Google BERT is an acronym for ‘Bi-Directional Encoder Representation from Transformers.’ It is one of the most extensive and comprehensive algorithm updates by Google which transformed the way a user performs a search on the internet. The latest update is based on the performance of long-tail organic search queries, and their impact on the search ranking, traffic, revenue, and conversion ROI.

With BERT, Google seeks to make search results better in today’s fast paced world. It is a known fact that Google receives more than 63,000 searches per second on a daily basis. This means that more and more users are relying on the search engine giant to get their day to day tasks done.

Therefore, Google BERT will make the search engine more receptive towards user’s query. This is done by promoting the natural and conversational language a computer can understand and interpret in a human-friendly readable format.

With a better understanding of user search intent, businesses get to benefit from the higher search ranking position with more traffic and revenue. The use of long-tail search keywords allows the machine learning algorithm to understand the complete context of sentences with the next and previous written words. The search bots can interpret the complete sentences along with prepositions like “For” and “To”. These prepositions are added up to make a huge difference in the search ranking and show the exact results to the visitors.

The use of long-tail search keywords allows the machine learning algorithm to understand the complete context of sentences with the next and previous written words. The computer can interpret complete sentences, like humans do, along with prepositions like ‘For’ and ‘To’.

But, the question remains whether this will impact businesses?

Impact of Google BERT Update on Search

The real impact of the latest BERT update is to show up the better and refined search engine results. It allows the businesses to keep their focus on producing high quality and relevant content and understand the audience’s behavior to increase the traffic. The audience behavior is the essential element that allows a business to analyze the age, gender, location, interest, preference, lifestyle, and income of visitors.

It is also necessary to find the arrival of traffic from various mobile and tablet devices and cross-browser compatibility. It increases the click-through and conversion and reduces the bounce rate to keep the audience stay for longer on the website. The power of original and user-friendly content can engage the audience and hook them to the website to increase the visibility and better search presence.

Enhanced Feature Snippets

Featured Snippets are the short and extracts of website information shown on the top feature post of Google SERP. These snippets can be displayed in a single small paragraph, list, or table format to give higher exposure to the website and increase search ranking. The BERT update focuses on optimizing and enhancing the visual appeal of featured snippets with exceptional quality content and a wide image. There are some essential ways to improve the search presence of featured snippets. Using how-to and Q/A schema markup can add a huge difference in the appearance of ranking on the SERP.

National Language Processing (NLP)

One of the most advanced features of BERT algorithm update is National Language Processing (NLP). It is a recent technique of understanding the flow of human language tone and converting it into machine language for better display of results. The NLP works on artificial intelligence technology that uses a question and answers based long-tail keyword search queries in Google Assistant. Google Assistant is a personal and virtual assistant device that receives voice search queries and translates them into textual and graphical user-friendly results.

The purpose of NLP is finding a definite intent of a search query and improving search behavior performance. It is based on three primary attributes of syntax, semantics, and pragmatics. All of these three advanced techniques enhance accurate grammar, sentence structure, and meaning to the context with expression and emotion in a sentence. With NLP, it is easy and straightforward to detect wrong search queries and eliminate them to promote relevancy and authenticity in content.

Impact on SEO

The impact of National Language Processing is tremendous on search engine optimization. It brings a drastic change in the search query process that shows accurate display results on search engine result pages. NLP promotes structured markup and rich snippet and gives more emphasis on long-tail keywords. It also improves local search content and shows nearby related searches about famous landmarks, restaurants, coffee shops, and shopping places on smartphones and tablets. The original and versatile content is an authoritative source of NLP that aims to bring real meaningful and informative value to readers.

Multi- Lingual Support

The multi-lingual support is an essential feature that makes Google the top leading search engine that promotes 104 different languages of the world. It gives mono-lingual and cross-lingual model transfer to exchange similar context words with other languages. This feature provides an ease of understanding and interpreting complex and difficult languages like Chinese, Japanese, French, Greek, Russian, and Italian. It improves the search capabilities of Google to deliver instant and accurate results in any spoken and written language script of the world.

This Bert Multi-lingual update features named entity recognition, parts of speech tagging, cross script generalization, code-switching and transliteration. It creates both mono-lingual and multi-lingual data sets of every single language for better encoding.

The multi-lingual support features works on four essential elements:


A match feature symbolizes the correct use of grammar, syntax, and semantics in a word sentence. It matches the relevancy of a word to its meaning and context in a sentence and ensures the accurate fitting of words for better content.


This feature makes sure of finding and detecting the wrong and mismatched fitting of words in a sentence. It eliminates the wrong word and replaces with a correct one with strict grammar check. The accurate flow of long-tail keywords has become easier to understand and comprehend for search engine for the relevant display of results.


The copy feature keeps a strict check on duplication and detects the repetition of words to promote unique word choice and vocabulary. Google keeps an eye on those keyword searches that are irrelevant and grammatically incorrect. The core purpose is to find relevant search results with a spoken or written query.


The term gibberish defines the words that make no sense at all. This multi-lingual support feature removes all search queries that have no purpose for a searcher and promotes meaningful query results for higher ranking and traffic.

IS Google BERT Being Used Globally?

The update was rolled out on 25th October 2019 where Google introduced it only in the United States (for now), and applicable to the English language only.

According to the company, it will affect only 10% of searches on Google (i.e. 1 out of 10 searches). For now, Google has not announced when it will be rolling out the BERT update for other regions. But, it is something that is in the plans – adding more countries and languages. The use of long-tail and conversational search queries can help show the better appearance of SERP with high-quality relevant content to bring huge traffic and conversion ROI.


Hence, in a nutshell, the above-mentioned gives a clear idea about the Google BERT Update and how it is being used globally to enhance the way of search. To bring a positive and dynamic change in ranking, content is the best-proven strategy to increase the value of traffic and increase revenue.

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