Direct Traffic & Popularity – Correlation, Not Causation via @sejournal, @TaylorDanRW

A new AI citation study sparked a familiar SEO debate: the difference between a ranking factor and a symptom of ranking success. The post Direct Traffic & Popularity – Correlation, Not Causation appeared first on Search Engine Journal.

Direct Traffic & Popularity – Correlation, Not Causation via @sejournal, @TaylorDanRW

Last week, Cyrus Shepard published an AI citation ranking factors study, and it created a lot of noise on X, LinkedIn, and a number of private WhatsApp groups I’m in. Not only the distinction between what is a factor, and what is a correlation, especially given a lot of studies in SEO and AI are multifarious and have high levels of imponderable complexity. To be clear, this isn’t a criticism of Cyrus’s work; the study is excellent, and the correlation/causation caveat is one he makes himself explicitly.

This led me to think about the parallels with other ranking factor studies done previously, which have implied direct traffic is a considerable traditional SEO ranking factor. At the time, these studies received a lot of negative feedback, and this was again discussed by many online after the documentation in Google’s DOJ trial revealed a “popularity” signal.

It makes sense for direct traffic to be a component of how popularity is measured through Chrome. Google uses Chrome data to find new websites. It also judges a page’s “quality” based on how users interact with it after clicking, but the atomic levels of how this is done, and how much weight the variables here carry, are not public knowledge.

Direct Traffic x Popularity Correlation

Direct traffic is widely considered a symptom of good performance, not a primary driver of search rankings.

Treating direct traffic as a ranking factor leads to a misinformation loop, which encourages superficial, low-effort tactics, such as purchasing bot traffic, in a misguided attempt to boost popularity, as it’s very possible to have high levels of direct traffic and poor SEO performance.

A wider view suggests that high direct traffic is typically an indicator of a strong brand, correlating with genuine ranking factors like numerous brand searches, high-quality backlinks, and strong social engagement.

These elements are the true causes of high ranking; the direct traffic merely serves as a quantifiable measure of the brand’s overall health and success, an “all ships rise in high tides” effect.

Spikes in direct traffic, don’t correlate with Organic Search traffic. (Image from author, May 2026)

If Chrome data were a direct factor, a sudden spike in browser activity on a specific URL would immediately push it up the SERPs, and this would be a gameable exploit.

This would also be something Google would pick up as it looks to stamp out obvious manipulations of search ranking, and this would have happened many years ago.

Other Insights From The 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 looks at historical clickstream data and user behavior on search results to identify which pages are most relevant for specific queries, effectively acting as a memory of what users have found helpful.

While NavBoost focuses on traditional organic results, Glue extends those same user interaction principles to all other SERP features: knowledge panels, video carousels, image packs, and featured snippets.

They allow Google to gauge a site’s authority based on how users interact with it in the search ecosystem, independent of the user’s traffic source.

→ Read more: What The Google 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 such as autocompletes and bookmarks.

It functions as a correlation to high rankings because it naturally aligns with the various signals that make a page rank.

Google may avoid using Chrome data directly as a ranking factor, choosing instead to use it as a dataset to train or validate its AI models. This we don’t know, and we likely won’t be able to prove or disprove through research.

Thank you to Ryan Jones, Mark Williams-Cook, Chris Green, Gerry White, Kristine Schachinger, Charlie Whitworth, Emina Demiri Watson, (and anyone else I’ve missed) for the fun weekend discussions on this topic.

More Resources:

The Facts About Google Click Signals, Rankings, And SEO Google’s Quality Rankings May Rely On These Content Signals Google AI Overview Citations From Top-Ranking Pages Drop Sharply

Featured Image: PerfectWave/Shutterstock