And even though SEO is an area focused on optimizing websites to match the requirements of a particular system. That system is the search engine. It’s essential that SEO experts understand how the system they’re optimizing for works.

Best SEO strategies are developed by those who have in-depth knowledge about how search engines crawl and index websites, how their search algorithms work, and how search engines consider user intentions in rankings websites.

A new area to which experts should pay attention is machine learning. News about advances in Artificial Intelligence (AI) is all over the place, and machine learning seems to be at the center of it all.

But how does machine learning relate to SEO? Read on to find out the basics of machine learning and how to take advantage of this powerful technology trend for SEO.

First, what is machine learning?

It’s impossible to explain how search engines take advantage of machine learning without defining what it is first. According to Stanford University,

Machine-learning-explanation

Now, you might be hearing a lot about machine learning in the context of Artificial Intelligence, but remember that the two aren’t the same thing. The line between their applications might be a little blurry, but it’s key to understand the difference.

Machine learning is about getting machines to arrive at conclusions on the basis of information we give to them – but without being programmed explicitly for accomplishing that task. Artificial intelligence, on the other hand, is about creating systems that have human-like intelligence and process information similarly to the way we do.

Here’s another way to think about machine learning and artificial intelligence.

Machine learning is an approach used to design software that solves a particular problem. For example, developers can create an algorithm that will be applied to a vast repository of data without programming what the algorithm will be actually looking for. Instead, the machine is given a list of red flags or warning signals. On the basis of that, developers will ask their machine learning system to produce a predictive model for future rates of such red flags on the basis of the data analyzed.

All of that work is purely mathematical. In fact, you could employ several hundred mathematicians to do that task, but it would take them many years, and you would need to be very optimistic about the potential error rate. Machine learning algorithms can accomplish the same task but in far less time.

Artificial intelligence, on the other hand, is a system that has more in common with what we believe to be human intelligence. That’s why it’s far more creative and less predictable. You can use an artificial intelligence system to perform a given task: for example, analyze documents on a subject and draw conclusions from previous studies or add new data. Artificial intelligence systems can produce further information on the basis of analyzed data just like we do when we interact with the world.

So how machine learning relate to SEO?

If you look at the central initiatives of major search engines, you’ll see that machine learning pops up as one of their focus areas. Google has been pouring an immense amount of resources into machine learning research and made its machine learning framework TensorFlow open source.

Machine learning is the future so it’s in your interest to understand where it can get you regarding SEO. Here are several essential applications Google is implementing right now that you should know about.

RankBrain

Machine-learning-RankBrain

RankBrain can understand entities (concepts that are unique, well-defined and distinguishable) and how they are connected in a search query to help in better understanding the query and provide a set of good answers.

In other words, Google gives the system data and a set of known entities. The system will then train itself on the basis of these entities to learn how to recognize unknown entities. After all, search engines would be rather useless if they wouldn’t be able to understand the name of a new restaurant or movie.

RankBrain helps Google solve many of its problems. For example, it continually learns about how entities are connected to one another and understands when words function as synonyms and when they don’t.

Managing spam

Machine-learning-managing-spam

If you’re using any type of email system – including Gmail – you’re actually seeing machine learning in action all the time. Google claims that its algorithms can block 99.9% of all spam and phishing emails with a fantastic false-positive rate of only 0.05%.

Again, what Google is doing is giving their machine learning system data and letting it learn on its own. If Google wanted to program manually all the different permutations that would generate a 99.9% success rate in spam filtering, it would be an impossible task.

In fact, when Google did it that way they were able to achieve a 97% success rate with 1% of false positives meaning that 1% off and non-spam messages were sent to the spam folder.

So how does all that matter for SEO?

Understanding machine learning and its impact on how search engines layout SERPs is essential today. First, we need to take into account how the algorithmic factor influences the system in comparison to other factors.

It means SEO experts should pay more attention to creating content Google search algorithms will see as fulfilling the user’s intent. Machine learning is booming right now, and it’s not going anywhere it’s bound to become an even more essential part of Google.

That’s why SEO experts should keep in touch with these technology trends because they determine how search engines work and indicate the best ways to optimize content for SEO.