What is Natural Language Processing and Search?

What is Natural Language Processing and Search

Put simply, Natural Language Processing (NLP) is phrasing a search query just as you would if you were talking to an actual person, rather than Google.

The introduction of this algorithm update into Google search means users now have the ability to search with natural language since Google doesn’t fully rely on keywords to determine what content to deliver.

How Does Natural Language Processing Work?

Searchers no longer need to search for the exact keyword to find what we want. We can ask long, multi-part or even downright wacky questions and still expect to find what we’re after on the first try.

Whereas we might have previously search for “natural language search explanation”, if we were to search for “what is natural language?” we can expect to still find the same, if not better, results. Users are increasingly using conversational language in their searches.

What is Natural Language Search?

The conversational nature of voice recognition technology from voice assistants such as Alexa and Siri lends itself perfectly to natural language search. Google states that, 70% of Google Assistant voice queries are made in everyday language.

NLP can analyse the syntax of a page to better understand sentences and the context of specific phrases. Additionally, Google uses artificial intelligence and machine learning to able to determine whether a piece of content is well written — from a topic perspective as well as a grammar standpoint.

How Can We Utilise This?

We can start by brainstorming the type of questions a person would ask if they were to meet you face-to-face. Tools like Answerthepublic.com can help to flesh out this list further.  For best results, build your long-tail keywords around “what,” “how to,” “how,” “when”, “who”, “where” and “why” as these are the questions that are mostly commonly used and associated with voice search queries.

SEOs can then weave in the answers to the most important keyword searches into our static page content.

We can then group other common and related questions together in an FAQ page. This makes sense as voice searches are usually in Q & A format so utilising FAQs plays perfectly into this.

For more complex questions, these can be answered in blog content which has the added benefit of simultaneously helping to build your authority.

Try not to get caught up trying to repeatedly use the same keyword phrases. It is far more important that we use natural-sounding questions and answers, as these have a better chance of getting picked up in a voice-search. 

Use keywords that are related to, similar, or synonyms of your primary keywords. I’d recommend looking up keywords related to your primary keywords which people would use when asking follow up questions and weave them into your content too.

Putting Natural Language Processing into Action

To aid with Natural Language Processing and implementation, Goggle has a Natural Language tool that is incredibly useful to create content that performs well.

NLP ties strongly into sentiment analysis and entity recognition which are increasingly important factors in semantic search, especially with conversational search becoming increasingly popular.


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