In this video, we're going look at the relationship between content marketing and BERT, Google's Natural Language Processor, that's now integrated into Google search. This integration has shifted the way that we should approach our content marketing. We will also review how content is going to be ranking within the search results.
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In the latest episode of Hack My Growth, we're going to be looking at BERT and how Google's Natural Language Processing tool has really shifted and changed the way that we should approach our content marketing strategies. All right, let's go.
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As I said in the opener, we're going to be looking at the relationship between content marketing and BERT, Google's Natural Language Processor, that's now integrated into Google search. This has shifted the way that we should approach our content marketing, and how that content is going to be ranking within the search results. Let's get into the content.
If you have any background in SEO, you'll know that content obviously is a very important part of Search Engine Optimization. It's obviously the foundation of our websites. And that's why we've gotten this, you know, idea that content is king. While that may be true in some sense, it's quickly shifting. And really the way that content plays the role, and how it plays a role, has drastically changed just in the last year, and really more so in the last six months, as Google has gotten more advanced and they've applied a lot more of Natural Language Processing and machine learning into the algorithm. We're going to take a look at how this has shifted in the industry and what you can do about it to make sure that you're on the cutting edge and the forefront.
Let's take a look at some common content marketing best practices as they pertain to the SEO industry. These are things that you'll find on pretty much every SEO blog. They're pretty much what we would call industry standard in a lot of cases, but they may not be the best practices today. These are things like, you know, write content around keywords and topics, right? We started with keyword-focused content in early parts of SEO, and then we moved to really dominating and owning topics. You know, the advent of a pillar page and really in-depth content. This led us to writing content of 2000 words or more, right? You need to have long-form content. That was something that's been preached for quite some time.
Then also you want to explore these topics from many different facets and angles. You would really attribute to long-form content and pillar pages. And also moving into something like an ultimate guide. Or using the skyscraper technique, where you would take what's ranking, recreate it in a better fashion and then, obviously, you know, use that for link outreach. Now these are some best practices. These are very common practices for a number of people in the SEO world.
Let's take a look at why this no longer works, or why those best practices may not be best practices anymore. For one thing, voice search has changed the way users search. Users today are much more comfortable using conversational speech in search. And this is not just for mobile devices or digital assistants, but also when we're on the keyboard. People are being much more conversational. They're being much more specific in the types of questions or the types of queries they're inputting into search. We're also seeing that short-form content, specifically when it comes to featured snippets, are performing or outperforming, in a lot of cases, those longer pieces, that longer-form content.
Google has also expanded its knowledge and its reach. It's now tapping into linked open data. So it's looking at sites like Wikidata, Wikipedia, and these other large databases and reference centers of information online. It's learning from that information, and it's better to really understand context and content in the meaning that the author originally intended for it to be understood. Now, this is because we have these unique queries. These unique intent-based queries, they're demanding very specific answers. Google can't give these broad answers for queries because each query has a really specific intent behind it. So as Google is learning, they're trying to give those more specific answers. As search has become more personalized, this plays a huge role. As well as Google's desire to diversify results. They're not wanting to show one site multiple times in the search listings anymore.
What's driven this change? BERT's been one of the big drivers. BERT is the Natural Language Processing tool that has been integrated into Google search. It's a neural-based technique for Natural Language Processing, and it's called Bidirectional Encoder Representations from Transformers. Now, traditional NLP uses something called RNNs to determine meaning. And what that does is it looks at each word in sequence to try to understand the contents as a whole. Well, the difference between that and BERT, BERT uses what's called a Transformer. And the Transformer, it performs small, consistent number of steps, but in each step, what it does is it actually applies self-attention directly to each word in that sentence in relation to all the other words. So instead of reading it like "John," you know, "went to the store," it's looking at each one of those words. Like, "John," how does "John" apply to "went" and "to" and "the" and "store." And it's looking at the relationships between all of the words.
This is actually what's happening in our brain. When we hear a sentence, our brain is looking at each of the words that are given to us and how do they relate to one another in order for us to understand context. It's a huge advancement when it comes to Natural Language Processing and it helps machines better understand what the sentence actually means. So BERT can really understand the full context of a word by looking at the words that come before it and after it. Now this is extremely important in understanding intent and that's been one of Google's main drivers. If you're reading a lot of the Think with Google blogs, and you look at a lot of stuff they're putting out, that's really what they're trying to do, is better understand the intent of the users. And BERT is helping enable that.
