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Twiddlers are C++ code objects used in Google’s ranking algorithms that help Google re-order search results. They are used in a Google system called Superroot which is Google’s ranking framework. I came across this 2017 Google document on Twiddlers upon reading Mario Fischer’s excellent breakdown of what we can learn about how ranking works based […]

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 […]

This is part 2 of a series of posts I am writing to discover more about what we can learn from the information in the recently discovered Google documentation on API references. Yesterday we started to learn more about the files that were found that possibly discuss important factors in Google’s ranking systems. We learned […]

Well this has been an interesting week. Rand Fishkin published a fascinating article about a set of documents that was shared with him. These documents contain the documentation for making API calls to Google’s Cloud Content Warehouse. There is speculation, for good reason, that this documentation can help us learn a significant amount about Google's […]