How machine learning is redefining SEO and Google Search!

With RankBrain, Google is going the machine learning way for SEO

With RankBrain, Google is going the machine learning way for SEO

 

For anyone who is a stakeholder in the SEO business, arguably the most keenly anticipated event is the Google algorithmic update. Whenever Google updates its algorithm, content owners and marketers get busy with deciphering if the new code changes would cause any sudden dip in ranking of their pages. If there are beings in the animal kind SEO aficionado care the most about, they are Panda and Pigeon, until Mobilegeddon came along!

But all that, it seems, is about to change. The change is expected to be transformational, though through a long gradual process. I am referring to significant inclusion of machine learning algorithms in the SEO updates. Why do we consider it to be transformational? Inclusion of machine learning will help the algorithm self-learn and update itself seamlessly. This will eventually eliminate the need for Google to manually update the algorithm after periodic intervals. What it will also eliminate is the frantic panic the community suffers immediately after each algorithmic update. Not many know that even today, Google employs a seemingly large force of human quality assurance workers that form the backbone of its search engine algorithm effectiveness.

But what exactly is the need to include machine learning methods in SEO algorithms? Is it only to remove manual updates? The clear answer to the second question is “no”. The intent is to build better algorithms. Future SEO algorithms should have heightened ability to understand content. The current capabilities mostly rely on keywords and other specific parameters. With this intent, Google included RankBrain method in its latest SEO algorithm. RankBrain tries to understand the context of the content in an attempt to eclipse the concept and significance attributed to keyword density. In layman terms, RankBrain is now trying to read sentences, instead of merely seeking keywords in them. It also further improves upon the Latent Semantic Indexing (LSI) method, the de facto way to ascertain relevance of the content.

The results is that Google is able to classify pages better based on the content. It will also look for content that might not exactly match the keyword in the search query yet answer the query. Since deployment, RankBrain has become Google’s third most important signal in its SEO, according to SEO blog Search Engine Land. A publisher Wordstream conducted some analysis to suggest that RankBrain works similar to the Google AdWords Quality Score and is aimed at transitioning the focus of the content industry from current SEO to metrics such as CTR. It is also undeniable that RankBrain is just one among more than 200 factors in the Google Hummingbird algorithm, and despite its high rank, isn’t playing a make or break role yet in the SEO world. One must realize, however, is that algorithms such as RankBrain and other machine learning methods can play a vital role in deciphering 15 percent of daily queries on Google which its systems have never seen before.

Anubhav, a data scientist, writes about new developments and future trends in the machine learning and data analytics domain.
He can be reached at anubhav@thinkbigdata.in
Follow him on Twitter at: https://twitter.com/think_bigdata

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