What Is NLP SEO? A Guide To Natural Language Processing In SEO

Remember the time when you had to re-phrase your Google searches again and again until you managed to find the information you were looking for?

From 2018 on, following the release of the BERT algorithm, things have changed. Today, it is Google that does the hard work for you.

So now, instead of re-wording your queries to elicit your ideal information, it is Google that matches your queries to the right search results.

And what’s more, you often get to find what you search for at the very top of the SERP list!

How does Google do that?

Well, it’s all based on semantic searches and the implementation of NLP (Natural Language Processing).

As Google search results become increasingly sophisticated, search engine optimizers are applying NLP SEO to maintain high rankings.

And it looks like this fairly new concept will be trending for years to come.

If you are wondering how to apply natural language processing in SEO, here’s a short guide to get you started.

What Is NLP (Natural Language Processing)?

Natural Language Processing (NLP) is a branch of AI (Artificial Intelligence) that allows computers to comprehend human speech and writing as a real person would.

Human speech goes far beyond words themselves.

Indeed, when we speak, many linguistic nuances are at play: The wording, syntax, and feel behind each sentence is understood by the other party based on their comprehension of the actual words, their general knowledge, and their real-world experience.

So, NLP brings together rule-based modeling of human language (computational linguistics) and statistical machine learning in order to understand human speech (or writing) in its entire meaning that embodies the speaker’s internet and sentiment.

What Is Google’s Natural Language Processing Good For?

By employing NLP, Google brings up surprisingly relevant results with diverse SERP features, allowing for further semantic match to queries.

Such features, like suggested searches, sitelinks, rich snippets, People Also Asked questions, image/video results, knowledge boxes, etc., help users find diverse sources that will best meet their search intent and also help refine vague or broad searches.

Example Of NLP-Based Queries

Semantics and NLP are by now fundamental in the Google algorithm.

For example, let’s take the word: bank.

By definition, a bank is a financial institution, a slope, and a river’s edge.

So, when you type in “bank” in Google search, are you going to get results for all 3 meanings?

Thankfully not.

To help users avoid scanning through a long list of search results, Google has identified that searchers looking for “bank” need to find a bank near them.

Think about it.

The truth is that if you looked for any information regarding a river’s bank or a slope, you would definitely add some other wording around it, like: ‘What is a bank slope?’ or ‘Which river bank is London?’

Hence, the results you get for the single-word query ‘bank’ bring up pages from various financial institutions, mainly from those with branches around your current location.

Let’s see another example of a multi-word search using the same term: bank.

Check out Google results for the query: ‘Let’s go to the bank’

This time, we get a variety of search results, as there’s no specific search intent for this query among U.S.-based searchers. That’s because Google can’t tell for sure what information you need.

As a result, by searching for ‘Let’s go to the bank,’ you might be looking for a song, a book, some Pokemon game insights, sociological information on why people still go to the bank, a coloring book, a Family Guy episode...

Βut looking for a financial institution is the least possible - according to Google’s algorithm.

What Is NLP In SEO?

Using NLP in SEO entails deciphering user intent and behavior and incorporating natural language processing practices in your search engine optimization process.

How Can You Implement Natural Language Processing In SEO?

To implement NLP for SEO, you must analyze search data with semantics in mind. You need to focus on intent, sentiment, named entities, readability (difficulty) level, and more.

With that in mind, let’s take a closer look at various things you can do to improve your NLP in SEO.

Focus On Search Intent In Your Keyword Research

Instead of merely looking for matching SEO keywords and keyword gaps, now, more than ever, you need to concentrate on the user search intent behind each query.

By incorporating intent-focused keywords in your content, you increase your chances of appearing for the right queries to your target audience.

Plus, a SERP analysis provides crucial data on what resources (images, videos, social...) Google considers intent-matching.

So, then, you can go ahead and try to match these resources in an SEO-friendly way.

Include Entities In Your Content

Entities are various elements on your page that help Google connect the dots and define which piece of content -out of millions out there- would be the best match for a specific query.

Google reads entities to disambiguate ideas - as it cannot rank all the sources that include similar information on the 1st page. According to the Search Engine Journal, “when Google tries to serve up results to a user search, it aims first and foremost for an accurate answer.”

In practice, entities include everything current SEO practices dictate: titles, meta-tags, images, schema markup, etc.

By optimizing all these elements to match your keywords and the search intent behind them, you have more chances to rank high for your desired queries.

SEO, NLP & Content Sentiment

To better shape your SEO for NLP, you must craft content with the sentiment it evokes in mind.

Yes, Google actually understands and takes into account the emotion of a piece of content to determine its ranking. Then, it categorizes it according to positive, negative, and neutral sentiments.

Positive sentiment ranks better than negative (thankfully!).

In fact, about 87% of all top 10 results invoke positive sentiment, compared to 12.03% with negative sentiment and a mere 0.26% with neutral sentiment.

So, to leverage your NLP SEO, try to include words like: “great,” “excellent,” “must read,” “hero,” etc., and minimize the use of negative words, for instance: “weak,” “fragile,” “boring,” or “danger.”

However, if your SERP analysis shows that top-ranking results are rather negative-centered, then you should shape your content accordingly.

Tip: Analyze the sentiment of the page titles that appear in SERPs for your branded queries. It can significantly help you boost your online reputation.

To take this further, you can also identify any ‘negative’ words that appear for your brand online and find ways to ‘combat’ them.

For example, you can use off-page SEO techniques and start a link-building campaign to strategically promote brand-positive results.

Internal And External Links For NLP SEO

With NLP SEO, internal and external links are pivotal. Consider them carefully and place them in a way that helps the reader and adds value to your piece.

To enhance your internal linking appeal, use anchor texts that include keywords related to a specific query. Like this, Google will see your content as more relevant and eventually list it higher.

On the other hand, external links to trustworthy sources indicate that your content is valid and well-researched.

Some best practices to follow for internal and external links include:

• Link to thematically related sources.
• Check the trustworthiness of your linked sources.
• Strategically place your links to enhance the flow of the text.
• Ensure an appropriate ratio of internal and external links within a text.
• Add the correct ‘link rel’ attribute.
• Select appropriate anchor text.

Once you get into it, NLP SEO presents countless opportunities for innovative improvements that can lead your way to the top (of SERPs).

Leverage Your Search Engine Optimization

Great SEO means following the latest Google trends - like NLP. At Atropos Digital, we do all the hard work for you.

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