Comparison Pages
The go-to advice for winning AI search is to write your own comparison page. But being cited by AI is not the same as being recommended: a model can quote your page as a source and still pick a rival. Does the page actually close that gap? This is the causal answer.
Cited a lot, chosen rarely
Start with the problem a comparison page is meant to fix. These brands are quoted as a source but left out of AI’s top picks. The less visible a brand, the more its citations leak: cited for evidence, skipped for the recommendation.
Do comparison pages work?
So you publish the page. Does it move anything? A staggered difference-in-differences study around the week each owned page is first cited: the odds of being recommended before versus after, against brands not yet cited.
Average treatment effect on the odds of being recommended, in percentage points, by week relative to the first citation. Flat and near zero before; a clear step up after, holding for two months.
How we know it's the page
A jump right after citation could be coincidence, so the data carries its own control. The same study, split by engine type: engines that retrieve the live page versus engines answering from memory. If the page is doing the work, only the engines that can read it should move. That is exactly what happens.
The lift appears only in engines that can read the page. Engines answering from memory show nothing, which is what you would expect if the page itself is doing the work. Bars are the difference-in-differences estimate; whiskers are the 95% brand-clustered confidence interval.
Your own page sells your rivals
Here is where brands hand the gains back. The same comparison page that helps you also names your competitors, and AI reads those names as a vetted list of who else to recommend. Share of each brand’s cited pages that give AI at least one rival to suggest.
A weekly recommendation panel for 180 brands, built from 1.1M AI answers, with a staggered difference-in-differences and a Callaway-Sant’Anna event study around the first citation of an owned page. Controls are brands not yet cited; windows run eight weeks either side; confidence intervals are brand-clustered bootstraps.
- Quasi-experimental, not a randomized trial.
- Publish-date anchoring could not be completed (archival publish dates were unavailable), so we date the effect to first citation, not first publication.
- A mild pre-trend exists in grounded engines (joint pre-trend test p=0.05), consistent with the citation timestamp lagging true onset.
Common questions
Is being cited by AI the same as being recommended?
No. A model can quote your page as a source and still recommend a competitor as its top pick. In this study, owned pages are a median 4.6% of what AI cites about a brand, and nearly a third of cited pages name a rival. Citation is evidence; recommendation is the verdict.
Why does AI cite my page but recommend a competitor?
Comparison and "best of" pages are the pages AI reaches for, and those pages name rivals by design. So the page you wrote to win becomes the evidence the model uses to list everyone else. The less visible a brand already is, the more its citations leak into a competitor recommendation.
Do comparison pages actually help you get recommended?
Yes, modestly. Around the week an owned page is first cited, a brand’s odds of being recommended rise by about 2.7 points overall, and 5.5 points for challenger brands with room to grow. The lift is real but concentrated, not a step change.
Which AI engines does the page lift work in?
Only the engines that can read the page. Web-grounded engines (ChatGPT, Perplexity, Gemini, Google AI Overviews) show a clear lift of about 5 points; engines answering from memory (Claude, Meta, Deepseek, Grok) show essentially nothing, which is what you would expect if the page is doing the work.