What is BERT and how is it important in content marketing strategy
What is BERT?
BERT stands for Bidirectional Encoder Representations from Transformers. This technique was created by Google, its neural language to a technique that helps google to understand search queries and provides better results, which are more relevant for the users.
BERT helps Google search engines to understand queries and the meaning of words in search queries. With the BERT algorithm, it understands the words in a given context and synonyms to search for beyond the words in a search query.
In near future, BERT will reflect on content creation for different websites, also will impact the search results, and people will try to write more for humans, not for the machines, It will surely be one the latest SEO trend’s in 2020.
Importance of BERT in SEO
The following are some points that show the significance of the BERT in SEO:
- Google’s BERT improves the understanding of search queries. It analyzes search queries, not web pages.
- It provides a facility to Google to better understand what exactly users are looking for and produce accurate search results and featured snippets.
- It can translate the given word by looking at the words that are used before and after that specific word. This makes easy to understand the query.
- It helps a machine to understand the meaning of any search query or word in a sentence.
How does BERT work?
It uses different approaches to learning. It takes billions of sentences at training time, and then it has to find a random selection of missing words from those sentences. After completing its training it gets an idea that how these sentences fit together grammatically. Here, we have explained how Google BERT works:
- It takes the search query
- Divide a query word-by-word
- Consider all possible relationships between words
- Make a bi-directional map and outline the relationship between words
- Analyze the pairs of words and get the meaning of those pairs
Let’s discuss this with an example:
In the above example, the meaning of the word ‘optimize’ changes when it integrates with other words. The relationship is done in both directions, that’s why we have used a bidirectional arrow to make it clear. This is a very simple example that shows how BERT looks at the context. It identifies the relationship with each word and other meaningful segments.
If a BERT deeply analyzes this contextual relationship then it may look like:
Before BERT Update
Before BERT update there was a big confusion with a preposition, but after the BERT update, it resolves this problem. The meaning of a sentence is changed by a preposition, so understanding of this thing is important for a quality search result. Suppose the difference between “of” and “for” etc. it is important for Google to understand this difference. After BERT update this problem has resolved.
After BERT Update
BERT is bi-directional, BERT encodes a sentence in both directions. It takes the target query or sentence and looks at all possible relationships between words.
Its bi-directional method is different from earlier NLP (Natural Language Processing) frameworks. In the case of the OpenAI GPT NLP framework, it encodes the sentence in only one direction, i.e. left-to-right.
Later NLP framework model ELMo encodes a sentence in both sides, i.e. left side and right side of a target word. But this model integrates the encoding independently which disconnects the context between each word.
After BERT update, it examines the sentence by breaking it down word-by-word and identifies the target word by making all possible pairs simultaneously. It can examine how the meaning of the sentence changes by making pairs and consider how the meaning of the words impact on the context of the sentence entirely. Below example will make it a bit more clear:
In the above examples, the BERT goes in both directions. BERT will make a pair of target word with every possible word. BERT looks at the surrounding collocates (gather) to determine the meaning of the word used in the sentence.
Windows 7 often occur with electronic devices such as computer, laptops etc. and here laptop is associated that means the definition is correct according to the context. Here window is not that window which we use for walls. So, BERT has solved this problem by determining the sentence using the bi-direction technique.
Optimizing Your Content Marketing Strategy for BERT
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Voice Search and BERT
Google keeps on trying to improve the BERT algorithm to understand voice search queries. Approximate 20% of Google searches are performed by voice. With BERT update, it gives more importance to voice search queries.
The keywords while typing are different from when they conduct a voice search. While conducting voice search people uses complete phrases, ask questions to get a particular answer. For SEO strategy, focus more on long-tail keyword phrases and questions that are relevant for your products and company.
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User-centric answers to input queries
Your content should be to the point, i.e. direct answers to the questions and informational search queries correspond to your service and product. For example, if a user searches for something then you should provide an accurate answer to the question with a featured snippet.
