Navboost
Also called: nav boost, navboost algorithm, google navboost
Navboost is a Google ranking system, confirmed under oath at the 2023 DOJ antitrust trial, that re-ranks search results using aggregated user clicks. It memorizes click patterns per query over a rolling window of roughly 13 months and uses them to promote the results people actually engage with.
What the DOJ trial revealed
Google VP Pandu Nayak testified that Navboost is “one of the important signals” and dates back to at least 2005. It behaves less like machine learning and more like a giant lookup table: for a given query it records how often users (split into “slices” by location and device) click each result, then uses that memory to cull a large candidate set down to a much smaller one before other systems finish the ranking. Because it runs on memorized history, Navboost cannot help a page that has no click data yet.
Not every click counts the same. A “good click” is one where the user stays; a “bad click” is a pogo-stick, where they bounce straight back to the results. The strongest pattern is the “last longest click,” the result someone settles on and reads. Google normalizes (“squashes”) these counts so viral spikes and click fraud cannot dominate. The window is roughly 13 months (18 before 2017), long enough to smooth seasonality and resist quick manipulation. A related system, Glue, extends the same idea to hovers, scrolls, and swipes to place SERP features, with an Instant Glue variant reacting within about 24 hours.
How it affects your traffic
Navboost means rankings are partly earned after the click, not only before it. If searchers pick your result and stay, you gain ground; if they pogo-stick back to Google, you slide. You cannot fake this with CTR bots, since Google squashes and filters manipulation, so the real lever is matching search intent and satisfying it fast. That is a positioning and content-architecture problem, which is where SEO consulting earns its keep: we read the SERP behind each query, fix the intent mismatch, and shape pages to win the last-longest-click.
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