Google said, "These improvements are oriented around improving language understanding, particularly for more natural language/conversational queries, as BERT can help search better understand the nuance and context of words in searches and better match those queries with beneficial results.
Particularly for longer, more conversational queries, or searches where prepositions like "for" and "to" matter a lot to the meaning, the search will be able to understand the context of the words in your query. Thus, you can search in a way that feels natural for you."
What is the BERT algorithm?
BERT stands for Bidirectional Encoder Representations from Transformers. It is a transformer-based machine learning method for natural language processing encrypted by Google. This machine learning technique was created and launched in 2018 by Jacob Devlin and his colleague.
In 2018, Jacob Devlin and his colleague from Google designed and launched the BERT algorithm. In 2019, Google leveraged BERT to understand user queries better.
In simple words, BERT is a natural language processing pre-training approach that is specifically used on a large body of text. It operates tasks including entity recognition, question-answering, among other natural language processing, and parts of speech tagging. BERT helps google inculcate natural language text from the web. Google bring forth this technology, and others have created modification and up-gradation of BERT.
How does BERT affect on-page SEO?
You can't optimise your website according to BERT. Rather than focus on writing engaging content for your audience, pay attention to responding to a searcher's intent, be aware of the specific motivation of your audience, and create an incredible user experience for your audience.
To get better output from your webpage content, focus on long-tail keywords that will give you better ranking on search engine result page, analyse organic acquisition performance for educational content, take featured snippet ownership, check movement of your competitor website.
The consequence of BERT in Digital marketing.
After BERT was released, B2C companies have noticed that a high volume of content improves their website ranking. But they were not ranking for ‘about us’ and ‘solution’ pages anymore. Instead, they got organic traffic from informational pages.
Because BERT changes content marketing strategy for digital marketers, thus, digital marketing experts should create content on some defined topic rather than content related to selling their products.
BERT is designed to analyse the user queries on Google.
Thus,
Google can provide the most relevant search result to a user. The new
BERT updates don't replace the old algorithm of Google. But upgrade
Google's language processing abilities, and make it more sophisticated
to parse.
The optimisation procedure is similar to RankBrain.
Write contents on common queries placed by users. Google also claimed
that the old SEO method would not be enough for a better ranking.
Instead, the best approach is to make original, valuable, informative
content based on search queries and long-term keywords. That will help
you to build up authority. Be aware of what audiences want.
SEO
experts used to focus on meta description, inter-linking, keyword
density, and content optimisation in the old search engine strategy. But
the upgraded Google algorithm BERT focuses on website content that is
valuable for people and gets more organic traffic for content.
So, digital marketing company India
should create content based on demanding topics and not around the
high-volume keyword. This is the best way to optimise for BERT.