer.
Source study: Anatomy of a Citation“Mostly, interpret it as a benchmark profile rather than a magic lever. The schema data shows what cited pages tend to have in common, which helps teams design better page templates even when it does not prove strict causality.”
Mack Grenfell · What is the most useful way to interpret the schema data?
The Anatomy of an AI Citation · Trakkr Research · Updated 30 March 2026