Google’s Latest Search Algorithm


BERT, acronymed as Bidirectional Encoder Representations from Transformers, is a new update rolled out by Google and is an innovation in Machine Learning for Natural Language Processing (NLP).

You must be wondering if it is relevant and worth my time or not? Indeed, Google must be having some intent behind it, which we as users should know. Besides, it one of the biggest updates Google has released after RankBrain as it can affect the traffic on your site directly. BERT impacts search by identifying the intent behind search queries of users. Let’s have a detailed look.

Google BERT Algorithm: Explained


Google speaks of BERT as Google’s neural network-based technique for pre-training of natural language processing (NLP). Google continues to make changes in the search system to make it easy for Google to comprehend the user’s needs and queries. BERT is in itself is a breakthrough that can help discern Google the context of the words used to show relevant search results. Initially, it is rolled out for English language queries but its exposure will expand to other languages in the future. BERT evaluates search queries and not web pages to improve Search Query Understanding. It’s not only an algorithm update, but it’s also a machine learning for NLP and research paper.

BERT’s Impact on Organic Rankings and Featured Snippets



To date, Google often gets confused with words like “to” and “for” and their usage but after BERT, this issue is resolved. BERT can bring a change in organic ranging by implementing precision to long, colloquial, and specific search terms to produce intended results. It simplifies the results for long-tail keywords precisely.



Improved Understanding of linguistics


Bert is designed to reduce the ambiguity of words with multiple meanings, i.e., it pays focus on Ambiguity, synonymous & Polysemy of sentences and phrases as minor as “to” and “for”. It can now understand the relation and similarity between king and queen and man and woman with an enriched understanding of part-of-speech.

How it affects search ranking?



BERT impact upon top-of-the-funnel keywords. The specific the search, the accurate the results. Besides, informational keywords are easy to rank. Most of us believe in posting long-form content to rank, however, this is not the trust, Google focuses on quality than quantity. Emphasize on creating a better user experience by answering user’s queries better than your competitors. Use anything from audio and videos to images to show relevant search results.

Have a look at this example:



For instance, when we google “let’s not play Ludo” the queries will rather show searches for “let’s play Ludo” with no or little focus on the word “NO” in featured snippets; same happens with “Parking on a hill with no curb” in which the search query ignores “NO” and emphasizes on “CURB” word. However, with BERT, the results become more precise and relevant by letting Google understand the relation between two words.


In a nutshell, Google can produce results based on search intent more like a human and less like a robot. BERT helps google understand the language just like the humans do, it now focuses on context rather than the word itself to read between lines.