Frequently Asked Questions on Google’s BERT Algorithm

Google’s BERT Algorithm

It was on October 25, 2019 that Google announced BERT (Bidirectional Encoder Representations from Transformers), its biggest algorithm update since RankBrain in 2015. Considered to be the most important update in five years, Google’s BERT rollout is expected to impact your site’s organic rankings. With BERT, Google aims at understanding the complete context of a word in a sentence and making it easier for searchers to find the right information they are looking for. Professional digital marketing services in Long Island will be up to date with such current algorithms to meet their clients’ online marketing requirements.

Hope you have read our blog on Google’s BERT Machine Learning Update.

Here are some frequently asked questions and answers about BERT.

What is BERT?

BERT or Bidirectional Encoder Representations from Transformers helps Google understand natural language better, particularly in conversational search. This neural network-based technique for Natural Language Processing (NLP) was open-sourced by Google last year. BERT will help people find what they’re actually looking for. With BERT, Google can now return more accurate, better results for more complex and more conversational long-tail search terms.

Google’s official blog says that BERT’s creation “was the result of Google research on transformers: models that process words in relation to all the other words in a sentence, rather than one-by-one in order. BERT models can therefore consider the full context of a word by looking at words that come before and after it. This is particularly useful for understanding the intent behind search queries.”

How does BERT impact content and search?

This new algorithmic update will impact around 10% of queries. It will impact organic rankings and featured snippets in other languages. It focuses on delivering useful, informative, authoritative, and accurate information to users. It also helps Google better understand the longer, more conversational and complex search queries.

In its blog, Google has mentioned an example to highlight how BERT impacts search.
If you search for “2019 brazil traveler to USA need visa”, results before and after BERT will be

BERT impact content and search
https://blog.google/products/search/search-language-understanding-bert

BERT allows Google to process words in search queries in relation to all the other words contained in the query – unlike the word per word process that Google has been using before. Google’s application of the BERT model enables them to do a better job of assisting users in finding useful information. A page will be considered unhelpful if it doesn’t match the context in a specific search query. Google’s BERT can also notice the intricacies of language, and understand how the use of specific words completely changes the meaning of what’s being requested.

How does BERT impact featured snippets?

Other than the U.S., BERT is not yet applied to foreign search markets apart from the Featured Snippet cards. So far, this rollout has been put in place for featured snippets in 12 countries. Google says that BERT will affect 1 in 10 English-language searches as well as searches returning Featured Snippets for any language that supports snippets.

With an example, Google compares the featured snippets for the query “parking on a hill with no curb”. Earlier such questions will confuse search engines and the readers may not get relevant results.

BERT impact featured snippets

When applied to ranking and featured snippets in search, BERT models will consider processing words in relation to all other words in a sentence rather than considering them one-by-one. With the focus on featured snippets, Google highlights that searcher intent is to find content that responds exactly to their questions. With the BERT update, Google also focuses on showing even more relevant featured snippets.

BERT and RankBrain – are they the same?

Even though some of BERT’s capabilities sound similar to RankBrain, Google’s first AI method for understanding queries, both are different. While RankBrain adjusts results by looking at the current query and finding similar past queries, BERT looks at the content before and after a word to inform its understanding of the meaning and relevance of that word. Both these algorithmic updates are used by Google to process queries and web page content to gain a better understanding of what the words mean.

How to optimize my content for BERT?

Google advises not to optimize for BERT, but to optimize your content for humans. This search engine giant says that there’s nothing to optimize for BERT. However, certain strategies can be used to make your content easy to understand for readers.

The best content is those that answer and satisfy the needs of users.

What you can do is –

  • Make your content as simple and direct as possible
  • Provide quality and informative content that is useful for readers
  • Avoid using unnecessary or difficult to understand words in content
  • Try to improve search visibility for a particular topic than for a specific keyword
  • Focus on keywords or queries you target
  • Use analytics to check the long-tail keywords/phrases users use to search for your products or services

By doing it this way, you’re not only optimizing your content for users but also helping search engines better understand the content you’re putting out.

For website owners, digital marketers and copywriters, Google’s BERT update is a reminder that the ideal way to improve search rankings and satisfy readers is by providing accurate content that’s rich in information and which answers the questions your searchers are asking. Businesses can consider partnering with experienced hands providing result-oriented content writing services including web pages, blogs, articles marketing materials and more.