Natural Language Processing (NLP) in SEO guide

Jack Boulton

As a fellow SEO nerd, you're probably just as obsessed as we are when it comes to keeping in the loop with all things Google.

The funny thing is, while we're all busy trying to keep on top of algorithm updates and ranking factors, Google is trying just as hard to keep up with us.

You see, we're humans, and therefore we speak like humans (most of the time).

Which up until recently, Google has kinda struggled with and is one of the reasons why so much emphasis has been placed on keywords over the years.

But things are changing.

Thanks to Natural Language Processing (NLP), Google is becoming better and better at using context to understand the true nature of content.

Coupled with the rise of voice search, NLP is teaching Google how to think and communicate like humans.

Google is learning our lingo, and learning it quick.

This article will help you learn more about what Natural Language Processing really is, why it’s important for SEO, and how you can start implementing it into your strategy.

So settle in and get comfy, because we're about to go real deep.

What is Natural Language Processing?

NLP is effectively the process in which search engines break down and understand human language better.

This process is made possible by Google as it’s able to leverage powerful AI and its vast data reserves.

Now, Google can interpret search queries better than ever before, meaning it’s able to serve up more relevant and more accurate search results time after time.

Let’s look at a real life comparison.

If you’re at a bar with friends and you announce that you fancy a screwdriver, then you’re probably referring to the vodka-based cocktail and not the trusty tool kit essential.

Although who knows, maybe you’re a passionate tradie always on the lookout for odd jobs, each to their own.

But let's assume you’re just thirsty and wanna let your hair down a bit more.

Your friends are probably going to assume you want a cocktail. Why? Because you’re in a bar, it’s a Friday night and your favourite song has just come on.

That’s the context.

Similarly, when you search for a screwdriver online, Google is also on the hunt for context.

This is when its Natural Language Processing kicks in, analysing content and examining search phrases to understand the true meaning and intent of the search.

And, just like your friends, Google assumes what you want.

Voila, you now have your search results.

So how does NLP affect SEO?

Before we look at how Natural Language Processing affects SEO, let's start by having a quick history lesson.

Back in 2019, before the days of face masks and social distancing, Google announced an algorithm update: BERT.

The fact that Google even made an announcement was enough to prick the ears of SEOs across the world. And rightfully so, as soon after the update was announced, Google confirmed that one in 10 searches would be affected by BERT.

This was the signal for the SEO community to mobilise and do its thing.

Countless tests and brainstorming sessions later it was decided that the algorithm update centred around three main pillars: quality content, context and NLP.

So, armed with this knowledge, SEOs were able to determine that content that’s more specific, more relevant and more descriptive would rank higher on Google.

Which makes sense, right?

If Google is moving towards a system that focuses on processing natural language, then of course it's going to favour content that sounds more like how we normally speak.

No one goes around stuffing keywords into sentences while talking to people, do they? Just imagine...

“Should we food fine dining restaurants in Sydney near me this weekend?”

That's not how people speak.

So content that has clearly been written just to ‘rank' isn't going to cut it anymore.

The introduction of Google's Natural Language Processing AI, the brains behind the BERT algorithm update, caused a seismic change in the way the search engine crawls content.

Google no longer looks at individual words or phrases like it used to. Instead, the search engine uses a wider lens when going over content, analysing collective sentences and entire search queries rather than the specific keywords.

This is something to bear in mind when you're next creating content, but more on this and other content strategy tips a little later.

How does Natural Language Processing work?

This is where things get a little bit technical, so let’s quickly zoom out for a second.

To get to grips with the ins and outs of how NLP works, we have to begin by considering exactly what Google’s intentions with it were.

Aside from the fact that it sounds nice and fancy, Natural Language Processing was introduced to improve search quality.

At the end of the day, it’s Google’s users who pay the bills. No users would mean no searches and no searches would mean no ads etc.

So improving the user's search experience is always top of Google’s priority list.

But here’s the challenge: users are getting smarter at searching.

They’re becoming more specific about what they’re looking for and growing more impatient when they don’t find whatever it is they’re after.

In fact, data from Google shows that 15% of searches are completely unique as an increasing number of people use long-tail keywords when looking for an answer to their question. This means that every now and then Google’s algorithm doesn’t have enough data to decipher the user’s search intent.

But rather than just saying, ‘Nope, can’t really help you there buddy,’ Google bridges this gap in its knowledge, and it does so by understanding language better.

This is where NLP steps in…

Now we’re going to break down the core elements of Google’s Natural Language Processing AI. This will give you a better understanding of exactly how Google interprets your content so you can optimise it accordingly.

Be warned though, because you’re about to have your mind blown.

Syntax analysis

Rather than just analysing what a piece of content is about, Google’s syntax analysis method goes one step further and examines the actual structure of the language used.

It cleverly breaks up text into bite size chunks, also known as tokens, to better understand the sentence content and context.

The introduction of Syntax analysis helps Google easily identify and punish users guilty of implementing black-hat SEO tactics while rewarding quality content by ranking it accordingly.

In short, syntax analysis makes it easier for Google to separate the wheat from the chaff when it comes to content. Focus on writing quality content rather than aimlessly pumping keywords all over the place and you’ll be fine.

Sentiment analysis

Another tool Google has developed to help gain a deeper understanding of what content is all about is its sentiment analysis software.

Sentiment analysis is Google’s way of measuring the general feel and emotion of a piece of content and it kinda works like a vibe thermometer.

It looks at whether the words used in the text hold positive, negative or neutral connotations and scores the content based on the results.

