Google BERT

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BERT - Bidirectional Encoder Representations from Transformers - is a neural network-based natural language processing technique and can better understand the full context of your search query by looking at all the words in your search. Google has developed new software and hardware for this update to improve your search results and dive deeper into the relevant information you're looking for.

Google says, "With our research team's latest advances in the science of language understanding - enabled by machine learning - we are significantly improving the way we understand search queries.

The search giant realized that in the billions of search queries it receives every day, people were looking for things they wouldn't normally ask about - in an everyday conversation, for example. Rather, people were tailoring their questions to what they thought Google would understand best. With BERT, you now have the ability to search the way it feels natural to you, rather than the way you think Google or a robot would best understand.

For conversation requests and Long Tail Keywords where prepositions like "for" and "to" are influential words, Google - or rather BERT - can understand the context of the words in your search. BERT models are able to recognize that a word as simple as "to" has a lot of meaning.

Previously, Google systems matched search terms with keywords found on a page, but BERT models understand words in different use cases. For example, Google tested before BERT was introduced and found that a search of "do beauticians stand a lot at work?" resulted in a page with "alone" in the text simply because the word "stand" appeared. The SERP was not relevant to the search query. The BERT now recognizes that "stand" was used in a different context.

Has the Google BERT-So, will the BERT update have an impact on your SEO? During the introduction of the BERT update, you should not make any major changes to your SEO. Search engine optimization notice, as was the case with previous Google algorithm updates. Danny Sullivan from Google has said that you should not optimize for BERT. Keep creating content and optimizing for people and their natural search queries.

BERT models are used for the Ranking applied and will focus on the Featured Snippets Impact. Google says, "BERT will help search better understand one in ten searches in the U.S. in English, and we'll expand this to other languages and regions over time."

The aftermath of BERT

Following the release of BERT, B2C companies, including AT&T, found that terms with high Search volume had a positive effect on their rankings. However, they were no longer ranked for solution pages, but for information pages. For this reason, BERT changed the Content strategy for digital marketers. Instead of creating content to sell something to a consumer, digital marketers must first and foremost define the topic they are looking for.

BERT is designed to find out exactly what the user is searching for so that Google can deliver the most relevant results pages to the searcher. Below you can see several search use cases for the keyword "rose". The question "What is a rose?" led to results pages for what a rose flower is. In this case, Google used natural language processing and assumed that the searcher was looking for general information about what a rose is.

Google BERT Example - BrightEdge

Then you see that "What is a rose" provides information about the rosé wine. Here, Google assumed a search for the wine and provided information on the entire first page about the pink wine, how it is made, where it comes from, why it has become so popular lately, and more.

Natural language processing BERT - BrightEdge

Below you can see that searching for "define rose" leads to several different pages of results. Rose is not only a flower, a type of wine, and a name, but also a verb. The search "define rose" was not as unique as the ones above and offers several definitions for "rose" to answer a number of possibilities for the search.

Track BERT changes

It's difficult to track whether or not BERT has affected your site's rank, but it is possible to see how it has affected your Ranking-content continues to change over time.

Data Cube offers monthly documentation to report on changes in the Keyword-rankings. You can use the keywords in the Keyword Track reporting week by week to see which keywords are ranking for your pages. There you can see how the content is performing and what type of content your page is ranking for. Is it what, who, how the content is? If you rank for Glossary- and FAQ pages, you should create a content plan with even more informative content for your website.

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FAQ

What is Google Bert? arrow icon in accordion
Google Bert is a machine learning model developed by Google to better understand natural language. It is part of the BERT family of machine learning and was released in October 2019. BERT is an acronym for Bidirectional Encoder Representations from Transformers.
How is Google Bert used? arrow icon in accordion
Google Bert was developed to improve the accuracy of Google's search engine. It uses machine learning to better interpret and understand natural language queries. This means that it understands more search queries that are more complex and formulated in natural language.
Why was Google Bert developed? arrow icon in accordion
Google Bert was developed to improve the accuracy of Google's search engine. It uses machine learning to better interpret and understand natural language queries, so it understands more search queries that are more complex and formulated in natural language.
How does Google Bert work? arrow icon in accordion
Google Bert uses a bidirectional transformer architecture to understand speech. It looks at two things at the same time: Word sequences and context. This means that BERT has a better understanding of natural language because it looks at both the words and the context.
What are the advantages of Google Bert? arrow icon in accordion
Google Bert offers many benefits, including improved search accuracy, better understanding of natural language queries, improved understanding of context, and improved efficiency.
What problems does Google Bert solve? arrow icon in accordion
Google Bert solves many search accuracy problems by better interpreting and understanding natural language queries. This makes it easier for people to find the answers to more complex search queries.
How is Google Bert different from other machine learning models? arrow icon in accordion
Google Bert is different from other machine learning models because it uses a bidirectional transformer architecture to understand language. This allows it to interpret and understand both the words and the context in a natural language query.
Can Google Bert be used anywhere? arrow icon in accordion
Google Bert cannot be used everywhere, but only in Google's search engine. It was developed specifically to improve search accuracy and is therefore not suitable for other applications.
What languages does Google Bert support? arrow icon in accordion
Google Bert currently supports English and Chinese.
Will Google Bert be developed further in the future? arrow icon in accordion
Yes, Google Bert will be developed in the future to further improve the accuracy of Google's search engine. More languages will also be added to enable improved understanding of natural language queries in other languages.

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