So RankBrain was the machine learning, right? This was them, you know, understanding what things mean, and understanding what entities mean. And now BERT is helping them understand what those entities mean within the context of the language. Which is obviously very important.
Let's look at an example of before and after BERT. And these are examples straight from Google. This query would be like "2019 Brazil traveler to the U.S. need a visa." What this person's looking for, Brazil traveler, that's moving, going to the United States. Do they need a visa?
Now, before you would get this Washington Post article, which is actually giving you the answers in the opposite direction. This is showing that a United States citizen can travel to Brazil without red tape, but that's not what the query is looking for. The query is saying, does a Brazilian traveler need to go to the U.S. Because that word "to" plays a huge role in the context, Brazil to the United States, not the other way around. Now after BERT, you get this site from the U.S. Embassy, which gives them information of people from Brazil traveling to the United States. Obviously this result is much better.
Let's look at one more. "Do estheticians stand a lot at work?" So what they're doing down here is they're comparing a medical aesthetician versus a spa aesthetician. And they're talking about the different types of jobs or the different types of estheticians there are. That's not what the query is looking for. What the users wanted to know was, do they stand a lot. Are they on their feet a lot at work. And now with BERT, there's a new article, the physical demands. Well, now they're going to talk about exactly what the physical demands of the job are. So BERT's getting a lot more specific, and it's getting very, very close to the intent of what the user's looking for, and giving them more relevant search results.
This means as SEOs, as content marketers, we have to know the intent of our users, because Google, with BERT now, can understand that and can match that content with them. Our content has to match the user's intent and it has to be within the right context. We can't just try to write as much content or as much long-form content as we want. We have to be very specific about what our users are looking for and the answers that they're trying to understand. We can't just target keywords and topics. We can't just be really broad. We have to be more customized. We have to have our content structured properly so that the search engines can really understand the intent, and that our users are happy with the results that they're getting. We can't just, you know, like I said, write these broad pillar pages and try to cover everything. We have to really look at, what does the user need, and then, what is the exact answer that they're looking for that can solve their problem in the fewest amount of steps as possible.
Let's look at an intent example. If I was going to be writing a blog on entrepreneurship, and I want to talk about what does it mean to be an entrepreneur, changing a few words can vastly change the results in search. The first one is, "what does an entrepreneur mean." Now, the intent of this query, "what does entrepreneur mean" is probably somebody looking for a dictionary definition. What is the definition of an entrepreneur? Here we've got a rich feature of a featured snippet that's showing dictionary, entrepreneur, the links in here, and also right underneath, people also ask for. So what does it mean to be an entrepreneur? What is an entrepreneur example? What's the meaning of an entrepreneurship? This is somebody looking for a dictionary definition. If I'm writing content here, I have to approach it from that angle.
If I'm talking, what does it mean to be an entrepreneur, which is a very different, but very close query, you can notice here, what does it mean to be an entrepreneur? I have to answer this question specifically. I have to talk about what it means as the individual and what that job is. What does it look like in everyday work. What are the characteristics of an entrepreneur. And you can see right away, we've got a featured snippet again. Then we've got a few other articles. Again, the reason I think this one from entrepreneur.com isn't doing well is, in this case, is the true meaning of entrepreneur. It almost is much closer related to this example over here, where this is the definition, when really they're looking at, what does it mean from like more of an emotional standpoint than it does from a definition standpoint. As you can see, by changing just a few words, you can get a vastly different search result. And it can also be the difference between you ranking for that term or not at all.
Short-form content can get the job done much better than people think. Yes, the crawlers do need content to understand what you're talking about. But as we've seen today with the advent of RankBrain and now BERT, we see that the search engines can understand context much more clearly. I looked at 67 featured snippets that we've earned for our clients, and that's just a small sample of them. But the average page had less than 1500 words. Now, remember before, an SEO best practice is to have 2000 words or more. Most of these featured snippets are less than 1500 words, and many of them are well under 1000 words. They're short-formed answers. We have one site that has very short-formed answers for a number of these questions that are ranking very well.
Their site has strong authority. A lot of the other metrics still apply. Like, you have to have strong backlinks. You have to have authority. You have to have expertise. You have to have trustworthiness. You know, all those things still play a role. But after you've earned that, you don't necessarily have to have these super long in-depth pieces of content. You have to have specific content that quickly answers people's questions. The reality is with featured snippets, you'll get a ton of impressions, but it doesn't always result in clicks. Most clicks now, especially when it comes to these featured snippet listings, turn into what are called zero-click searches. People are looking, they're seeing their answer really quick. They get what they need right from that featured snippet, and then they typically move on. Maybe they bounce to a deeper search or a different search. Or they've gotten what they've wanted and they move forward.
