The rise of big data and better processing has enabled computers to become smarter and more powerful tools. Google and other search engines have been leveraging big data for years. Today’s search engines are smarter than ever and use Machine Learning (ML) and Natural Language Processing (NLP) to better grasp user intent and deliver more targeted results.
SEO has been and still is about optimizing a site or page for a user and a search algorithm. As user behavior online has changed over the years, so has the technology that runs the search engines. Those in the search field that aren’t keeping up will quickly be left behind. In today’s video, I’ll share why NLP is a big deal for SEO.
Hey, what's going on everybody? Welcome to Hack My Growth. In today's episode, we're going to be talking about the impact of NLP on SEO.
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Today is no different. Today we're going to be talking about NLP and its impact on SEO.
Now you might be wondering, "Okay man, what's with all of these acronyms? What do these mean?" NLP stands for a lot of things, but in this case, it's going to stand for Natural Language Processing. NLP is a very cool machine learning tool and capability that we have available now because of big data.
Big data has exploded over the last couple years, and now we can leverage that data to understand text as we've never understood it before. We can also understand websites as we've never understood them before, understand multimedia assets as we've never had an opportunity to do before.
So what's its impact on SEO? Well, one of the most significant impacts it has with Google is using NLP to understand the web and website assets better. Because they can better understand them and categorize these different pieces of content, it's going to rank differently because the algorithm is going to understand it differently. This is a little bit more of how RankBrain is working and impacting search in a big way.
If we look at Natural Language Processing, there's a number of things that are going on. We're going to talk about five of the things that you can do right now using Google's REST API inside of Google cloud. You're able to use this for yourself as well if you want to do some research or go deeper into the process. But maybe if you're not a programmer, or you don't want to go that deep, but you want to understand what's going on, this will help you better understand what's happening behind the scenes.
What it can do is, first it can do syntax analysis. It can break down the structure of sentences, content, and also understand what the context is. What's a verb, where the adverbs are, understanding the syntax of how the sentence was written, understanding how the formation of the content was made? This is really important because now it's understanding, is this a well-written piece of content? Did this person use the right grammar? What kind of audience would this be appropriate for? Based on understanding the syntax of that sentence.
It also has the ability to do entity recognition. So, this is an image. It also has the ability to go, "Okay, what's in this image?" This is a video, "What's in this video?" Now, NLP allows, with the leveraging of big data, to understand these entities like never before. They're starting to understand text inside of images, understanding what is that image without having to put an ALT tag or a title tag. These are things that we've done a long time in the history of search, which now we're having computer machine learning do a lot of this for us
Sentiment analysis. Now, this is a big one. This is going to try to understand the feelings behind the content. What's the emotion behind the content? They're using this in a lot of reviews. Is this a positive review or a negative review or a neutral review? Is this a strongly negative review or a kind of a mediocre negative review? Is this a strong positive piece of content, or just not one side or the other?
This sentiment analysis is really important, especially if you're a content producer, because we want to look at how this content's impacting how people react in search, how people react with our content and understanding, are we really pulling or hitting those emotional triggers to help bring people into our fold, help bring people into what we're doing online.
Sentiment analysis is something that NLP is doing and looking at content and saying, "Is this content emotionally appealing?" That's a very powerful thing when we start to talk about search, and we start to talk about digital marketing, content marketing.
It's also able to do content classification. It's able to read content and say, "This is a marketing piece," or, "This is an audible piece," or, "This is an engineering piece." It's going to be able to do that now without us having to tell the subject matter.
Now, yes we want to continue markup of our content and use schema because the more data we feed Google about our piece, the better picture they're going to have about it. But left on its own, it's doing these things, so we need to understand what's going on.
It also has multiple language support. So if your site is in multiple languages, it's going to be able to understand these things whether it's in English, Spanish, Portuguese, whatever language you may be using.
What can we do as SEOs? Well, we need to write for the users. People have been saying this for years, but a majority of people still don't do it. They go, "I have a blog just because I need to have fresh content." If the only reason you're posting is to have fresh content, but you're not putting time into good content, stop posting. Stop posting, rethink your strategy and write for the users. Understand their pain points, understand their needs, understand what they want, and then deliver that to them. If you can't do it, find somebody who can.
That's a really important tip. Don't just add noise to add noise; context is king. Make sure that your content makes sense within the context of the people reading it. Don't just throw stuff out there because you think that they need to know it. Again, don't only publish noise. Google's focusing on, how can we feel what the user's feeling? How can we understand the emotional sentiment that they have going into a search, and then deliver the most emotionally appropriate response?
That may seem crazy, and it's not going to be perfect all the time, but that's what they're trying to do. As content marketers, as digital marketers, as SEOs, it's our job to give people the best experience possible, to deliver the best piece of information possible, the most truthful information possible. If you do those things and you slow down your process to take time to write better content, to create a better web experience, to do better images, have better video, you're going to give better information to the algorithm. Which is then going to hopefully give you better results.
This is just the tip of the iceberg. We're going to be doing a lot more studies in NLP, in machine learning, to understand how we can leverage it to be better marketers online. If you've got any questions, please comment below. We would love to have you as part of the conversation, as part of our community, so please subscribe. Until next time, Happy Marketing.
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