Google BERT and Its Impact on SEO - Saletify

Google probably made the biggest change in recent times to its search engine algorithm last year, when the company rolled out, what it calls the Bidirectional Encoder Representations from Transformers (BERT). The California-headquartered company has claimed that the new system will impact one out of 10 queries on its search engines in terms of changing the rank of the results returned. BERT, undeniably, will also have an impact on search engine optimization (SEO) techniques.

What is BERT?

The system is being used by Google as a neutral network-based technique for natural language processing (NLP) pre-training. BERT was open-sourced in 2018 and was written in more detail on Google’s artificial intelligence (AI) blog. BERT, in a nutshell, will help computers to understand the input language a bit more like humans. Google claims that BERT will help its search engine to better comprehend the context and nuances of keywords, resulting in more relevant results. For example, if a user enters a phrase like Best SEO Company in Pune, the word ‘in’ assumes importance in its relationship with other words used in the query. The Google search algorithm, previously didn’t understand this relation. This particularly happened when a user entered a preposition in the search box. Google now says that with BERT, its search engine will be able to grasp this nuance which is extremely important in returning more accurate results. The word ‘in’ is a commonly used word and with Google implementing BERT, the user will get a more relevant result from his/her query.

Impact on SEO

Experts say that BERT and its family will improve the understanding of 11 NLP tasks. It’s expected to beat even human understanding where linguists often debate for hours on a single word’s part of speech in a particular phrase. Besides prepositions, understanding pronouns have been much problematic for Google. But BERT is expected to iron out this problem to a great extent.

Also, the Google search engine will be able to understand the context of the query since BERT is bidirectional in nature. A phrase like ‘

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