How Natural Language Processing affects SEO, businesses and media

By Rudi Davis Published: 22 September, 2020 Last updated: February 17th, 2022 at 1:45 pm

a screen full of code and a picture of ahuman

Natural language processing (NLP) is a cornerstone of AI, with programs like Siri and Alexa becoming the crucial link between us and the technology we use. 

NLP develops computers to understand natural language in order to enhance the communication between humans and machines. This is done through AI technologies such as voice recognition, machine translation, and sentiment analysis, just to name a few. 

These NLP technologies are evolving faster than any other field in machine learning and present endless opportunities for businesses.

To understand what the NLP engines are capable of, a study at MIT that looked into the way neural networks are trained provides a great example of the level of detail achieved in machine translation.

So what does this NLP progress mean for SEO, businesses and media?


The recent algorithm updates such as Google BERT in 2018 that enhanced the use of NLP in its search engine results has become the focus of various SEO advice articles.

BERT has made Google understand the websites more accurately than ever and SEOs are now rushing to optimise their content for different nlp technologies such as voice search queries.

The biggest change this evolution of speech recognition has made in SEO is that target search terms have moved towards more conversational long-tail keywords incorporated with natural language.

Syntax analysis is another way NLP affects SEO. It recognizes whether your piece of content is well-written, both in terms of topic and grammar, or stuffed with keywords.

NLP also has entity recognition which recognizes whether your images and videos are relevant to your content, even without ALT texts. So tricking the search engines is getting harder and those who still are using short-lived SEO hacks over quality content it’s high time to change their strategy.

NLP and customer service

The fast NLP development has improved customer service and even increased sales with more personalized and humanized chatbots and more effective customer feedback analysis.

Digital consultancy Rain began working with companies to develop apps for Amazon’s Echo products which break down customer feedback to inform future product developments. Greg Hedges, VP of emerging experiences at Rain, told AdWeek, “If [laundry detergent manufacturer] Tide learns someone is asking about a specific stain and fabric combination, and it’s not one they’ve encountered before, maybe a new product comes out of that. With voice, it’s almost like a focus group of one.”

The ability for NLP to reliably deliver accurate results means that such search engines can, by corollary, identify where they don’t have the information being requested. As such the degree of accuracy can be used to highlight flaws in databases which can then be filled, further spurring development.

The sentiment analysis, NLP AI that extracts data from topics being discussed and determines whether that data is negative or positive is one of the most significant ways NLP has improved customer service. It can detect and directly respond to negative customer feedback and protect your brand reputation.


We can talk of the ability of AI machines to digest information and form short articles which deliver news. While this happens to a certain extent, NLP functionality is still a long way from being able to replace journalists.

However, what is becoming more of a possibility is the potential for search engines to understand what a journalist is interested in depending on what they’re writing about and searching for. Not only does this fit with Google’s ability to assign categories and sentiments to articles through NPL engines, but it introduces the ability for adverts to be presented alongside relevant content.

In theory, this could improve the ability of media outlets to drive revenue through their content, potentially saving an industry currently in crisis.

Final thoughts

NLP technologies are already affecting our daily lives every time we make a search query, use Google Translate or talk to a ChatBot. But these are just a few examples of what natural language processing can do.

The future possibilities with NLP are endless.

All these AI technologies are only going to become more accurate and predominant in the future. Therefore, it’s important to stay aware of the development of NLP, finding ways to leverage it for your business and adapt to the changes it’s ushering.