First, neither has the Google Search algorithm been leaked nor do SEO professionals suddenly have all the solutions. However, the leak of such a massive amount of Google documents is significant as it provides an unprecedented look into the internal workings of Google.
The most crucial revelation from 2,500 documents is that the search engine giant may have misled people about how it evaluates and ranks content for its search engine.
We know nearly nothing about Google’s content ranking processes. Every website relies on search traffic for survival. Many will go to great lengths to surpass competitors and reach the top of the SERPs. The higher the ranking, the better the visits, translating to more revenue. As a result, website owners follow every word Google publishes.
Over time, Google representatives have denied that user clicks affect website rankings. Testimony from the US Department of Justice’s antitrust suit unveiled a ranking factor called Navboost, which uses searchers’ clicks to rank content in search results.
According to Rand Fishkin, a veteran of the search engine optimization (SEO) industry, the meta takeaway is that more of Google’s public statements about the data they collect and the method their search engines use to work have evidence against them.
The leak became public after SEO experts Fishkin and Mike King published some of the documents’ contents earlier this week, along with their analyses. The leaked API documents contain repositories with information about and definitions of data Google collects, some of which may inform web page rankings. Initially, Google dodged questions about the documents’ authenticity before confirming their.
Google spokesperson Davis Thompson cautioned against making inaccurate assumptions about Search using outdated, incomplete, and out-of-context information. He said they have shared abundant information about how Search works and the factors that Google weighs while securing the integrity of the results from manipulation.
The documents don’t specify how different attributes are weighted. It’s possible that some attributes — like an identifier for “small personal sites” or a demotion for product reviews — were used at one point but have since been phased out. They may have never been used for ranking sites at all.
King said that they do not know how the named factors are being used and the only thing they know is that they have different descriptions.
The idea that the world’s largest search platform doesn’t base rankings on user engagement seems absurd. Yet, repeated denials, carefully worded company responses, and industry publications that uncritically carry these claims have made it a contentious topic among SEO marketers.
Another significant point highlighted by Fishkin and King concerns how Google might use Chrome data in its search rankings. Google Search representatives have claimed they don’t use anything from Chrome for ranking, but the leaked documents suggest otherwise. One section, for instance, lists “chrome_trans_clicks” as influencing which links from a domain appear below the main webpage in search results. Fishkin interprets this as Google using the number of clicks on a page in Chrome to determine the most popular/important URLs on a website, which go into the calculation of which to include in the sitelinks feature.
With over 14,000 attributes mentioned, researchers will be examining the documents for weeks to uncover hints. There’s mention of “Twiddlers,” or ranking tweaks deployed outside major system updates, that adjust content ranking based on certain criteria. Elements of webpages, such as the author’s identity, are mentioned, as are measurements of a website’s “authority.” Fishkin notes that much is absent from the documents, like information about AI-generated search results.
So, what does this mean for everyone outside the SEO industry? Expect website operators to scrutinize this leak and try to decipher it. SEO often involves experimenting to see what works, and publishers, e-commerce companies, and businesses will likely conduct various tests based on the documents’ suggestions. As a result, websites might start to look, feel, or read differently as these industries try to understand this new, albeit vague, information.
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