Navboost, an essential part of Google’s ranking algorithm, analyzes user interactions—such as clicks, hovers, scrolls, and swipes—to refine and prioritize search results. SEOs must understand how Navboost affects ranking, as it tracks critical user signals to decide which pages are most relevant and helpful. Whether users linger on a page, return to search, or quickly find what they need, these behaviors influence how Google ranks content.
Part 1: What is this “leaked” Google documentation?
Part 2: What are attributes?
Navboost's History and Its Impact on SEO Rankings
Navboost has been a core part of Google's systems since 2005. It stores 13 months of data on what people click on and engage with from the Google search results. Prior to 2017 Navboost stored 18 months of data.
How Navboost Works
Navboost collects and analyzes a wide range of user interaction signals, including clicks, hovers, scrolls, and swipes. . This comprehensive data helps Google rank the most engaging and relevant content.
I first heard about Navboost while reading the Pandu Nayak testimony in the DOJ vs Google case. If you have not yet read this testimony, I encourage you to put aside a few hours to dig in!
The Nayak testimony starts with a discussion about user data. Did you know that for every search you perform, the actions you take on Google are monitored and anonymously stored?
Since 2005, Navboost which stores data about every single search that is performed.
What did the user click on after searching that query? Did they click on a specific website? A sitelink? A search feature? Did they click on a site and return to the search results to end up being satisfied by another? Did they swipe through a carousel? Hover over a particular SERP feature? Or perhaps did they engage with the first result and not return to search?
It’s not hard to imagine that this type of information could be used to help determine which content people are finding helpful.
An internal Google email from 2019 shows that the Navboost system was powerful.
Navboost looks at much more than just clicks. It uses a number of things that Google calls user interaction data.
Engagement signals: Clicks, hovers, scrolls and more
Look at these two slides from a Google presentation during the DOJ vs Google trial called, Life of a Click. I’ve marked in red boxes the parts that help us understand more about which user interactions are used by Google and why. These are referring to user interactions from within the Google Search experience - not on websites themselves. In a moment, we’ll talk about whether Google is using data from Chrome. For now though, these user engagements are referring to actions that users are taking on Google’s search results pages.
In another presentation called "Q4 Search all Hands" from 2016, Google shares how the actions of previous searchers help Google perform better for future searches.
Google learns from the actions of users.
Navboost Components: How Glue and Slices Affect SEO and Google Rankings
There are other systems mentioned in the DOJ vs Google trial that are a part of Navboost as well.
Glue is a real-time system that considers more user data such as hovers, scrolls and swipes to help the system respond to real time, fresh queries. When there is a newly changing event in the world, it is the Glue component of Navboost that helps Google adapt its algorithms to understand what content to rank.
Slices take into account certain characteristics of a search query such as the device type or location.
Navboost attributes that can be used in Google's search algorithms
The API docs that were discovered this year tell us a lot about the attributes that can be associated with Navboost. What I am most interested in are the attributes that have “Navboost Craps” in the name.
QualityNavboostCrapsCrapsClicksSignals
These attributes store information about clicks and impressions. There are a number of things that can be stored and used by a module called QualityNavboostCrapsCrapsData.
Here’s the documentation for this module which is used to store data related to Navboost if you want to dig in for yourself.
We learned above that every query searched on Google is stored by Navboost. There’s an attribute for that:
Several of the variables used by the Navboost module tell us about clicks. The system stores impressions, clicks, goodClicks, badClicks and more. I really would like to know what unicornClicks are.
Navboost puts all of this information together and learns from it. A website that has a high number of lastLongestClicks is more likely to be one that is consistently providing the answer users are looking for. While badClicks aren’t defined in the document, it’s not hard to imagine what they are. I expect they could look at things like whether people consistently return to the search results after clicking on a site and find another site that satisfies their search. A "badClick" is likely a click that didn't satisfy the user. We want to aim to have fewer of those!
I’d encourage you to spend time with Cyrus Shepard’s Moz article which looks at Google patents related to clicks: 3 Vital Click-Based Signals for SEO: First, Long, & Last.
I’d also highly recommend In the Plex by Steven Levy as it talks about long clicks and short clicks. Google has been working for many years now to use this information in algorithms designed to improve its ability to return results that are likely to be helpful.
Does NavBoost use information from Chrome?
There is some debate on whether Google’s systems use information from user interaction in Chrome. It’s certainly possible, as Google’s privacy policy tells us they monitor quite a few things that we do, including how we interact with content, even looking at things like whether we hovered our mouse over an ad or if you interact with a page on which an ad is served.
Look at all of these things that Google collects about us.
It would make sense to me that Google uses these signals to determine what people find helpful. Google knows, via Chrome, which sites people are making purchases on, which content people are sharing, and more. It’s not hard to imagine that a system could learn which of those pieces of information to use in determining whether pages are likely to be helpful and useful. What would be a better indication of the helpfulness of a recipe page - that it has links pointing to it? Or that people tend to keep the page open, hovering over the recipe section while they make the recipe, sharing it with a friend, and coming back to it repeatedly?
Here is more information on whether or not Google uses information from Chrome to measure user engagement:
SEO Focused strategies for using this understanding of Navboost
Understanding more about the Navboost system helps us to see just how important it is to focus on user experience. As we create content for the web, we need to be striving to be a result that people will often click on, and then go on to find helpful.
To improve SEO performance by understanding Navboost, focus on these actionable steps:
- Improve User Engagement: Create content that engages users from the first click. Optimize for long clicks and reduce bounce rates to ensure users stay on your page.
- Improve usability: Users like fast pages that are easy to navigate and read.
- Focus on dynamic and interesting content: Keep your content fresh and relevant, especially for time-sensitive queries. Navboost’s real-time adjustments mean SEOs must regularly update content to stay relevant in evolving searches.
- Most importantly, Optimize for searchers rather than search engines!
Remember Google’s helpful content documentation? These questions are not a list of things that Google’s algorithms specifically reward but rather, the types of things that people tend to find helpful.
A few of the questions include:
- Does the content provide original information, reporting, research, or analysis?
- Does the content provide insightful analysis or interesting information that is beyond the obvious?
- Is this the sort of page you'd want to bookmark, share with a friend, or recommend?
- Does the content provide substantial value when compared to other pages in search results?
- If someone researched the site producing the content, would they come away with an impression that it is well-trusted or widely-recognized as an authority on its topic?
- Is this content written or reviewed by an expert or enthusiast who demonstrably knows the topic well?
These are the types of things that people like.
SEO in the age of Navboost requires a shift in focus - optimizing not just for keywords but for user satisfaction. SEOs need to create content that engages users through every click, hover, and scroll, ensuring their websites meet Google’s changing ranking signals.
There's much more on this in my new book - SEO in the Gemini Era: The Story of How AI Changed Google Search.
Here are my of my thoughts on Navboost
This is part 3 of my series working to understand more about the attributes in the recently discovered Google API files. Here's the first two posts of this series if you haven't read them yet:
Part 1: What is this “leaked” Google documentation?
Part 2: What are attributes?
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