Google BERT Algorithm to understand natural language
Google releases the major change in its algorithm in intervals, After the RainkBrain releases 5 years ago. Google now releases BERT Algorithm, which is the biggest release in search after the RankBrain. In this article, we will discuss the Google BERT algorithm and its effects.
BERT rolling out in October 2019 and getting fully live in a time interval. Basically, it is rolling out for English language queries and will expand to other languages in the future.
What is BERT?
BERT stands for Bidirectional Encoder Representations from Transformers. It is a computer to understand the language used for natural language processing. It is an open-source algorithm.
BERT helps in understanding the nuances and context of words in searches and gives the user the best matching and relevant search results.
Now, you must think that RainkBrain does the same? The answer is Yes, but RainkBrain check Queries and Context while BERT checks for Words and Context.
BERT does not replace RankBrain, it is an additional method for understanding queries and context. RankBrain will be used to understand the queries but When Google thinks that BERT can Analyze it more accurately then BERT will be used. BERT improves the analysis of search queries.
RainkBrain understands the whole query and produces the result according to the query. While BERT understands each Word in the query and provides the result.
For Example (reference from Search Engine Journal Article), I type the query of how to catch a cow fishing?
In a few countries, the word “Cow” in terms of the Context of fishing means a large striped bass.
Striped bass is a popular saltwater game fish that millions of anglers fish for on the Atlantic coast.
Before the month of October, If you type this phrase in search query Google provided results related to livestock, to cows.
After the BERT rolled out, Google provides a search result related to striped bass and fishing.
Impact of Google BERT Algorithm:
BERT impact on 1 of 10 search queries. Irrelevant and spammy content will hammer with the BERT Algorithm. It impacts on the featured snippet result as Google says BERT will be used globally in all languages.
Can We Optimize for Google BERT Algorithm:
In terms of SEO, there is no need to do any changes, just remember that your Content can meet the expectation of user search queries. It must provide all the answers to the search query and relevant to the topic. The rest of Onpage SEO tactics can be the same and must be followed only things keep in mind that content must be useful for users and leave the rest of things on Google.
Frequently Asked Questions on Google BERT Algorithm:
How does BERT Work?
BERT looks for the entire set of words in the search query and provides the search result according to words in the search query. Keep it noted that it is a bidirectional training.
Does Google Uses BERT for all Searches?
No, Google uses it for 1 out of 10 queries for the language English. Particularly for longer queries and for searches where prepositions like “for” and “to” has a lot of meaning.
Does BERT affect Featured Snippet?
Yes, Most of the featured snippets getting affected by BERT.
What is the Difference between RankBrain and BERT?
RankBrain runs parallel with the normal organic search algorithms and checks the full query for the search result.
BERT looks for the content before and after the word to check the relevance of the result with the query.
Is there an SEO technique to Optimize for BERT?
Just write the content that covers the topic very well and relevant to the topic. Rest of the SEO process is the same.
For Which Languages BERT Releases?
Google releases the BERT algorithm for more than 20 languages, the list is as follow, Portuguese, Punjabi, Romanian, Russian, Serbian, Sinhalese, Slovak, Slovenian, Swahili, Swedish, Tagalog, Tajik, Tamil, Telugu, Thai, Turkish, Ukrainian, Urdu, Uzbek, Vietnamese and Spanish.
After releasing BERT, many people think about optimizing the website for BERT algorithm and have lots of confusion about BERT. Its a neural Language algorithm to process query more accurate so just write for the user and forget about other things.