Most people can say they've had the experience of typing a phrase into Google and receiving results that didn't quite match what they were searching for. This was the result of technology not being able to fully understand the human language.
Well Google has finally come up with a solution... the Google BERT update.
In this blog, learn how Google's Bert machine learning technology is able to understand the context and intent behind search queries.
Google's Need To Understand Language Has Increased
Over the last 15 years, Google has been working on making their search queries better and better... and one way of achieving this is by trying to return results they can't anticipate.
This is based on the fact that people typically go to Google to learn.
They don't always know the correct words to use or sometimes how to spell those words, so this is where Google's necessity of understanding language has come into play and continued to advanced over the years.
Now their research team is using machine learning - a subset of artificial intelligence - to study computer algorithms and statistical models that perform specific tasks relying on patterns instead of explicit instructions.
This has allowed Google to make huge steps forward in how they understand search queries, leading to the creation of BERT.
What is the Google BERT update?
BERT is an open-sourced, neutral network-based technique for natural language processing (NLP) pre-training that stands for 'Bidirectional Encoder Representations from Transformers'. It was officially launched in late 2018 and allows anyone to train their own question answering system.
Essentially, these 'transformer's process words in relation to all the other words in a sentence, rather than one-by-one in order. This is what allows the BERT model to understanding the intent behind search queries, by considering the full context of a word by looking at the words that come before and after it.
Not only were advancements in software technology needed for this, new hardware was required as well. This is why Google is also using the latest Cloud TPUs to display search results to get people more relevant, contextual answers.
How Google's BERT Updates Affects Content Marketing
Since Google will continue to apply BERT to both ranking and featured snippets in Search, allowing you to search in a natural way, using longer, more conversational queries, this will force marketers to create content with this in mind.
If you want your content to be found, your content marketing strategy will need to reflect these changes in search.
Gone are the days of targeting one keyword and adding that to your URL, title, meta, alt text, and copy... and honestly we couldn't be happier about this.
It's so much easier to write content that reflects how humans actually talk, and with the increase of smart speakers, voice assistants and Google Home, the need to develop contextual content will only continue to grow.
You might be thinking now, do you need to optimize your content for BERT?
The answer is... not really.
Danny Sullivan, Google’s public Search Liaison, states that there is nothing that you should do now that you shouldn’t have done before BERT. And that is: write content for users.
With that said, because the BERT update is going to focus heavily on rankings and featured snippets, you want to make sure you are keeping up-to-date with the most current SEO best practices and optimizing for featured snippets!
Check out these 15 tips for featured snippet optimization from Databox.
You can also learn more about featured snippets in one of our other posts titled, '5 HubSpot SEO Strategy Tactics You Need To Learn Now'.
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