This is a preview of Chapter 2 from my new ebook – Strategic SEO 2025 – a PDF which is available to download for free here.
“Topicality” was addressed with surprising specificity in the trial.
Far from being an abstract concept, “topicality” was revealed to be a formal, engineered system within Google, designated as T*.
The explicit function of the T* system is to compute a document’s fundamental, query-dependent relevance.
It serves as a “base score” that answers the question: How relevant is this document to the specific terms used in this search query?
Google uses topicality signals to judge how well a page’s content matches a user’s query. This is essentially the relevance of the page’s topic and text to the search terms:
- On-Page Content: The actual words on a webpage are the foundation of topical relevance. “The most basic and in some ways the most important signal is the words on the page and where they occur,” testified Pandu Nayak (Google’s Vice President of Search) regmedia.co.uk. He emphasised that the presence of query terms in the content, whether in the title, headings, meta tags, or body text, is “actually kind of crucial” for ranking regmedia.co.uk. In short, what the document “says about itself” is central to determining its topicality. Nayak noted that signals such as term frequency and position (e.g. title vs. body) are “very important” relevance cues regmedia.co.uk.
- Anchor Text (Context from Links): Google also evaluates what other websites say about a page. Nayak testified that “another very important signal is the [hyper]links between pages,” known as anchor text, which provides “a very valuable clue in deciding what the target page is relevant to.” regmedia.co.uk In other words, if many pages link to a webpage using certain keywords, it signals the topic or context of that page. (For example, a page heavily cited with the anchor “JavaScript tutorial” is likely about JavaScript tutorials, boosting its topical relevance for that query.) Importantly, Google clarified that it does not mix user click data into its link analysis. When asked if click data influences the anchor signal, Dr. Kenneth “Ken” Lehman (a Google search quality witness) explained: “To generate the anchor signal, that’s just from links between web pages, and it doesn’t involve clicks.” regmedia.co.uk Anchors are purely derived from the web’s linking behaviour, independent of user interactions.
- User Interaction Signals: Internal evidence shows Google also monitors aggregate user behaviour to refine relevance. A Google “Three Pillars of Ranking” slide (from 2016) listed User-interactions (“what users say about the document”) as a third pillar alongside Body and Anchors. These interactions can include clicks, attention (hover/scroll), swipes, and whether users quickly return to search results. While Google has long maintained publicly that clicks are not a direct rank booster, trial documents indicate Google does use such data in a feedback loop to evaluate search quality. Indeed, as HJ Kim noted, Google historically tracked dwell time (length of time on a result before returning) as part of topicality scoring justice.gov. However, Google witnesses stressed that user data is used carefully, primarily to learn and adjust algorithms, not to blindly promote whatever gets the most clicks. (See the discussion under Authority about the pitfalls of click metrics.) Q “How does that relate to the question of user data or user interaction data? A. So the chart is a little bit complex, but what it’s illustrating is one of the problems with using click data in connection with ranking search results. It’s a very strong observation that people tend to click on lower-quality, less-authoritative content than we would like to show on our search engine. Our goal is to show — when someone issues a query, to give them information that’s relevant and from authoritative, reputable sources. People tend not to click on those so much. So if we’re guided too much by clicks, our results would be of a lower quality than we’re targeting.
The T* score is composed of three core signals, collectively referred to as the “ABC signals,” which are themselves developed and tuned by engineers.
“ABC” Signals – Anchors, Body, Clicks: Hyung-Jin “HJ” Kim (a Google search engineer) explained in a February 2025 DOJ interview (Trial Exhibit PXR0356) that Google’s “ABC signals are the key components of topicality (or a base score)”, which is Google’s determination of a document’s relevance to a query justice.gov.
- A – Anchors: This signal is derived from the anchor text of hyperlinks pointing from a source page to the target document. This confirms the enduring importance of descriptive, relevant anchor text as a powerful signal of what another page on the web believes a document is about, a direct legacy of the principles that underpinned Google’s original PageRank algorithm.
- B – Body: This is the most traditional information retrieval signal, based on the presence and prominence of the query terms within the text content of the document itself.
- C – Clicks: This signal was one of the most significant confirmations of the trial. It is derived directly from user behaviour, specifically defined in testimony as how long a user dwelt on a clicked-upon page before navigating back to the search engine results page (SERP). The inclusion of a direct user engagement metric at this foundational level of relevance scoring underscores the centrality of user feedback to Google’s core ranking logic.
Clicks vs. Quality
One revelation was Google’s caution against using click metrics as a proxy for quality.
An internal evaluation found that “a large number of clicks on a link does not necessarily mean that the page is of high quality.”regmedia.co.uk
Dr. Lehman explained a known issue: “It’s a very strong observation that people tend to click on lower-quality, less-authoritative content” disproportionately. In other words, popular clicks can sometimes go to clickbait or less trustworthy pages.
“If we were guided too much by clicks, our results would be of a lower quality than we’re targeting.”
Lehman warned (discussing an internal slide. Google’s ranking engineers, therefore, treat user click data with scepticism when it comes to authority – they use it to refine algorithms but do not simply promote pages because they’re popular.
In fact, Pandu Nayak noted that page quality tends to be “anti-correlated” with pure click-through rates in some cases – improving the quality of results in tests sometimes led to fewer clicks, as users might chase clickbait even when higher-quality info is available. This reinforces why authority signals (like PageRank and quality scores) are crucial to keep search results genuinely trustworthy.
It is clear – Google uses some types of click signals (like dwell time for Navboost/T*) to refine relevance but avoids using raw click volume as a direct measure of authority or quality, as it can be misleading (e.g., clickbait).
These three were “fundamental signals” combined into a topicality score (T★) to judge relevance justice.gov and justice.gov.
Notably, Kim said even historical user behavior – e.g. “how long a user stayed at a particular linked page before bouncing back to the SERP” – was used as a topical relevance signal in the past justice.gov.
Google’s ranking engineers hand-crafted the formulas for these signals (rather than relying purely on ML) so they could understand and adjust how each factor contributes to relevance justice.gov.
These three signals are combined in what was described as a “relatively hand-crafted way” to generate the final T* score.
The user engagement data that powers the Navboost re-ranking system also provides the foundational ‘Clicks’ signal for the T* topicality score.
The development of this system was a major engineering undertaking, described as being in a “constant state of development” from its inception until approximately five years prior to the testimony, indicating its maturity and foundational status within the ranking stack.
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