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Dec 27, 2022

How Natural Language Processing Is Changing SEO in 2022

Image of Saurabh Wadhawan, Co-founder
Saurabh Wadhawan
How Natural Language Processing Is Changing SEO in 2022

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We live in the world of search. 

From nail cutters to home renovation experts, you can find everything online. You can type or talk about what you want to know, and search engines will find that information. 

With the help of advanced artificial intelligence technologies like NLP, search engines like Google, Yahoo, and Bing are introducing new features like voice search. In a way, they are creating even more opportunities for marketers to get in front of their target audience with quality content. 

NLP improves their understanding of search queries and helps them produce better search results. It is also applied to crawling and indexing your websites better. This technology helps search engines understand the content on a webpage just like a reader would. 

As a marketer, you need to know about these technologies to improve your SEO and content marketing results. 

In this blog, we will dive into the world of NLP and understand how this technology is changing the search engine optimization game forever. 

What is NLP and how does it work? 

Natural Language Processing (NLP) is a linguistic data analysis technique that allows computer programs to understand the meaning of words with respect to their use in sentences. It enables search engines to understand the content and gauge the quality of information. 

Before NLP, black-hat SEO techniques like keyword stuffing made it hard for great content to rank higher and get the organic traffic it deserved. 

However, with the help of NLP, search engines like Google can now easily identify what is good content and what is just a lot of keywords stuffed into content to make the page rank. NLP employs a few important processes to analyze content. Let’s take a look at three key processes. 

  • Syntax Analysis

Syntax analysis refers to the process of analyzing words, phrases, and sentences in the order they occur in your content. Search engines use this to understand the meaning and relevance of entire paragraphs without the need to look for keywords. Good content will always rank higher on search engines that use NLP syntax analysis to index and crawl websites. 

  • Sentiment Analysis

Every piece of content has a sentiment around the central topic. It could be positively talking about the topic, it could highlight the pitfalls of a specific topic, or it could just be trying to explain the concept neutrally. 

Sentiment analysis is a part of natural language processing that helps search engine algorithms figure out how people really feel about something. Sentiment analysis helps search engines give users the most helpful search results. Usually, sentiment is measured on a scale from 1 to -1, where 1 is very positive, and -1 indicates very negative sentiment. 

  • Entity Recognition

Entity recognition is another NLP process that helps search engines identify the important words in a sentence or phrase. It helps them better categorize different pieces of content based on the central subject of the content. 

If you’re publishing a blog post on different types of products, it will identify that and only show your webpage when a user searches for product options. 

Understanding Google’s BERT and its impact on SEO 

In 2019, Google released a major breakthrough in the search engine world, BERT or Bidirectional Encoder Representative Transformers.

This update helped Google enhance its understanding of the information on the internet and the search queries that users enter while searching for information. 

The special thing about BERT is that it does away with the conventional method of analyzing words one by one. With BERT, Google analyzes words in relation to all the other words in a sentence. This helps Google's algorithms understand the search intent behind queries. 

Screenshot of how BERT impacts search results
Source

As you can see, before the BERT update, Google would produce a result of US citizens traveling to Brazil. In contrast, after the update, it can understand the context of the search term and produce results that show information about Brazilian citizens traveling to the US. This ensures a better user experience.

Want to look at more NLP examples? Refer to this detailed Scalenut blog, ‘12 Real-World Examples of Natural Language Processing (NLP) In Action.’

In the meantime, let’s look at what goes in the background of NLP-based search engine algorithms.  

  • Entity, Category, and Salience

Google’s algorithm analyzes a search query for the entities in it and categorizes them into different groups, such as place, person, company, process, etc. It then scores every entity based on the importance it carries in a search query. That is called salience. 

When you enter a search query, Google follows this process to determine which words are the most important and what category of content is best suited for it. 

  • Sentiment analysis for SEO

The other part of BERT that every SEO professional should know about is sentiment analysis. BERT uses this process to understand the emotions behind a searcher's query, user-generated content, and the content on websites. 

If the general feeling behind a search is positive, Google will rank content with a positive meaning higher to give the most relevant search results. 

How NLP is impacting search engine optimization (SEO) 

NLP is changing the SEO game forever. We can never go back to the old methods of creating keyword-focused content. Marketers and SEO experts must be aware of this and create content that truly helps users. 

The following are a few major changes that you should consider while creating your next campaign:

  1. More focus on search intent 

Following the BERT update, search intent has taken center stage. Every search query is first analyzed for the intent of the user, and then Google produces a search result that will best answer their questions. 

It's important to think about what people are looking for when they search for the keywords you use in your content strategy. If your content does not serve the purpose of a user’s search, it is likely to rank lower than others. 

  1. Use of term frequency-inverse document frequency 

Term frequency-inverse document frequency (TF-IDF) is a new concept introduced by the Google BERT algorithm. TF-IDF increases based on the number of times a search query appears in your content and decreases based on the number of documents that have the same word. 

This means that common words such as “a,” “an,” “what,” “how,” and “the” are not considered while ranking websites in search results. It works by multiplying two metrics —

  • Term Frequency: A count of the number of occurrences of a word in the content in relation to the overall length of the document. 
  • Inverse Document Frequency: This is measured as the ratio of the total number of documents divided by the total number of documents that have the keyword. If the keyword is very common, the score is close to 0, and if the keyword is not common, it is close to 1. 

