BERT: The New Algorithm Update the Biggest After Rankbrain

Last Updated on July 14, 2021 by Subhash Jain

Google introduced ‘Bidirectional Encoder Representations from Transformers’ (BERT) algorithm update in last week of October 2019. It is a massive update. Such a massive algorithm update with similar magnitude was introduced in 2016 under the name of RankBrain. According to an official announcement by Google, BERT can impact 10% of search results across all the languages . BERT draws wide scale attention because Google stated, “It is the most important and powerful forward leap in past five years; and, one of the biggest algorithm change.”
 

Why So Much Emphasis on BERT:

1 out of 10 organic search results on Google search results are going to be affected by BERT. BERT will get support from all its predecessors like Penguin, Hummingbird, Panda, RankBrain etc. It is a voice search results will be affected in a great way delivering the better experience to users.

Some brands may experience impact on their organic visibility and traffic. It helps the Google to interpret the intent of search query better and to deliver precise results as desired by the users. BERT brings more perfection to Google in understanding the commonly used natural language by the users. Also, the machine learning advancement powered by Artificial Intelligence (AI) innovation efforts. BERT processes the words in the relation to other words of the sentence.

How Can BERT Work to Affect Your Brand’s Visibility and Traffic?
BERT is the neural network- based technique designed for the natural language processing pre-training. Neural networks of algorithms recognize a pattern. What is natural language processing  (NLP)? NLP is a stream of artificial intelligence that deals with linguistics enabling the computers to understand the communication practices by the humans. It will help Google better understand the context of words used in search queries. For example, in the phrases “ten to six” and “quarter to six,” the word “to” has two different meanings; it is obvious for humans but not for machines. BERT will reduce such nuances to deliver better relevant results.
 

BERT trains the language models according to the set of words in a search query or sentence or rather than training the Language in traditional way of ordered sequence of words. It allows the language model to interpret the word context in relevance to surrounding words instead of just the preceding words. For example, in the sentences ‘I operated the bank account, and ‘I visited river bank’, BERT will help Google to interpret the meaning/context of word ‘Bank’ with relevance to words like ‘operated the —account ’ and ‘visited river’. 

Difference Between RankBrain and BERT:
RankBrain runs in the line with normal organic search ranking algorithms, and makes the adjustments in search results calculated by organic algorithms while looking at the current search query and similar past searches. BERT wouldn’t replace RankBrain; it is a more advanced method for understanding the context of words in queries and content. 

Traditional NLP algorithm looks at the content before OR after the word to understand the additional context with query word. BERT makes it different; as, it looks at the content before and after the query word with relevancy. BERT is critical enhancement for NLP designed to interpret human communication that is naturally complex and layered.

How Should I optimize my Content for BERT?

There is nothing specific to optimize for retaining the existing ranking after BERT. BERT also supports the Google’s intent to serve the users by delivering the best fine- tuned results.

Optimize Content For BERT

BERT is designed to interpret the intent of user, therefore, you are required to keep the content focused and precise to a specific users’ interest. Now, the SEO copywriters and content developers may be less concerned for writing for the AI machines; instead, great quality content should be generated only for the ‘users’. The approach: “Don’t create the content specially for BERT; instead, be special for your ‘target audience’.’

Concluding Note:
The noticed changes at wide scale after rolling out of BERT were not much worrisome for SEO community; therefore, chatter about BERT was not as loud as it used to be for other Google updates. Reason being that the results will appear slowly on the basis of reshuffled search results. However, SEO community needs to welcome BERT by changing its commonly applied AI machines centric approach for content development. Write to please the users not the machines.          

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