As a fellow SEO nerd, you’re probably just as obsessed as we are with keeping up with everything Google.
The funny thing is, while we’re all busy tracking algorithm updates and ranking factors, Google is working just as hard to keep up with us.
Because we’re humans, and we speak like humans (most of the time). And historically, that’s something Google has not always been great at understanding, which is a big reason why keywords have been such a focus for so long.
But that’s changing.
Thanks to Natural Language Processing (NLP), Google is getting better at using context to understand what content actually means, not just what words it contains. Combine that with the rise of voice search, and you can see why NLP matters. It is helping Google interpret language more like a real person would.
In other words, Google is learning our lingo, and it is learning it fast.
In this article, we will break down what NLP actually is, why it matters for SEO, and how you can start using it in your own strategy.
So settle in and get comfy. We’re about to go deep.
What is Natural Language Processing?
NLP is essentially the way search engines break down and understand human language.
It is powered by Google’s ability to leverage advanced AI and its massive data reserves. Because of this, Google can now interpret search queries better than ever, which allows it to deliver more relevant and more accurate results consistently.
Let’s look at a real-life example.
If you are at a bar with friends and you say you feel like a screwdriver, you are probably talking about the vodka-based cocktail, not the tool from your toolbox. Although who knows, maybe you are a passionate tradie always on the lookout for odd jobs. But let’s assume you are just thirsty and keen to let your hair down.
Your friends will naturally assume you mean the drink. Why? Because you are in a bar, it is a Friday night, and your favourite song has just come on. That is context.
When you search for a screwdriver online, Google is also hunting for context. This is where Natural Language Processing comes in. Google analyses the language you use, looks at the surrounding signals, and works to understand the true meaning and intent behind your search.
And just like your friends, Google makes an educated assumption and serves up the results it believes you are looking for.
So how does NLP affect SEO?
Before we dive into how Natural Language Processing affects SEO, let’s start with a quick history lesson.
Back in 2019, before the days of face masks and social distancing, Google announced a major algorithm update called BERT. The fact that Google even made an announcement was enough to get SEOs around the world paying attention. And for good reason. Google later confirmed that around one in ten searches would be affected by the update.
That was the signal for the SEO community to jump into action.
After countless tests and a lot of brainstorming, it became clear that BERT centred around three core pillars: quality content, context, and Natural Language Processing.
With that in mind, SEOs quickly realised that content which is more specific, more relevant, and more descriptive would perform better in search results. Which makes sense. If Google is moving towards a system that focuses on understanding natural language, then it is naturally going to favour content that sounds more like how people actually speak.
No one goes around stuffing keywords into sentences in real life. Just imagine saying something like, “Should we food fine dining restaurants in Sydney near me this weekend?” It sounds ridiculous.
Content that is clearly written just to “rank” is no longer going to cut it.
The introduction of Google’s Natural Language Processing systems, which sit behind the BERT update, marked a major shift in how Google understands content. Instead of looking at individual words in isolation, Google now looks at full sentences and entire queries to understand meaning and intent.
This is something to keep in mind when creating content, and we will cover exactly how to apply this a little later.
How does Natural Language Processing work?
This is where things get a little technical, so let’s zoom out for a second.
To really understand how NLP works, it helps to start with why Google introduced it in the first place. Beyond the fact it sounds fancy, Natural Language Processing exists to improve search quality.
At the end of the day, Google’s users pay the bills. No users means no searches, no searches means no ads, and the whole engine slows down. So improving the search experience is always going to be high on Google’s priority list.
But here’s the challenge. Users are getting smarter at searching.
People are becoming more specific, asking longer questions, and they are far less patient when they do not find what they are looking for. Google has even said that a meaningful chunk of searches are brand new or have never been seen before, which makes it harder to interpret intent based purely on historical data.
So instead of basically throwing its hands up and saying, “Can’t help you there,” Google fills in the gaps by getting better at understanding language itself. That’s where NLP comes in.
Next, we’re going to break down the core elements of Google’s Natural Language Processing systems. Once you understand how Google interprets language, it becomes much easier to optimise your content in a way that actually aligns with how search works now.
Fair warning though, it might melt your brain a little.
Syntax analysis
Rather than just looking at what a piece of content is about, Google’s syntax analysis goes a step further and examines how the language itself is structured.
It breaks text into bite-sized chunks, known as tokens, to better understand sentence meaning and context.
This allows Google to more easily identify content that has been manipulated using black-hat SEO tactics, while rewarding genuinely helpful, well-written content with stronger rankings.
In simple terms, syntax analysis makes it easier for Google to separate the wheat from the chaff. Focus on writing quality content rather than stuffing keywords everywhere and you will be fine.
Sentiment analysis
Another tool Google uses to better understand what content is really about is sentiment analysis.
Sentiment analysis is Google’s way of measuring the overall tone and emotion of a piece of content. You can think of it as a kind of vibe thermometer.
