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Sep 25, 2023 4:07:53 PM
Eric Lehman, a former Google software engineer with a 17-year tenure, recently testified in the ongoing U.S. vs. Google antitrust trial, shedding light on Google's ranking mechanisms.
Lehman stated that clicks play a role in rankings, a point that has raised questions and debates within the industry.
However, Lehman clarified that clicks are not a direct ranking factor. This revelation has prompted discussions about Google's ranking algorithms and the weightage assigned to user behavior.
In addition to discussing clicks, Lehman highlighted the increasing importance of Google's machine learning systems, BERT and MUM, in comparison to user data.
He pointed out that advancements in technology allow Google to rely more on unsupervised learning of raw text, potentially diminishing the need for vast amounts of user feedback.
The distinction between "user data" and "training data" was also addressed during the trial. While some questioned whether BERT's effectiveness was linked to Google's access to user data, Lehman clarified that "training data" referred to a different dataset.
Lehman's testimony also touched upon Google's avoidance of discussing the use of clicks in search rankings.
This practice, Lehman explained, was aimed at discouraging the perception that SEO could manipulate search results.
The SEO community has reacted strongly to Lehman's statements, using them as evidence of Google's alleged deception regarding the use of clicks in rankings.
However, Google's Gary Illyes previously acknowledged that Google employs historical search data for its machine-learning algorithm RankBrain, indicating that user behavior data plays a role in the search giant's ranking systems.
In summary, while Google does track clicks and user behavior in its search results, it does not necessarily translate into direct ranking factors.
The exact role of clicks in Google's ranking algorithm remains a topic of speculation and debate within the SEO community.
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