Learn How BERT Algorithm Optimization Will Impact Your Google Search
We are going to investigate the new optimization model of Google called the BERT Algorithm Update. First, we must look at what BERT Stands for. The introduction of BERT by Google was to improve the search algorithm update results. In our world of today, every day seems to be different.
In this age as technology improves, you see more tech-inclined people coming from every part of the world regardless of race, color, ethnicity, religious background and so on, we all have something to offer in this evolving world of today. Truly the world is now a global village that can navigate within seconds or minutes in the palm with a single fingertip.
In the past there were several tech companies, but as time goes on the tech giants swallows up other weaker tech companies, now this is the time for Google a global powerhouse and tech giant, Google algorithm update has made a lot of difference with the way we see the online world of today, with the introduction of BERT they have taken it an extra step thereby leaving other companies to play the role of catchup.
What Is BERT Algorithm?
BERT (Bidirectional Encoder Representations from Transformers) is an AI (Artificial Intelligence) language published by research at Google. it’s a neural network-based technique for natural language processing (NLP) by Google this system started last year, it was designed to handles tasks such as entity recognition, part of speech tagging, and question-answering among other natural language processes. BERT Algorithm optimization helps Google understand natural language text from the Web.
It is a Natural Language Process (NLP) that builds on pertaining contextual representation, it makes it unique from the rest of the model as it is the first bidirectional language that is not supervised. It is an open-sourced project, anyone with machine learning knowledge can easily build a Natural Language Process (NLP) model without the need for sourcing huge datasets for training the model. It saves time, knowledge, energy and resources.
How It Came and What It’s Targeting?
The idea of BERT rolled out in Google algorithm update in October 2019 for English language queries including snippets, as Google intends to extend it to all languages, though they have not set a time to accomplish that purpose yet.
Google said that the inclusion of the BERT algorithm in their search update will help it understand better the intent of the user’s search queries, which should mean more relevant results. BERT will impact 10% of searches, as Google believes that it will likely have some impact on a brand’s organic visibility and traffic.
Their major target is to have more reach to users worldwide, BERT is pre-trained on a very large corpus of unlabeled text which includes the entire Wikipedia (that’s about 2,500 million words) and a book corpus (800 million words) with such large collections of word it has a wide target and a wider reach to users.
Points to Note in BERT:
- On-page SEO
It is just a simple checklist that will bring more search engine traffic from every piece of content that you publish. For you to have SEO-friendly URLs, you need to make them short and sweet, always include your target keyword in your URL.
For your SEO to have good benefits always ensure you use images, diagrams screenshot most times, in the backlink, because Google pays attention to user-interaction aided by multimedia boosting.
- Search Query & Search Intent Optimization
BERT algorithm optimization allows Google to understand more human-like queries, queries, and content that are more natural language and conventional based.
BERT helps Google understand the nuances and context of words in searches and better match those queries with more relevant results.
- Featured Snippets
Featured Snippets can help you rank high in Google search results, to attain such levels you must take into consideration what featured snippets are, how it is to understand them and how to optimize for them.
First, a featured snippet is a special search result that appears at the top of Google search result that contains content that Google thinks answers the searcher’s question. Featured snippets include; content relevant to the query, page title, page URL finally an image from Google’s image search algorithm update results for the keyword.
Types of Featured Snippets
There are 4 ways featured snippets presented, they are:
Content Optimization & New Ranking Opportunity
Content optimization is the process of making sure that your content is written in a way that it can reach the largest possible target audience, this process includes making sure associated keywords are present, adding Meta tags and title tags and all relevant links. With BERT it has a far wider reach since Google has more access to millions of words from Wikipedia (2.5 million words) and book corpus (800 million words).
This makes me believe that with such a huge level of word data it would be easy to gain high ranking if you follow the steps carefully step by step.
What BERT Can’t Do?
BERT cannot optimize, the only way to get around it is to improve your content by exploring more of the large dataset of words which Google has, another way to do such is by studying more about the project you want to write about by making a niche that can easily get the attention of the readers or the searchers in such niche make careful selection of the right meta tag and title tag.
Change is the only constant thing, there is not much to say about the Google BERT that makes much different just that it gives the users better ground to get best results from their search or online experience, in more future updates I believe that the BERT system would greatly be improved once Google delves into other languages, as they do so, they will have more understanding of were exactly BERT needs improvement and work on it. There is no doubt that with the new BERT algorithm update, your result in SERP i.e search engine result page, will have a real upward effect. So, ensure you follow to get updates about any new information that comes up.