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I have had the pleasure of working with many leading search engine optimization (SEO) specialists in my nearly decade-long career as an SEO expert. But one stood out for her ambitious goal to think like a human and a bot at the same time.
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 fundamentals of NLP, offering a simple analogy to how it works. I then focus on optimizing content using NLP in a way that both bots and your readers will love. Let's get started.
Related: How to Leverage AI to Boost Your SEO Efforts and Stay Ahead of the Competition
Fundamentals 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 literally thousands of search queries. And on the right side are search engines like Google, containing possibly the world's largest library of information accessible at one's fingertips.
So, how do people get their searches answered? The answer lies in algorithms. For example, Google's algorithms crawl millions of content pieces each 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.
Wondering how this is done? Basically, highly sophisticated computer systems take language found in sentences and break them down into words, phrases, symbols and other meaningful elements. This process is called tokenization.
There is also "stemming," which reduces words to their root form. Lemmatization, on the other hand, groups together different forms of a word that are then analyzed as a single unit. But there's more.
Other ways NLP kicks into high gear include through syntax analysis, named entity recognition, sentiment analysis, topic segmentation and others. And to add a cherry on top, NLP also carries out tasks that include speech-to-text recognition, grammatical tagging, disambiguation, coreference resolution and others.
With so much intelligence and sophistication in NLP, it's becoming clearer that SEO experts need to rethink their strategies for optimizing content. 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 complexities of the BERT algorithm rollout or the statistical measure called frequency-inverse document frequency (TF-IDF), if there's one thing you will want to walk away from knowing, it is that catering to user intent on Google has never been this important.
Gone are the days of happily stuffing keywords to get a high keyword density score just to boost the rankings of your content. Today, Google is much smarter and is prioritizing the user experience over anything else.
That's why its NLP technology is so sophisticated and is worth paying attention to. Therefore, whether you're aiming to revive your content strategy or embark on a totally new route, 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 to keyword research. Firstly, I need to mention that comprehensive keyword research should be the backbone of your content optimization efforts.
Without quality keywords, you risk your content piece never seeing daylight on the first page of the search engine results. Secondly, you need to identify relevant, high-traffic keywords which are accompanied by an in-depth user intent analysis.
To achieve all this, you need NLP-powered tools to streamline your keyword research process. While the choice of tool is up to you, ensure you make the right investment because this will pay off in the long run.
Related: How AI Is Transforming Keyword Research (and Why You Can't Afford to Ignore It)
Optimizing content with NLP
A few 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 structuring in your content with appropriate H1s, H2s, H3s and bullet points or numbering to match the user's journey. Add semantically related keywords in your text, ensuring they flow naturally. However, keep the use of stop words in SEO to a minimum.
Write short and unambiguous sentences with each sentence conveying one main idea. Avoid jargon and colloquial language. Lastly, get to the point by providing answers to questions quickly, followed by indicating the subtle nuances in your answers in more detail later.
Measuring NLP-driven content performance
Every SEO expert worth their salt knows that measuring content performance is a big deal. Ignoring the metrics is done at your own peril. Constantly monitoring your metrics is critical for your content optimization success.
That's because they allow you to refine and tweak the 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, a couple of metrics you will want to keep an eye on are:
Search engine results rankings
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 assist us with our content optimization through the power of NLP. It's as simple as creating a new project and typing in your primary keyword. Once you've 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 your meta title and description, either manually or through the help of AI magic. Once you've taken these steps, you'll be taken to a screen where you can paste in your blog article. You'll get a numerical score for your article's current performance.
You'll also see which keywords you should include naturally in your text so that you boost your score, outperforming the highest-performing article for this keyword. By using NeuronWriter, we managed to drive organic traffic up to 49,000 in the space of just six months, while incorporating 1,623 keywords.
Another article that performed well during the same period saw traffic of 16,020 with 8,082 keywords.
Future trends in NLP-powered content optimization
A few trends that I foresee taking center stage with NLP in the near future must be mentioned, too. Among the prominent ones that will make a splash in the world of SEO are:
Optimization for mobile searches
Catering to voice search queries which usually use long-tail keywords
Using generative AI
Data and insight-driven strategies
Hyper-personalized content
Ultimately, 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 get smarter and more effective at understanding the nuances of human language, you'll need to stay at the very top of your SEO and content game to make a mark in the industry.
