Last week, Cyrus Shepard published a AI Citation Ranking Factors Studyand this has created a lot of noise on X, LinkedIn and a number of private WhatsApp groups that I am a part of. Not just the distinction between what is a factor and what is a correlation, especially since many studies in SEO and AI are multiple and have high levels of imponderable complexity. To be clear, this is not a criticism of Cyrus’ work; the study is excellent and he himself explicitly states the caveat about correlation/causation.
This got me thinking about the parallels with other studies on ranking factors previously carried outwhich implies that direct traffic is a huge traditional SEO ranking factor. At the time, these studies received a lot of negative feedback, and it was discussed again by many people online after documentation in Google’s DOJ test revealed a “popularity” signal.
It makes sense that direct traffic is a part of how popularity is measured through Chrome. Google uses Chrome data to find new websites. It also judges the “quality” of a page based on how users interact with it after clicking, but the atomic levels of how this is done and the weight of the variables here are not common knowledge.
Direct traffic x popularity correlation
Direct traffic is widely considered a symptom of good performance and not the main driver of search rankings.
Treating direct traffic as a ranking factor leads to a misinformation loop, which encourages superficial and effortless tactics, such as buying bot traffic, in a misguided attempt to increase popularity, as it is very possible to have high levels of direct traffic and poor SEO performance.
A broader view suggests that high direct traffic is generally an indicator of a strong brand, correlating with real ranking factors such as lots of branded searches, high-quality backlinks, and strong social engagement.
These elements are the real causes of high rankings; direct traffic simply serves as a quantifiable measure of overall brand health and success, an “all ships rise at high tide” effect.
If Chrome data was a direct factora sudden spike in browser activity on a specific URL would immediately cause it to rise in the SERPs, and that would be a playable exploit.
This would also be something that Google would take up in an effort to eradicate obvious search ranking manipulation, and that would have happened many years ago.
Other information from DOJ files
NavBoost and Glue are specialized systems within Google’s infrastructure that focus on user interaction signals rather than the raw volume of direct traffic.
NavBoost examines historical clickstream and user behavior data in search results to identify the most relevant pages for specific queries, acting as a reminder of what users found useful.
While NavBoost focuses on traditional organic results, Glue extends these same user interaction principles to all other SERP features: knowledge panels, video carousels, image packs, and featured snippets.
They allow Google to assess a site’s authority based on how users interact with it in the search ecosystem, regardless of the user’s traffic source.
→ Read more: What Google’s Antitrust Verdict Could Mean for the Future of SEO
So what is Popularity?
Based on what we know from various official (and unofficial) sources, research, and the general SEO hive mind, we can define popularity as a sign of brand strength characterized by user behaviors like autocompletes and bookmarks.
It works as a correlation to high rankings because it naturally aligns with the different signals that determine a page’s ranking.
Google may avoid using Chrome data directly as a ranking factor, instead choosing to use it as a dataset to train or validate its AI models. We don’t know and we probably won’t be able to prove or disprove it through research.
Thanks to Ryan Jones, Mark Williams-Cook, Chris Green, Gerry White, Kristine Schachinger, Charlie Whitworth, Emina Demiri Watson (and everyone I missed) for fun weekend discussions on this topic.
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Featured Image: PerfectWave/Shutterstock