For example, words like, ‘amazing', ‘delicious' and ‘stunning' would be given a score between 0.25 and 1 (good vibes) whereas negative words like, ‘horrific', disgusting' and ‘disaster' would score between -1 and -0.25 (bad vibes).

Words that hold what Google classes as ‘neutral sentiment' (meh vibes) are given a score in between -0.25 and 0.25 as you can see from the table below.

But having negative sentiment doesn’t harm your rankings, Google just uses your sentiment analysis score to determine whether or not to match your content with specific searches.

Let’s say someone is looking online for ‘how to bake a victoria sponge cake’. All the highest ranking pages will be positive, talking about how delicious and fluffy their recipes are.

But if your slice of cakey content instead focuses on bland and unappealing ingredients that taste bad together, then guess what? Google won’t consider your page relevant to the user’s search and your content won't rank.

And you should also probably invest in some baking classes too.

Entity analysis

Entity analysis is Google’s way of identifying and evaluating different nouns used in content to help it provide better search results.

Google defines entities as: ‘A thing or concept that is singular, unique, well-defined and distinguishable.’

Some examples include:

  • Places
  • People
  • Numbers
  • Goods
  • Organisations

After crawling your content, Google provides each entity with a salience score ranging from 0.0 to 1.0. Salience basically represents each entity's importance in the text, and the higher the salience score, the more important and relevant Google deems it.

Let’s say for instance you’ve written a piece about surfing. Google would give the word ‘wave’ a higher salience score than ‘grass’ because it is considered more important to the subject of the page.

This is Google’s way of building that all important context, think back to ordering that screwdriver while at the bar with your friends!

Content categorisation

This one is pretty straightforward.

Content categorization, or content classification, is just the way in which Google is now able to scan a piece of text and immediately identify what category it belongs in.

Let’s look at the previous two examples we used again.

Google would scan your not-so appetizing cake recipe and immediately classify it as baking content. The same goes for your blog post about surfing, Google would have a quick once over and say, ‘Yep, watersports it is!’

For all you Harry Potter fans out there, just think of the content categorisation process as Google’s version of the sorting hat.

“Not Slytherin, eh?”

Why is Natural Language Processing so important?

So, now you know much more about Google's NLP and how it all works, the next question is why is it so important?

In short, NLP is important because it gives us an insight into how Google views our content. Understanding NLP enables us to put ourselves in the shoes of Google and see where tweaks and improvements to our content can be made.

The bottom line is that Google has made it abundantly clear that it's placing greater emphasis on understanding user intent and search relevancy. That isn't to say that you should abandon all the SEO tactics that have gotten you success in the past, it's just something to be aware of.

In a way, NLP is just the latest piece to the growing SEO jigsaw.

Thanks to Natural Language Processing we now know the metrics Google uses to measure the quality and relevancy of our content. We know more about what it likes and dislikes and we can edit our content based on these parameters.

The primary function of search is to connect users with answers, fast, and NLP is just another step in the direction of streamlining this process.

Incorporating NLP into your SEO strategies

When it comes to incorporating NLP into your SEO strategy, it should come as no surprise that the usual culprits are at play.

Analysing and testing.

As always, a good place to start is on your competitors' sites, but unlike normal, you should look at their content a little differently to understand what Google likes about it.

Take a look at the top ranking pages for your niche and see what the context around the keywords you’re trying to rank for are. Can you see any patterns? If so then try optimising your content so that you can show Google you’re providing similar context to your high ranking competitors.

Another thing you should consider taking into account when incorporating NLP into your SEO strategy is the rise of voice search, which we briefly mentioned earlier on.

Figures from Google reveal that 27% of the global online population uses voice search on mobile with this number only set to increase as technology improves and more people purchase smart devices.

The increasing popularity of voice search is another one of the reasons behind why Google has opted to pay more attention to natural language, and it’s easy to see why.

Just like when people talk to each other, when performing a voice search, people speak using natural language, and Google picks up on this.

Again, this is all the more reason to make sure your content is coherent and wouldn’t seem out of place in a conversation with your friends, or Siri for that matter.

For years now SEO gurus have been shouting from the rooftops that content should be written for the user and not for search engines. With the introduction of Google’s Natural Language Processing, those words have never been more true.

But there is a slight hitch…

The only problem with incorporating NLP in your SEO strategies is that it can be extremely time consuming. Analysing and examining your pages to search for NLP optimisation opportunities can be a seriously lengthy process.

That's where Natch comes in...

Natch is natural language processing SEO software that we have developed inhouse at Local Digital.

It plugs in to Google's Natural Language Processing AI and allows you to quickly audit and compare copy to identify all those juicy entities and salience scores and other NLP good things, then use them in your SEO campaigns.

If you're interested in using natural language processing for SEO we recommend checking out Natch. It's a tool that makes the sometimes time consuming process faster and easier.

Using NLP for SEO is part art and part science. There are many different ways you can go about it, and it often requires a lot of testing then re-testing. So the tool is just a tool - you'll still need to use good old fashioned creativity and thought to come up with your own approach to working with NLP for SEO.

However, it's well worth creating a free trial with Natch and having a play around. We've generated huge ranking and visibility wins for our clients with it already, and you can too.

Next: How to learn webflow within 30days

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

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Static and dynamic content editing

Static and dynamic content editing

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Jack Boulton
Jack is the conversion copywriter at Local Digital. With a background in journalism and reporting, he specialises in getting to the crux of the issue when it comes to writing high-converting sales copy. You can typically find him in his copy cave writing pretty much anything from ad copy and landing pages to website content and B2B emails.

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