Our own AI-visibility score started at 0/100. What 2,150 cited URLs taught us about getting recommended by ChatGPT

Agreed on the distinction, and we do split it — cited, mentioned and not-cited are three states in the product rather than one. But your second suggestion is the more interesting one, and I went and ran it, because I had not looked at the panel that way. Segmenting by repeated mentions instead of total volume, this week's run across the 40 buyer questions: 790 distinct domains cited. 727 of them, 92%, appear in exactly one question. Only 21 appear in three or more. That repeat set is almost entirely platforms and publishers, not vendor pages: YouTube in 30 of the 40 questions, Reddit 28, TechRadar 10, Forbes 7, CNBC 6, PCMag 5. So your method surfaces something real, and it points somewhere I did not expect. The pages that earn repeated mentions are not the ones making claims about a product; they are the substrate the engines keep returning to. Vendor pages live almost entirely in that 92% tail, chosen once for one question and then not again. Which suggests the claims-and-proof-points work, where it happens, happens per question rather than accumulating into a durable position. Two things I should be straight about rather than dress up. Counting was already deduped: a domain counts once per question per engine, so four engines naming one page on one question is four, never four for one page. Volume was never raw volume. But that is exactly why your reframing earns its keep. Breadth across questions and breadth across engines are different axes, and I had been reading the first as if it implied the second. The part this instrument cannot answer is which claims and proof points do the work. We store cited URLs, not rendered page content, so I can tell you a page was chosen and for which question shape, not what about it was persuasive. That needs a content analysis on top, and I would rather name the gap than infer it from URLs. On cited versus recommended, the sharpest version I have is our own domain: on branded questions we are named 4 times out of 4; on the 15 where we compete on merit, zero. Same product, same pages. Being retrievable and being chosen really are two different measurements.

Honest answer: citation volume is the stronger signal for us so far, and I would not claim qualified traffic yet. Two reasons, both measurement rather than marketing. 1. Most assistants open links with no referrer, so the visit lands in analytics as Direct. We keep two buckets apart: confirmed (a referrer, or an assistant user-agent like ChatGPT-User fetching the page on a user's behalf) and inferred (Direct sessions landing cold on a deep /vs or /alternatives URL, which typed-in Direct almost never does). The inferred bucket runs roughly 2 to 3x the confirmed one. That gap is the honest size of the attribution hole. 2. On our own domain the numbers are small enough to say out loud: a handful of AI-referred visits and no attributed revenue. The comparison pages that got cited in the dataset were third-party ones, and we do not have their analytics, which is exactly the publisher-side number I was asking for. What I can say: the citations are weekly and reproducible, the traffic is not yet. We started publishing the source side in the open today (promvia.app/ai-source-index, 40 fixed buyer questions across seven engines every Monday), and the first week already showed the engines leaning on YouTube and Reddit far more than on any directory for consumer questions. If your /vs pages show AI referrals out of proportion to organic, I would genuinely like to see the numbers.