BERT and its impact on SEO and other Google products



Everybody is talking about BERT and how it is going to affect SEO.


So, what exactly is BERT?

BERT stands for Bidirectional Encoder Representations from Transformers. It is a recent Google algorithm update that has caused a lot of stir and there is a lot of misinformation about it.


BERT is an advanced algorithm that tries to understand how humans communicate.

Whether a search query includes broken language or local languages, BERT will ensure that users get to see more relevant Google search results. Simply put, BERT understands your search queries better and provides you with results that you can understand. For marketers, it can mean that your content marketing efforts will now pay off.


Why was BERT introduced?

Millions of search queries take place across the globe on a daily basis. These queries are entered by diverse people and sometimes they can be incomplete or involve complex conversational queries that can confuse search algorithms. This lack of understanding prevents algorithms from providing users with meaningful answers. Hence, to make conversations with search engines more engaging, BERT was introduced.


How does BERT work?

According to Google, BERT is one of the biggest leaps in the history of search and a huge leap in the last five years. The algorithm tries to understand the context of users’ search query by evaluating the words used in the query.


BERT uses the Transformer (attention mechanism that learns contextual relations between words and subwords) in a query. The Transformer includes two mechanisms- encoder that reads the input text and decoder that produces the answer for the task. Since BERT will generate a language model, only the encoder mechanism is sufficient.


How will BERT affect SEO?

The quality of the content will impact SEO performance. Your SEO content should be meaningful and within the right context if you want to rank higher in BERT-enabled queries. Furthermore, BERT will also affect featured snippets. Snippets that are able to answer search queries with relevant answers are more likely to rank higher in search engines.


BERT’s effect on search results

Here is an example to understand how BERT may impact search results.


The query “math practice book for adults” would formerly produce a list of books for 6-8 graders at the top of organic results. However, with BERT, Google provides you with a list of a book titled “Math for Grownups” at the top of the search results.


(Source:Search Engine Land)


What other Google products will BERT affect?

According to Google’s announcement, BERT will pertain to search only. However, it will impact the Assistant in some way especially when queries conducted on Google Assistant trigger answers via featured snippets or web results from a search, that are influenced by BERT.


Currently, BERT is not being used for ads. However, if it does get integrated in the future, it will reduce some of the “close matching variants” that annoy advertisers.


How to optimize for BERT?

There is nothing to optimize with BERT. Google has consistently rewarded marketers who have included content that satisfies users’ search intent. BERT is designed to interpret that intent and therefore, all you need to do is to keep providing meaningful content to users.


In simple terms, optimizing now could mean that you focus on writing more clear and relevant content rather than compromising between creating content for your users and the linear phrasing content for machines.


Conclusion

BERT is an important algorithm that will surely affect your rankings. This latest update will help users get correct search results. However, do note that BERT is still an ongoing project and may not be able to provide absolutely correct answers now. It will take time to understand different languages and create models for providing better answers across languages.


As of now, BERT is used on a limited number of English language queries that include snippets in the US. Google will soon provide more information about the BERT update.

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