Google focuses on user’s queries. And Google wants to provide the most relevant results to the users as fast as possible. This is the reason why page speed is the most important factor. Develop an editorial calendar around particular questions and queries related to your services.
The main goal is to provide user-focused answers to the queries. When users search any query they don’t want to scan the entire page for a particular answer. So, the answer should be relevant to the query. Every person wants concise and high-quality content that provides a direct answer.
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Longer content is not always better
We think that if we use long content then it’ll be beneficial for our website ranking, but this thing is not true. According to the new BERT update, longer content doesn’t achieve a higher ranking. The length of the post will depend on the search query. For example, you have searched for “what is linking in html” it requires less content.
In the above screenshot, the first snippet shows the result and it contains only 400 words. If you search for “what is digital marketing” then it’ll contain vast content. To get higher ranking your content should concise and relevant to the search query.
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Use long-tail keywords
Google aims to provide relevant answers to the search query. Every algorithm updates strive to increase the relevancy of the results or answers they offer in search results. Google increases its ability to process natural language as well as it focuses on long-tail keywords.
While using long-tail keywords, suppose you want to search for “search engine” but in long-tail keywords, you would search like “top 10 search engines”, “internet search engines”, “list of search engines” or “types of search engines”.
These long-tail keywords are not only the terms which are searched by the people but they also have less competition as compared to basic keywords and easier to get a higher ranking.
People will pay attention to your services if you are providing accurate and specific answers to people for their long-tail search queries. You should provide high-quality content.
You should try to avoid using general or basic keywords. Particular long-tail keywords search queries get attention from customer’s side that is interested in your services.
Optimizing your blogging for BERT
If your website already offers high-quality content then BERT will not have a greater impact on your content marketing strategy. BERT is designed to provide a specific answer to search queries. Apart from this, if you are already using well-placed keywords in your blogs and you are producing blogs while keeping your target users in mind, so when Google engage traffic on your website, you provide relevant information according to the search query.
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Focus on keywords
You should focus on main keywords and include those in your blog posts because they still matter for your blog posts, avoid using those terms which can spoil the natural flow of the sentences.
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Improve your vocabulary
As we know BERT will look for those articles or posts which contain the synonyms of the queries. In other words, BERT will look for all alternatives and synonyms of the given query. You should use relevant language for keywords instead of using exact or same words again and again. In addition to this, if BERT shows the same article or post which users are searching for then it’ll be better for readers.
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Answer to search queries
After reading an article or post may your customers have a question about that article so try to answer those questions.
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Descriptive Queries
After BERT update, most of the websites hit with a 20% to 30% drop in their website traffic. BERT gives priority to those websites which provide a direct answer to the queries instead of long-form or navigational results.
In other words, BERT prefers those results which are concise and relevant to the search queries. If any content which doesn’t provide a direct answer or relevant answer then BERT is not going to give priority to that content.
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Include insight and inputs in the articles
To enhance the quality of the content, the insight and inputs provided by the experts should be included in the articles. This will provide more accurate information to users and offer authority to the content.
Optimizing for user intent will optimizing for BERT
Most of the website users ask a question “how to optimize for BERT?” and the answer is you can’t. BERT is an AI framework. Whatever it gets, it learns every new piece of information from that. The BERT’s developers can’t predict the choice of the decision made by BERT that at which rate BERT has made a decision. Even BERT doesn’t know why it has taken the decision if BERT doesn’t know SEO will not be able to optimize it directly.
You can rank in search pages by producing human-friendly content which provides an accurate and exact answer to the search query. The main objective of BERT is to help Google understand the user intent, so that’s why we have mentioned “optimizing for user intent will optimizing for BERT”. Here, we have mentioned three basic steps to optimize user intent:
- Continue with whatever you’ve been doing
- Research target keywords
- Focus on well-written content that fulfills the user intent
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