Google released a new podcast episode in which John Mueller, Gary Illyes, Martin Splitt, and a member of the Google search quality team, Duy Nguyen, discussed how Google tackles search result spam and ranks search results.
When asked how Google ranks search results, they shared that Google first comes up with a shortlist of around a thousand results. That list is produced depending on whether the query and the page’s material are relevant and topical. Following the list’s creation, Google applies several of its ranking signals and criteria to the shortened list. That’s where “the magic” happens, according to Gary Illyes.
He further explains that these documents are assigned scores or numbers, and Google assigns a number. They then calculate that number using the signals that they collected during indexing plus the other signals. And then essentially, what you see in the results is a reverse order based on those numbers they’ve assigned.
On how Google prevents spam, Duy Nguyen shared that Google uses machine learning models to deal with obvious spam. This machine learning model has years of data to improve its spam prevention method and search. It also allows the Google search team to focus on more critical work. For example, it could include hacked spam, online scams, and other issues that the machine does not pick up.
Key takeaways:
- Listening to Google representatives about search may give clues into what matters with rankings.
- SEOs should focus on making better functionality, quality content, and an overall better user experience.
- Because Google has hundreds of ranking signals, focusing on just one or two is unlikely to help you rank well in Google Search.
Read more: https://searchengineland.com/google-on-how-it-ranks-search-results-and-prevents-obvious-spam-350218