Natural Language Processing (NPL) is something SEOs need to get an understanding of quickly as it’s becoming an essential part of how content is understood and ranked organically. Search engines like Google are continuously increasing their reliance on NLP to understand the intent behind searches so they can be better equipped to serve up the best and most helpful results to its users.
NLP is going to drive a lot of the changes SEOs need to think about when creating content, structuring site architecture, user intent, and more.
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What is NLP (Natural Language Processing) in SEO?
Natural language processing is a branch of linguistics and artificial intelligence that bridges the gap between computers and human language. This involves teaching computers and machines to interpret and generate useful and meaningful responses in human language.
Put simply, NLP gives computers the power to process and analyze large amounts of data and text by extracting necessary insights and generating something a human can use and interpret without the need for follow-up questioning.
How Does NLP Work?
While natural language processing is a complex topic, we can break it down using a few different steps. The entire process involves many different techniques and algorithms to bridge the gap between human language and machine understanding. The infographic below summarizes and simplifies these steps:
A deeper breakdown of the process reveals a little more of what’s going on under the hood of the NLP car. There are specific actions that have to take place before a response is generated, most of which happen within seconds. Here’s a breakdown of some of the steps happening when search engines are using natural language processing:
- Text/Audio Preprocessing: Text processing involves tokenization, breaking down text into individual words and removal of common words like “the”, “and,” “is” or words that don’t add meaning to the request. During this process, the machine will tag parts of the speech to identify the role of important words to improve its understanding.
- Feature Extractions: Feature extraction represents the conversion of text and audio data into numeric data that computers can easily understand. Some machine techniques included in this stage are TF-IDF (Term Frequency-Inverse Document Frequency) and word embeddings like Word2Vec or GloVe.
- Machine Learning Models: The machine learning model stage applies common processing models so the machine can understand and process the data more accurately. Some of the models include:
- Naive Bayes: Classification tasks like sentiment analysis.
- Support Vector Machine (SVM): Text classification and categorization.
- Hidden Markov Model (HMM): Speech recognition.
- Deep Learning: This includes Recurrent Neural Networks (RNNs), Long Short Term Memory (LSTM), and Transformers (BERT) used for translation, text generation and question answering.
- Natural Language Understanding (NLU): This step extracts meaning and intent from the text the machine has already converted. This includes entity recognition and relationship understanding.
- Natural Language Generation (NLG): The final step is to create human-like text based on the data the machine was able to gather, convert, and understand.
6 Ways To Use NLP for Modern SEO
1. Focus On Search Intent
The natural language understanding (NLU) portion of the language processing steps is arguably the most important. Search engines crave understanding, this is why structured data has been on the rise for some time now. The more clarity a search engine has on the concepts and text you include in an article or with your voice, the better they can formulate a response.
2. Write For Clarity
Step out of the content brief for a second and write your blog post like you’re talking with your best friend. Too often SEOs are sucked into the black hole of content briefs, SEO alignment, and self-consciousness about what Google will think about their writing. Since the introduction and widespread use of AI-generated content, REAL content writing has never been more valuable.
Even as you’re reading this, you can tell that it’s not AI-written. Clarity is the most important part of communication. We need to focus more on how people learn and understand the concepts we chose to write about in the name of generating more organic traffic.
7 Tips for Writing For Clarity
- Avoid complex sentences.
- Vary sentence length.
- Use an active voice.
- Use precise language instead of vague or jargon terms.
- Choose strong verbs to convey meaning.
- Break up long blocks of paragraphs into bite-sized chunks.
- Maintain a consistent tone throughout your writing
3. Include Related Entities
Related entities are critical for improving your NLP SEO. Including relevant entities in your content helps search engines get a better understanding of the context and depth of your content.
Including entities helps search engines to categorize your content in the right section so it can match it to relevant searches. Covering a topic holistically means including entities. It not only helps with categorization, but it also demonstrates expertise on the subject. Including entities means that you understand how concepts are connected and what information is needed to deliver a comprehensive understanding to the user.
Entities usually carry their own value from a keyword perspective too. Related entities are often long-tailed keywords that help expand the reach of your content, assist in answer engine recognition and can attract more targeted traffic. All of these things lead up to more engaged users who are more likely to stick around and learn, improving session duration and the likelihood of conversion.
4. Double Down on Semantic Keyword Inclusion
On a similar thread, semantic keyword inclusion improves a search engine’s understanding of your topic. In the old days of SEO where a targeted keyword in an H1 and title tag would get you to the top of search results, semantic SEO was just another way of expanding your organic visibility and showing your expertise.
As the awareness for NLP SEO becomes more prevalent, focusing your efforts on semantic keyword inclusion give you a competitive advantage and set your content apart from the competition. It’s important to remember that you don’t want to overuse or insert these keywords where they don’t naturally flow with the rest of the content. The focus should remain on creating high-quality content that informs the user and genuinely answers their questions.
5. Use Question-Answer Formats
Question-answer format is a great way to quickly educate users on a concept while also ensuring complete coverage of a topic. Providing question-answer formatted content in your marketing efforts can help search engines get a better view of your own understanding of the concepts you’re talking about.
Not only is the question-answer format good to include for NLP SEO, it’s also a good way to get listed in AI summary searches or AEO. Answer engine is a key component to NLP. With the release of Google’s AI summary search function, more SEOs are focused and attempting to reverse-engineer ways of getting listed in high-visibility search areas.
6. Intentionally Structure Your Content
The content throughout your post is obviously the meat and potatoes on the plate. The vegetables are how you structure the content. You want to make sure you’re providing a pathway for the user to digest the information. If you’re writing a blog post about, I don’t know, let’s say ‘natural language processing’. You’ll want to start off by first defining the concept, talk about how it works, and then get into techniques and tactics.
Content structure also assists with user engagement metrics. If you have a barrier for information retention, it’s going to be how your content is structured and how it looks. Give the user what they want and when they need it. If information is needed to understand deeper concepts throughout your content, make sure to lead with that information.
Keep It Natural
Creating content for natural language processing should be, well, natural. You don’t want to try to complicate things with industry jargon. You want to create a connection between you and the user. Make them feel like they’re talking to a friend. This will not only help you engage more users, but search engines like Google are more likely to understand and choose to serve your content in key ranking areas like featured snippets, AI search summaries and rich results.
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