What Is NLP?


Natural language processing (NLP) is a type of artificial intelligence (AI) that helps computers understand, interpret, and interact with language. And involves processing and analyzing large amounts of natural language data.

In SEO, NLP is used to analyze context and patterns in language to understand words’ meanings and relationships.

This helps search engines better understand what users are looking for (i.e., search intent) when they search a given term. And deliver relevant results.

For example, Google uses NLP to help it understand that a search for “aluminum bats” is referring to baseball clubs. Not winged animals.

And it shows search results that demonstrate this understanding.

NLP also plays a crucial role in Google results like featured snippets. And allows the search engine to extract precise information from webpages to directly answer user questions.

All this ultimately enhances searchers’ experiences. And ensures websites can effectively reach those searchers.

How Does NLP Work?


Natural language processing integrates machine learning, linguistics, and AI to help machines understand and process human language.

Generally speaking, NLP involves gathering unstructured data, preparing the data, selecting and training a model, testing the model, and deploying the model.

Here’s an overview of some of the main concepts involved:

• Tokenization: Breaking down text into smaller units (like words or sentences)
• Stemming and lemmatization: Converting words into their root forms 
• Part-of-speech tagging: Assigning a grammatical category to each word (i.e., noun, verb, adjective)
• Named entity recognition: Identifying entities like names, dates, and locations within the text
• Dependency parsing: Analyzing the grammatical relationships between words in a sentence to understand its structure
• Semantic analysis: Extracting the meaning of the text considering factors like context, synonyms, and antonyms

In 2019, Google’s work in this space resulted in Bidirectional Encoder Representations from Transformers (BERT) models that were applied to search. Which led to a significant advancement in understanding search intentions.

As a result, modern search results are based on the true meaning of the query. 

This means content creators now need to produce high-quality, relevant content. Not just content that exactly matches certain words. 

Examples of How Google Uses NLP in Search

Here are some of the main ways Google applies NLP to search and search results:

Identifying the Meaning of Queries and Pages

Google introduced its neural matching system to better understand how search queries are related to pages—even when different terminology is used between the two.

For example, the query “eating based on what your body wants” describes a concept called intuitive eating. But searchers may not be familiar with that phrasing.

Google recognizes that and serves results accordingly:

You can probably see why Google’s Danny Sullivan referred to it as “super synonyms.”

Recognizing Entities

Entities are items like people, places, and things. And Google’s search algorithms work to determine whether a user is trying to find information about an entity.

If so, Google can extract relevant information from reliable content and display it in results. And possibly in a knowledge panel—a type of rich result that appears to the side of standard search results. 

Like this:

Notice that the user doesn’t even need to know the exact name of the entity to find what they’re looking for.

Providing More Direct Answers

Google’s NLP and other systems decide when generative responses would be helpful for a particular query. And when they are, excerpts are written using AI technology that draws on the Gemini language model.

These AI-generated summaries appear above all other search results. 

They’re intended to help searchers find the information they need without having to sift through multiple webpages. But also include links to the content the summaries are sourced from.

How to Optimize Your Content with NLP in Mind

You can significantly increase your chances of performing well in search by considering the way search engines use NLP as you create content.

Here’s how:

1. Analyze Search Intent


Search intent is the purpose behind a user’s search query. And understanding it is crucial for creating content that meets users’ needs and ranks well in search results.

These are the four main types of search intent:

Use Semrush’s Keyword Overview to effectively analyze search intent for any keyword you’re creating content for. 

Enter your target keyword and click “Search.”

You’ll see the “Intent” metric near the top.

Semrush estimates the intent based on the words within the keyword that signal intention, whether the keyword is branded, and the SERP features the keyword ranks for.

Once you have a general understanding of intent, analyze the search engine results page (SERP) and study the content you see. 

To do that, scroll down to the “SERP Analysis” section and click “View SERP” to see the actual search results.