The TF-IDF score is the multiplication of both of these measures. A keyword with a high TF-IDF is considered highly relevant. These are high-value words that can help you increase the visibility of your blogs, landing pages, and other marketing campaigns. 

Want to know more about TF-IDF and how you can use this metric for keyword research? Check out this helpful Scalenut blog, ‘TF-IDF SEO Optimization: A Guide For Content Marketers.’

  1. Sentiment analysis is important 

As NLP enables search engines to determine how people feel when they enter a search query, you must ensure that your content conveys the same sentiment. It should match their feelings and help them find the most relevant information for their searches.

Search engines like Google are continuously analyzing the sentiment of internet users behind brands, products, and services. Therefore, as a marketer, you must manage a positive online presence.  

  1. Focus on “anchor text” and “interlinking” 

Anchor texts that make sense for the page they link to are more important than ever. If your anchor text says “the best free tools,” the source webpage must have a list of the best free tools in its content. 

We should ensure that we use the same anchor text every time we interlink a web page for the website. This will help establish a relationship between the keywords in your anchor text and the blog that you link to. It will tell search engines like Google what your blog is about and which keywords best represent its content. Consider this an in-house link-building practice.  

  1. Pay attention to salience and category

Google's BERT update has helped the world's biggest search engine make sure it knows how important each word in a search query is. It helps the Google search engine establish relationships between different words on a webpage and the keywords it targets. 

For marketers, the salience score of keywords will help them prioritize terms you use in your content. For example, if you are creating a piece of content about the ‘benefits of green tea,’ your content should be focused on the benefits. Simply mentioning the benefits in a small paragraph won’t be enough. 

NLP searches work differently than conventional searches. If you want to know more about the nitty-gritty of NLP search, you may find this blog, ‘Natural Language Searches: The Secret Behind Search Engines,’ helpful. 

NLP techniques you can use to optimize your content for SEO

Now you have a fair understanding of the different aspects of NLP and their impact on search engine optimization techniques. Let’s look at some of the most effective ways to create NLP-optimized content for your website. 

  1. Provide direct answers to customer queries

Search engine crawlers understand the relationship between words and the importance of each word in a search term. So when creating Q&A content for your blogs, always answer the questions directly without straying away from the central topic. Users looking for answers do not want to read a lot of content before they get to the actual answer. 

  1. Avoid industry-specific jargon, write in simple language 

The goal of every piece of content should be to explain difficult concepts in the most simple terms. Refrain from using a lot of industry jargon in your content. If you want to talk about a complex topic, break it down into smaller parts and explain it in plain language that a normal user can understand. 

  1. Make sure your writing is grammatically correct

With the knowledge of the importance of prepositions, articles, and grammar, NLP-based search engine algorithms are very picky when considering webpages for search results. 

Your content needs to be free of grammatical errors. Ensure that every piece of content you publish is correct and well-phrased for better understanding.

  1. Focus on readability and convey one idea per sentence 

One downside of NLP is that it is yet to reach a stage in its evolution where it can understand complex sentences with more than one thought. A piece of content with a lot of complex sentences will not be able to rank high even if it explains the keyword topic in detail. 

While creating content, ensure you include only one idea per sentence. Make it simple for search engines and users to understand your content, and it will start ranking in no time. 

  1. Check for factual accuracy 

Whatever you publish, always double-check for accuracy. If you are claiming a statistic, ensure it is sourced from credible websites. Google evaluates the quality of content based on the accuracy of the information. 

Natural Language Processing is humanizing the SEO industry. Marketers that want to leverage this technology for better results need to adapt their content strategy to address the most important needs of their target audience. 

Scalenut can help you with SEO-friendly content

Wondering how you can identify NLP search terms for your next content piece? 

Look no further. 

Scalenut is a one-stop shop for everything you need. 

This all-in-one content and SEO platform allows you to analyze search trends and competitor websites for the NLP terms they use, as well as create content with those terms.

All you have to do is enter your target keyword, select the target location, and create an SEO report. Scalenut will give you a detailed report on the top-ranking content on the internet for your keyword. 

You will get useful insights for your SEO strategy, such as their outline, word length, number of images, list of NLP terms, and the content grade of those web pages. Once you have created an outline for yourself, you can create amazing content with our AI-enabled content editor. 

About Scalenut 

Scalenut is an all-in-one SEO and content marketing platform that is powered by AI and helps marketers all over the world make high-quality, competitive content at scale. From research, planning, and outlines to ensuring quality, Scalenut enables you to achieve the best in everything. 

Empower your content marketing campaigns with AI. Sign up on Scalenut, and start creating content today.

Saurabh Wadhawan
Co-founder
ABout the AUTHOR
Saurabh Wadhawan
Co-founder

Saurabh is the Co-Founder of Scalenut. He is a technology veteran with over a decade of experinece in product development. He is the co-captain of the ship, steering product strategy, development, and management at Scalenut. His goal is to build a platform that can be used by organizations of all sizes and domains across borders.

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