This is a preview of Chapter 5 from my new ebook – Strategic SEO 2025 – a PDF which is available to download for free here.
Perhaps the most impactful revelation from the trial was the detailed exposition of the Navboost system.
This system provides the crucial ‘C’ (Clicks) signal for the T* score.
For years, the search engine optimisation (SEO) community has debated the role of user clicks in ranking, with Google’s public statements often being evasive or dismissive.
The trial testimony, particularly from Google VP Pandu Nayak, ended this debate.
Navboost was confirmed to be “one of the important signals” that Google uses to refine and prioritise search results based on a massive, historical repository of user interaction data.
The system operates on a vast time horizon, storing and analysing 13 months of user interaction data to inform its signals.
This extended timeframe allows it to look beyond short-term fluctuations and identify persistent, long-term patterns of user satisfaction, effectively using the collective wisdom of billions of past searches to guide future rankings.
Navboost’s analysis is highly nuanced, moving beyond a simple click count to classify different types of user interactions.
Leaked documents and testimony point to several key click metrics:
- Good Clicks vs. Bad Clicks: The system distinguishes between positive and negative interactions. A “bad click” is probably a “pogo-stick” event, where a user clicks a result and then immediately returns to the SERP, signalling dissatisfaction. A “good click,” conversely, indicates that the user’s need was met.
- Last Longest Click: This metric appears to be of particular importance. It identifies the final result a user clicks on in a search session and dwells on for a significant period. This interaction is interpreted as the ultimate signal of a successfully completed search task, making the page that received the “last longest click” a highly valuable result for that query context.
To provide contextually relevant results, Navboost employs several sub-systems:
- Slicing: The system segments, or “slices,” its vast repository of click data by critical contextual factors, most notably the user’s geographic location and device type (e.g., mobile or desktop). This allows Navboost to prioritise results that have performed well for users in a similar situation, for example, boosting a local business’s website for mobile users in a specific city.
- Glue: This is a related, more real-time system that works alongside Navboost. The “Glue” system specifically monitors user interactions with non-traditional SERP features like knowledge panels, image carousels, and featured snippets. By analysing signals such as hovers and scrolls on these elements, Glue helps Google determine which features to display and how to rank them, especially for fresh or trending queries where historical click data may be sparse.
The primary function of Navboost within the overall ranking pipeline is to act as a powerful, user-behaviour-driven filter.
According to Pandu Nayak’s testimony, after an initial retrieval stage that identifies a large pool of potentially relevant documents, Navboost is used to dramatically reduce this set from tens of thousands down to a few hundred.
This much smaller, higher-quality set of documents is then passed on to more computationally expensive and nuanced machine learning systems for final ranking.
A key limitation acknowledged in the testimony is that Navboost can only influence the ranking of documents that have already accumulated click data; it cannot help rank brand-new pages or those in niches with very low search volume.
“Authoritative, Reliable” Results Priority: Google’s witnesses underscored that the search engine deliberately prioritises authoritative sources in rankings.
Nayak explained that Google’s “page quality signals” are “tremendously important” because the goal is to “surface authoritative, reliable search results” for users regmedia.co.uk.
In the same vein, Dr. Lehman testified that “our goal is to show – when someone issues a query – to give them information that’s relevant and from authoritative, reputable sources.”.
This philosophy was echoed throughout the trial: Google wants trustworthy content (e.g. official sites, established experts, high-quality publishers) to rank at the top, rather than sketchy or unverified pages, even if the latter are more crudely optimised for a keyword.
Key Takeaways
In essence, these three Google systems work in concert to deliver high-quality results: T establishes relevance, Q assesses trust, and Navboost refines the results based on user satisfaction.
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