How Does Google’s New Machine Learning Feature Change SERPs?

Machine learning is not a weird concoction done by Dr. Jekyll… No, it’s a set of principles and concepts in computer science which studies how machines can learn independently. These self-growing and self-learning algorithms can make predictions based on previously gathered data. Basically, a computer will look at signals and parameters and will make relevant predictions.

 

Tech companies are already employing machine learning in their algorithms. Facebook, Pinterest, Uber, Autotrader, Expedia and Yelp are just a few examples of big companies which successfully use this technology. For instance, Pinterest uses it to suggest and display content to users, according to their “previous preferences”.

 

As you probably expected, Google is one of the biggest user of machine learning. Its amazing RankBrain machine learning system is used to refine queries that Google receives daily. It focuses on previously unsearched queries and creates future models for search patterns. According to Greg Corrado, a senior research scientist at Google, the search engine uses machine learning as the third most important ranking factor in SERPs.

 

How does machine learning impact SERPs?

 

Since its launch, Google has worked hard to offer its users the best search results. Also called SERPs, the search engine results page, is the set of pages which reflect the search results, both organic and paid. Machine learning is used to determine a user’s intent for search and return a better result, in minimal time.

 

Each search query is uniquely analyzed by the machine learning system to provide the best result. Of course, static signals are also used, like content length, page speed, domain authority or backlinks. Machine learning is only employed as an additional signaling system.

 

Machine learning is subtle. For instance, two separate users, who may search for the same keyword, may receive different search results, depending on their history or intent. Machine learning improves this type of search, where users are monitored on their type of actions, and not only on the actual keywords.

 

Conclusion

 

Machine learning, by definition, improves itself, so there is a future to it. We expect to see more and more refined results for our queries. And we expect more adaptability from Google, and how we do our search. Probably, in the future, search will be so intuitive, that we won’t even have to use keywords, as we know them today.

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