What does the benchmark say about page design for AI citations? | Trakkr Research

It says citeable pages are explicit, structured, and evidence-dense. They tend to be long enough to resolve a topic and formatted so a model can extract answers confidently.

Methodology: Built from 1,465 AI-cited pages across 950 domains, using 28,033 citation opportunities and page-level crawl analysis.

Direct Answer

Mostly, the benchmark indicates citeable pages are explicit, structured, and evidence-dense. They average 2,289.6 words to resolve a topic and are formatted so a model can extract answers confidently.

What this means

This turns study findings into operating rules teams can use to prioritize structural elements like canonical tags and schema when deciding what to publish, refresh, or measure next.

Evidence table

Metric Value Why it matters
Pages with schema 67.8% Share of cited pages with schema markup.
Average word count 2,289.6 Average word count of cited pages.
Canonical tag rate 91.4% Share of cited pages with a canonical tag.
OG tag rate 89.2% Share of cited pages with Open Graph tags.

Frequently Asked Questions

How common is schema markup on cited pages?

The benchmark shows that 67.8% of cited pages use schema markup.

What is the average word count for a cited page?

The average word count of cited pages is 2,289.6 words.

Do cited pages typically use canonical and Open Graph tags?

Yes, the canonical tag rate is 91.4% and the Open Graph tag rate is 89.2% among cited pages.

What to do next

Related pages

Continue through the same study cluster.

Data & Sources