The study tested assumptions around domain authority, recency, structured markup, and new formats like LLMs.txt. The results point to a set of consistent patterns that influence whether a page appears in an AI response. Many common claims did not hold up under the data.
The strongest signal across the dataset is the number of referring domains. Sites with more than 32,000 referring domains are more than three times as likely to be cited compared with those that have only a few hundred. Once a domain reaches that threshold, citation growth rises sharply. This trend aligns with Domain Trust performance. Domains above DT 90 earn nearly four times the citations of those below DT 43. Page Trust also matters. Pages scoring above 28 average more than eight citations, which matches the broader pattern that ChatGPT responds to signals of authority spread across a domain.
Traffic plays a significant role but only at higher levels. Domains with fewer than 190,000 monthly visitors cluster in the same citation range. A clearer lift starts when traffic passes that point. Sites with more than ten million monthly visitors average roughly eight citations. The homepage appears to be a central factor. Domains with about eight thousand organic visitors to their homepages are about twice as likely to be cited as those with only a few hundred. Rankings show a similar pattern. Pages that average positions between one and forty five receive about five citations. Pages ranked between sixty four and seventy five average about three.
Content depth and structure contribute meaningfully. Long form articles outperform shorter ones. Pages above two thousand nine hundred words average more than five citations, while those under eight hundred words average just over three. The effect is even stronger for smaller sites where length influences citations by about sixty five percent more than it does for major domains. Pages rich in statistics show stronger results. Articles with more than nineteen data points average more than five citations. Pages with expert input average more than four citations compared with roughly two for those without. Clear structure also helps. Pages with sections between one hundred twenty and one hundred eighty words gain about seventy percent more citations than those with very short sections.
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The study also examined formats such as FAQ sections and question based titles. On the surface, pages with FAQ sections or question styled headings seem to underperform. But the model’s interpretation shows that missing these sections can be a negative signal. Their impact improves when combined with strong authority and depth. They act as supporting elements rather than primary drivers.
Social presence emerged as one of the clearest contributors. Domains with millions of brand mentions on Quora and Reddit perform about four times better than those with very few. Even smaller sites can use these platforms to build trust signals if they participate in discussions and generate genuine mentions. Review sites show a similar pattern. Domains present on platforms such as Trustpilot, G2, Capterra, Sitejabber, and Yelp average between four and six citations. Those absent average less than two.
Technical performance shows a consistent relationship. Fast loading pages with an FCP under zero point four seconds average almost seven citations, while slower sites fall to about two. A similar pattern appears in Speed Index results. INP scores behave differently though. Pages with moderate INP, around zero point eight to one point zero, perform best. Extremely fast INP scores tend to appear on simpler pages that attract fewer citations overall.
The study found little benefit from LLMs.txt files. They showed no meaningful impact on citation likelihood and even reduced predictive accuracy during testing. FAQ schema markup also showed minimal influence. Pages without it averaged slightly more citations than those using it, which suggests that LLMs respond more strongly to logical structure in the content itself.
All in all, the results point to a hierarchy that favors authority, depth, structure, technical quality, and visible engagement across platforms. Smaller domains can compete when they produce thorough content, maintain clear structure, update consistently, and build authentic presence on discussion and review sites. Large domains benefit most from their existing trust signals but still gain from fast, well maintained pages.
The data shows that AI models reward the same fundamentals that shape strong websites more broadly.
Notes: This post was drafted with the assistance of AI tools and reviewed, edited, and published by humans.
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by Asim BN via Digital Information World
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