This gives you a better overview of what the SERP looks like for your target keyword. To help you more fully understand what searchers are interested in.

Next, visit the top-ranking pages to find out:

• How do these pages structure the content? And what topics are covered?
• What content types and formats are used? Are the results blog posts, product pages, or something else? 
• How is your target keyword used? And how does that help you better understand the context behind user queries?
• What common themes and questions do these pages address? And how can you use this information to guide your own content creation? 

By understanding the answers to these questions, you can tailor your content to better match what users are searching for. 

2. Answer Your Audience’s Questions

Users often search keywords that are formatted as questions. And there are likely several that are relevant to your main keyword. 

That means answering these questions can help you gain more visibility. And have your content appear in featured snippets, AI Overviews, and People Also Ask (PAA) sections.

Like this:

Use the Keyword Magic Tool to find common questions related to your topic. 

Enter your target keyword in the text field. Then, select the location and click “Search.”

Next, select the “Questions” tab. 

Now, you’ll have a list of question terms that are relevant to your target keyword. 

You can further narrow down your list by filtering these keywords based on relevant SERP features. 

Click the “Advanced filters” drop-down, select the “Any” drop-down under “SERP Features,” and tick the boxes next to any SERP features you want to focus on.

This way, you can identify question-based keywords that are relevant to your topic. So you can include them and their answers in your content. 

When crafting your answers, it’s a good idea to take inspiration from the answer currently appearing for those questions. Which might mean using bullet points, numbered lists, etc. 

3. Include Entities in Your Content

Incorporating entities in your content signals to search engines that your content is relevant to certain queries. Which can improve your SEO performance. 

For example, if you’re writing a travel blog focused on planning a trip to Paris, it’s a good idea to mention entities like “Eiffel Tower,” “Louvre Museum,” and “Palace of Versailles.”

Keyword research often uncovers some relevant entities.

Find even more (as well as some additional semantic keywords) using the SEO Content Template.

Enter your main keyword. And click the “Create content template” button.

The tool will offer recommendations for terms (including entities) based on the top-ranking pages for your target keyword. 

Like this:

But don’t go overboard. Because it might look forced or over-optimized for search. 

Instead, aim for a smooth and informative piece.

4. Write Using Clear Language


Use simple words and clear sentences in your content. To help both Google and users grasp your content more easily.

Consider these examples:

Here are some tips for simplifying complex ideas:


• Break long sentences into shorter ones
• Use common words instead of jargon
• Focus on clarity and brevity

Further reading: 

5. Organize Your Information Under Relevant Headings


Headings help organize your content and improve readability. Which helps search engines (and users) better understand your content. 

So, group related information under clear heading tags—HTML elements ranging from H1 to H6. To break down your content into scannable blocks.

Like this:

Follow these tips to use headings effectively:

• Align your headings and subheadings with search intent
• Make sure each heading accurately reflects the content it introduces
• Use concise and descriptive headings 
• Maintain a logical hierarchy—H1 for the main title, H2 for main sections, H3 for subsections, and so on
• Include target keywords naturally within headings and subheadings when possible

To see whether you have any existing issues with your website’s H1 tags, use the Site Audit tool. 

Launch the tool, enter your website, and click the “Create project” button.

Follow the configuration instructions to set up your website audit.

Once you’re ready, click “Start Site Audit.”

You’ll see a dashboard once the audit is complete. Which shows an overview of your site’s health.

Click the “Issues” tab to see a list of problems found on your website. Categorized as “Errors,” “Warnings,” and “Notices.”

Apply the “Meta tags” filter to see issues related to H1 tags.

Click “Why and how to fix it” next to the highlighted issue. To learn more about the issues and ways to fix it. 

And follow the tips to resolve the problem.

Craft Your SEO Strategy with NLP in Mind

Understanding NLP principles helps you create content that will likely perform better in search results.

And Semrush’s suite of SEO tools can help you.

Start by creating your free Semrush account today.