It looks at whether the words used carry positive, negative, or neutral connotations and assigns a score based on that.
For example, words like “amazing”, “delicious”, and “stunning” would score between 0.25 and 1, which fall into the positive range. Negative words like “horrific”, “disgusting”, and “disaster” would score between -1 and -0.25. Words that are considered neutral sit somewhere between -0.25 and 0.25, as shown in the table below.
Having negative sentiment does not directly harm your rankings. Google simply uses sentiment analysis to decide whether your content is a good match for a particular search.
For example, if someone searches for “how to bake a Victoria sponge cake,” the highest ranking pages will usually be positive, talking about how light, fluffy, and delicious their recipes are.
If your content instead focuses on bland, unappealing ingredients that taste terrible together, Google is unlikely to see your page as relevant to what the user is looking for. As a result, it will not rank.
And you should probably invest in some baking classes too.
Entity analysis
Entity analysis is Google’s way of identifying and evaluating the different nouns used in your content so it can provide more accurate search results.
Google defines an entity as “a thing or concept that is singular, unique, well-defined, and distinguishable.” This can include things like:
- Places
- People
- Numbers
- Goods
- Organisations
After crawling your content, Google assigns each entity a salience score between 0.0 and 1.0. Salience represents how important each entity is within the text. The higher the score, the more relevant and important Google considers it to be.
For example, if you have written a page about surfing, Google would give the word “wave” a much higher salience score than “grass,” because it is far more relevant to the topic of the page.
This is another way Google builds context around your content. Think back to ordering that screwdriver at the bar. Context is everything.
Content categorisation
This one is pretty straightforward.
Content categorisation, also known as content classification, is how Google scans a piece of content and immediately works out what category it belongs in.
Think back to the examples we used earlier. Google would scan your not-so-appetising cake recipe and instantly classify it as baking content. The same goes for your blog post about surfing. Google would give it a quick look and decide, “Yep, watersports.”
For any Harry Potter fans out there, you can think of content categorisation as Google’s version of the sorting hat.
“Not Slytherin, eh?”
Why is Natural Language Processing so important?
So now that you have a better understanding of Google’s NLP and how it works, the next question is why it matters.
In short, NLP is important because it gives us insight into how Google actually views our content. It helps us step into Google’s shoes and see where tweaks and improvements can be made.
Google has made it clear that it is placing greater emphasis on understanding user intent and search relevance. That does not mean you should abandon the SEO tactics that have worked for you in the past. It simply means there is now another layer to be aware of.
In many ways, NLP is just the latest piece of the ever-growing SEO jigsaw.
Thanks to Natural Language Processing, we now have a better idea of how Google measures the quality and relevance of content. We understand more about what it likes, what it does not, and how to adjust our content accordingly.
At its core, search exists to connect users with answers quickly. NLP is simply another step towards making that process faster and more accurate.
Incorporating NLP into your SEO strategies
When it comes to incorporating NLP into your SEO strategy, the usual suspects still apply. Analysis and testing.
A great place to start is by looking at your competitors’ sites. But instead of only focusing on keywords, look at their content through a slightly different lens. Study the top ranking pages in your niche and pay attention to the context around the keywords you are trying to rank for. Can you spot any patterns? If so, use those insights to optimise your own content and show Google that you are providing similar, relevant context.
Another important factor to consider is the rise of voice search, which we touched on earlier. Google has reported that a significant portion of the global online population now uses voice search on mobile, and this number is only expected to grow as smart devices become more common.
Voice search is one of the key reasons Google has placed greater emphasis on natural language. When people use voice search, they speak naturally, just like they would in a real conversation. Google is learning to understand that style of language, and your content should reflect it.
This is why it is more important than ever to make sure your content sounds natural and would not feel out of place in a conversation with a friend, or even with Siri.
For years, SEO experts have said that content should be written for people, not for search engines. With the rise of Natural Language Processing, that advice has never been more relevant.
There is just one small catch.
Properly analysing and refining your pages for NLP opportunities can be time consuming. Digging through your content to find optimisation opportunities is a detailed and often lengthy process.
That's where Natch comes in...
Natch is our in-house Natural Language Processing SEO software, developed right here at Local Digital.
It plugs into Google’s Natural Language Processing systems and allows you to quickly audit and compare copy to uncover valuable entities, salience scores, and other NLP insights. You can then use that data to fine-tune your content and strengthen your SEO campaigns.
If you are interested in using Natural Language Processing for SEO, we recommend checking out Natch.
It is a tool designed to make what can be a very time-consuming process faster and easier.
Using NLP for SEO is part art and part science. There are many ways to approach it, and it often involves testing, refining, and testing again. The tool is just that, a tool. You will still need creativity and strategic thinking to get the most out of it.
That said, it is well worth starting a free trial of Natch and having a play around. We have already generated strong ranking and visibility wins for our clients using it, and you can too.