So these feature snippets are really about how specific that content matches the intent of the query. That's the most important piece today. Especially when we're developing content. Again, going back to that intent. How closely does it match what the user's looking for?
This brings us to the next thing. How do we make sure that our content is getting in Google in the right context. That Google can fully understand what I'm talking about. Again, BERT is going to look at each word and how it applies to the words around it, in the context of the sentence, or the context of the piece of content it's looking at. It really enables search engines to better understand and grasp context.
Now, this is really at the core of what Google is moving to when they do their strings to things. But computers can only understand the information that they've been given access to. This brings us into really understanding entities as one of the main drivers behind what Google's doing. An entity is a thing that exists in and of itself. You know, a lot of times you can think of something like a noun, right? A person, a place, a thing. But some entities have multiple meanings, right? So let's look at a term like CPQ. If we're targeting this term, it could be a number of things. It could be something in Quebec. It could be this enzyme that I'm not going to try to say. It could also be this main ingredient in dental rinse fillings. Or it could be Configure Price Quote.
If I work for a company that's trying to sell sales software, and I want to write a piece of content around CPQ, I have to really define what that means to the search engine. Now, by using terms like sales and price and quoting, the search engines can get an understanding of what I'm talking about with unstructured data. They can structure my unstructured content. But if I can begin to attach entities to my content, to help them better understand it, it's going to help move this deeper connection much faster so BERT's going to have a better understanding, RankBrain's going to have a better understanding. Google search as a whole is going to really know what I'm talking about very quickly without having to go through these extra steps of really figuring out what I'm trying to say.
Content marketers and SEOs can help these search engines by leveraging linked open data and allowing them to know exactly what they mean. This is called disambiguation. If I go to this page right here, this is a Wikipedia page, and I can connect an entity to this page. I can say, hey I'm actually talking about Configure Price Quote, that's the one that I'm talking about. Because what happens is, Google will come in, they'll say, okay what do we know about CPQ? Like I said before, it'll run through each of these four things. But if I can immediately point them to what I'm talking about, that will disambiguate my content and then allow me to make these deeper connections.
Now, there's a number of ways that you can do this. One of the best ways is using Tools, and there's a really powerful one called WordLift and I'm going to be doing a video on them very shortly. What this does is it helps us to create those connections and link our entities together so that our content makes sense of the search engines very quickly.
Now, another thing Google is doing is trying to be more specific and diverse in their results. They're seeing billions, literally billions, of search queries every day and 15 percent of those are queries that are brand new. Things they've never seen before. So again, think about this. As voice search has happened, as we begin to be more conversational and natural in our searches, the search engines have to better understand intent and context. And that's where BERT comes in. If we as SEOs and content marketers are only focusing on a few key terms and topics, we're missing out on literally millions and millions of opportunities to reach people exactly where they are with the questions that they're looking for answers for directly.
They want to be more diverse. In June of 2019, Google actually announced that they're going to really be pushing more diversity in the search results. They said this change is launching and it's designed to provide more site diversity. This means they don't want to see more than two listings from the same site in search. This means that you guys out there, if you're not one of these big brands, you have a huge opportunity to get into the search results, to leverage what Google's doing and opening it up and making ... and trying to make it more diverse. And the way that you do that is by writing content that matches users' intents, connecting that to the entities that Google understands, and help creating your site with this really deep linked information, as well as positive content that drives users into action, because you've matched their intent.
There's a huge opportunity, probably bigger than we've ever seen in SEO. And now, all we have to do is really just take a step back and start to adjust how we approach it, and be more conversational in our content and be more specific in how we're solving problems. This is extremely important. To me, this is like one of the biggest opportunities for us out there. And BERT has really opened the doorway for that. Now, it can be confusing when you start talking about Natural Language Processing, machine learning. What do all these things mean and what's happening? But the reality is, we've got more opportunity than ever before.
I really want to encourage you out there to look at the search results. Try to better understand what your users are actually looking for, create content specifically for those questions. And then create linked connections using linked open data and creating a really good linking structure in your back end, and structuring your day in a way that Google understands it.
Again, the other things apply. You need to have links. You need to have authority. You need to have trustworthiness. But if you do those things, you can actually get a lot of visibility without being one of these massive sites online.
I hope that you found this helpful. If you have any questions, please comment below. We'd love to continue the conversation with you. And until next time, Happy Marketing.
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