How natural language processing can transform your content strategy

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I have had the pleasure of working with many executives search engine optimization (SEO) specialists in my nearly ten-year career as an SEO expert. But one stood out for its ambitious goal to think like a human and a bot at the same time.

By sharing this philosophy, this is something I admit to doing myself. Why? Because advances in natural language processing (NLP) require a forward-thinking approach to content optimization.

In this article, I dive into some of the key basics of NLP, providing a simple analogy of how it works. Then I focus on optimizing your content using NLP in a way that both bots and your readers will love. Let's begin.

Basics of NLP

At the risk of oversimplifying, imagine a bridge over a river connecting two pieces of land. On the left side are people with thousands of search queries. And on the right hand side are search engines like Google, which contain perhaps the world's largest library of information accessible at your fingertips.

So how do people get their searches answered? The answer lies in algorithms. For example, Google's algorithms crawl millions of pieces of content every day and organize and structure them to meet search queries.

But where does NLP fit into the picture? As part of artificial intelligence (AI) and machine learning, it bridges the gap between real people's search queries and what search engines have to offer.

I wonder how this is done? Basically, highly sophisticated computer systems take the language found in sentences and break it down into words, phrases, symbols, and other meaningful elements. This process is called tokenization.

There is also “growth”, which reduces words to their root form. Lemmatization, on the other hand, groups different forms of a word that are then analyzed as a single unit. But there is more.

Other ways that NLP gets up to speed include through syntactic analysis, named entity recognition, sentiment analysis, topic segmentation, and more. And to add a cherry on top, NLP also performs tasks that include word recognition in the textgrammar tagging, parsing, proofreading and more.

With so much intelligence and sophistication in NLP, it's becoming increasingly clear that SEO experts need to rethink their content optimization strategies. Today, this task is as much about enabling bots to semantically understand content as it is about understanding the user's intent behind a search query.

While I won't go into the intricacies of how the BERT algorithm works or the statistical measure called the Inverse Document Frequency (TF-IDF), if there's one thing you'll want to walk away from knowing, it's that food user intent on Google it has never been so important.

Gone are the days of happily stuffing keywords to get a high keyword density score just to increase the ranking of your content. Today, Google is much smarter and is prioritizing user experience above everything else.

This is why its NLP technology is so sophisticated and worth paying attention to. Therefore, whether you're looking to revive your content strategy or start down an entirely new path, you can't afford to ignore NLP.

Applying NLP to keyword research

Having covered the importance of NLP, let's explore some ways in which you can apply it keyword research. First, I should mention that comprehensive keyword research should be the backbone of your content optimization efforts.

Without quality keywords, you risk your piece of content never seeing the light of day on the first page of search engine results. Second, you need to identify relevant, high-traffic keywords that are accompanied by an in-depth analysis of user intent.

To achieve all this, you need NLP-powered tools to streamline your keyword research process. While the choice of tool is up to you, make sure you make the right investment because it will pay off in the long run.

Content Optimization with NLP

Some tips worth sharing when optimizing content with NLP tools include the following:

Use it for both content ideation and generation
Optimize your content structure and flow based on NLP insights
Refine content for improved readability and engagement

To do this, focus on creating keyword-rich, but not keyword-stuffed, metadata. Use the right structure in your content with H1, H2, H3 and appropriate bullets or numbering to match the user journey. Add semantically related keywords to your text, making sure they flow naturally. However, keep using the ban words in SEO at a minimum.

Write short, concise sentences with each sentence conveying a main idea. Avoid jargon and colloquial language. Finally, get to the point by answering the questions quickly, followed by showing the subtle nuances in your answers in more detail later.

Measuring the performance of NLP-driven content

Any SEO expert worth their salt knows that measuring content performance is a big deal. Ignoring metrics is done at your own risk. CONTINUALLY monitoring your measurements is critical to your content optimization success.

That's because they allow you to refine and adjust content based on user engagement and data for even better results. To better understand and improve your users' experience with your content after applying NLP strategies to it, some metrics you'll want to keep an eye on are:

Search engine results ranking
Website traffic
User behavior data such as time on page, conversions, etc.

Case study — boosting SEO with NLP

At InBound Blogging, we use NeuronWriter to help us with content optimization through the power of NLP. It's as simple as creating a new project and typing in the main keyword. Once you have done this, you can select a list of top ranking competitors whose keywords will be extracted and which you can use in your article.

There are options to optimize yours title and meta descriptioneither manually or with the help of AI magic. After taking these steps, you will be taken to a screen where you can paste in your blog article. You will receive a numerical score for the actual performance of your article.

You will also see which keywords you should naturally include in your text in order to increase your score, surpassing the highest performing article for this keyword. Using NeuronWriter, we were able to drive organic traffic up to 49,000 in the space of just six months, covering 1,623 keywords.

Another article that performed well during the same period saw a traffic of 16,020 with 8,082 keywords.

Future trends in NLP-powered content optimization

Also worth mentioning are a few trends that I foresee taking center stage with NLP in the near future. Among the most prominent ones that will make waves in the SEO world are:

Optimizing for mobile searches
Catering to voice search queries which typically use long-tail keywords
Using Generative AI
Data and knowledge driven strategies
Hyper-personalized content

After all, if you're in SEO, you constantly need to stay ahead of the curve with NLP adoption and refinement.

If you haven't tried using NLP-driven tools and techniques to optimize your content, I strongly encourage you to do so. NLP is powerful, and as Google's algorithms become smarter and more effective at understanding the nuances of human language, you'll need to stay on top of your SEO and content game to make a mark in the industry.

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