Cited but Not Mentioned: Why AI Engines Use Your Page and Recommend Someone Else

An answer engine can read your page, use it, and still recommend a competitor. It is the most common shape of AI visibility failure we see, and it is invisible to any tool that reports a single "visibility" number — because on that number, being used as a source and being named in the answer look identical.

Here is what the split looks like on a real domain. Across 446 stored answers from five engines, the site was cited as a source in 68 of them and named in the answer text in 38. On one engine the gap was total: 22 answers retrieved the site and not one of them mentioned the brand.

Cited and named are different events

Two things can happen when an engine answers a question about your category:

• Cited — the engine retrieved one of your URLs while composing the answer. Your page was part of the evidence.
• Named — your brand appears in the text a person actually reads.

Both can happen, either can happen alone, and each alone means something specific:

• Named but not cited. The model knows you from training data but had no current page to point at. Usually the cheapest to fix: publish the page that supports the claim.
• Cited but not named. Your page was read as background material while a different source supplied the recommendation. Nothing is wrong with your crawlability, your schema, or your page speed. The problem is that the engine did not find you in the part of the evidence that decides who to recommend.

Teams routinely spend weeks on the first fix when they have the second problem.

Why it happens: you are one source out of many

An AI answer is a synthesis, not a redirect. In the same dataset, when the engine cited that domain it consulted an average of 7.7 other sources alongside it — so the site was roughly one-eighth of the evidence behind the answer.

Now consider what those other sources say. In this case the most-retrieved ones were competitor sites and category publishers, and each of them names a competitor. The engine reads your page for definitions and mechanics, reads seven other pages for opinions about who is good, and composes an answer from both. You supplied the facts; somebody else supplied the recommendation.

The sharpest example in the dataset: one engine retrieved the site's own comparison article — a page written specifically to win that query — and still answered with a competitor. The page was read. It just was not corroborated anywhere else.

How to tell which problem you have

You need three things per prompt, per engine:

1. Was your brand named in the answer text?
2. Was one of your URLs retrieved as a source?
3. Which other domains were retrieved for the same answer?

If your tool cannot answer the third question, it cannot tell you why you lost. That list of other domains is your real competitive set, and it is usually not the list of competitors you would have written down: it tends to be review sites, category publishers, and comparison pages you have never contributed to.

What actually fixes it

Being cited but not named is a corroboration problem, so the work is off your own site more than on it.

• Get named on the pages the engine already reads. Take the list of retrieved domains, sort by how often each was pulled in, and work down it. A mention on a source the engine retrieves for eleven of your prompts is worth more than a new page of your own.
• Claim and complete third-party listings. Review and directory sites are retrieved disproportionately for "best X" and "X alternatives" queries, and they are one of the few places you can add a factual entry directly.
• Publish the comparison you want quoted. If every retrieved source frames the category around competitors, there is no version of the comparison that includes you for the engine to find. Write it, with specifics rather than claims about rivals you cannot verify.
• Make the recommendation extractable. Engines lift self-contained sentences. "AEOTrack tracks five answer engines and separates naming from citation" survives extraction; the same fact spread over a paragraph of benefit language does not.

What does not fix it

If you are already being cited, the engine can reach your site and parse it. More schema markup, another rewrite of the meta description, and a faster page will not change who gets recommended. Neither will publishing a fifth page on the same topic — you will simply be one-eighth of the evidence on more prompts.

Measuring the fix

Track the two numbers separately and watch the gap close, not the total rise. A month where citations stay flat and mentions climb is exactly the result you want, and a tool reporting one blended figure will show it as barely any movement at all.

Expect weeks rather than days: the third-party page has to be updated, re-crawled, and then retrieved for the right prompt before the answer can change. And check per engine — in this dataset the gap was total on one engine while another named the brand in every answer that cited it.