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What is a Knowledge Graph & Why You Should Care

Jan 11, 2021
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In this video, we will learn about Knowledge Graphs. I'm explaining what knowledge graphs are and why all digital marketers should care about them. In short, a Knowledge Graph puts your data into context via linking, as well as semantic metadata. Google started building and using its Knowledge Graph to empower its transition from strings to things. This has helped them shift away from only featuring text and allows them to better understand concepts. Knowledge Graphs have huge implications for SEO, content marketers, and digital marketers across the web.

 

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Video Transcript: 

In this video, we're going to be taking a look at what a knowledge graph is and why we need to care. This applies a lot to the SEO community, but it also has huge implications for content marketers and digital marketers across the web. As these become more and more important, machines get a better understanding of who we are and what it is that we're talking about. This will make sure that our sites are not just optimized for search, but also allow us to offer better user experiences as well.

What is a knowledge graph?

I think this is a good definition, and is from ontotext.com. They say, "a knowledge graph represents a collection of interlinked descriptions of entities." These are objects, events, concepts. A knowledge graph puts that data into context via linking, as well as semantic metadata. This is a way to provide a framework for data integration, unification, analytics, and sharing.

After reading that definition, I understand that there's a little bit of intensity in it, but it's a really good definition. Let's break it down a little bit further. A knowledge graph represents the collection of concepts that we're talking about, and then it interlinks them together so that we can create new concepts and new understanding, and really add another layer of information. Now, this is typically for machines. Think like Google crawlers or other crawlers that are looking for information, but by having this information, it allows us to make more connections. It allows us to get better analytics. It allows us to share our information in more ways than just via text or just via links themselves. We're adding more context by connecting them and creating a knowledge graph.

How do knowledge graphs impact search?

Google began building and using its knowledge graph to empower its transition from strings to things, as they were making that shift away from just text and trying to understand concepts. This is where the idea of entities started to come into play when it came to SEO. 

They announced this in 2012, a while ago, so a lot of us may just be catching up to the understanding of how we can leverage this ourselves. Because knowledge graphs are not just things that can be used by Microsoft, Bing or Google search or some of these other big players, we can use them ourselves.

As we look at how Google has taken their knowledge graph and leveraged it in search, these are some things that we can see. You've got some of these broad cards, which are known as the knowledge panel, and we've got one here for knowledge graph. You see there are images in it, as well as a summarized bit of content. And then right below that we also see results.

You can actually click further. Then if I look at another term, we see even more information. So we look at communication. Again, we see that summarization, but then we also start to see some concepts around it. Why is it important? Ways to communicate. We have a bachelor, which is an interesting word, and then we've got adjectives.

We also look at books, Google saying, okay, if you're looking at communication, we've got a lot of data and connections that people may be looking for books. And then other information that we can look for,  information, language, speech, leadership. And there's view 10 more there. There's a number of pieces of information. Then we can also see in knowledge panels, which is pulling from their knowledge graph, for a company. This is Apple. We've got a summarization about the company. We've got stock prices, who founded the company, where they're headquartered.

We also see some more information about the company, things like support and battery and mission statement. Then below that we see their products. You can go down even further and begin to find further connections, as well as their social profiles and People Also Search For. The Knowledge Graph has enabled things like this in Google search. It's enabled search to become much more user engaging and also provide more information for the user right within the search query.

Why does this matter?

The original purpose of Google's Knowledge Panel was to help users find the right thing and understanding intent. This is something that we've talked about a lot, as well as many people across the web of finding the right intent, creating content that matches user intent.

The second way they wanted to use this was to summarize relevant content. As you can see, they've done that through all of those queries, typically using summarization of Wikipedia pages. And then they also want to provide deeper insights into queries, which you could also see in the knowledge panels today, where you can click deeper into content, maybe discover things you didn't know about, maybe discover connections you weren't aware of, or narrow down your search to really get to the original intent of why you started making that search.

This matters in a huge way. We can actually use these knowledge graph examples here, these panels within search, to understand quite a bit about what's going on within the query of the user and all the data that's been aggregated from behind the scenes that Google is now displaying for us in order to niche down and find the right content that we need to be producing for our end users.

Google's Knowledge Graph presents us with a ton of ranking potentials, not just in the Knowledge Panel, but also in other places throughout the SERPs. It allows us to have a deeper understanding of how our users are interacting. It also provides us with deeper understanding of how the search engines understand our queries. We can use this information to create targeted content, create content that matches intent. But we can also this to build a Knowledge Graph of our own, to enrich our sites for both our users, as well as the search engines.

Why does creating your own knowledge graph improve your SEO?

A really good quote from a word lift blog says, "Imagine the knowledge graph behind your site as a scaffolding that lets crawlers and bots access your content in a smarter and more efficient way."  Much like Google uses its knowledge graph as the engine to power up its search results, you can create a knowledge graph that describes the content of your site in a way that helps machines understand what it's really about. We're adding context, so "our web content is connected content." That's a quote from Andrea Volpini, the CEO of WordLift. Our content is connected through links. Typically this is what makes the internet work.

In the simplest form, you can build a knowledge graph by doing the following, defining the entities and the concepts that you or your site is about, creating pages with unique URLs for each of those, and then beginning to annotate your content to connect them all together, to start building these relationships.

You can do this manually. It takes a lot of work. It takes a lot of studying. It takes a lot of processes in place to do it right, because one of the keys is you don't just want linked data or linked entities, you want to have linked open data which is data that can be accessible by databases, by crawlers, by the internet as a whole. And that's what gives your data power. That's what allows your data to be used in more efficient ways. There are things that you can do to build this yourself, if you have the technical acumen.

But another way to do it is to leverage a tool. This is how we use WordLift on a number of our sites. Over here, we're using WordPress, but WordLift does work in some other domains as well. They've got a JavaScript implementation as well. But within WordLift, you can really see it quite well. This is an About Us page on one of the sites that we run that we have here. And as you can see, we've got these blue links here that are popping up. What WordLift has done is it's actually looked at the linked open web, it's pulled out entity concepts that are known. It said, hey, you need to create these entities on your site, build these URIs on your site, and create those connections. I just simply click on these to define the concepts I want to be known for and I start building my own Knowledge Graph. I started building this on the backend with simply clicking these here. And now, as we build our vocabulary to build our database, we can use this information to extend our site even further.  I'm going to take you behind the scenes really quick and show you a little bit more on how this works.

Here we have an article that we've already done quite a bit of this with, but this is an article on the site. And as you see WordLift running, it's starting to pool these entities. These are content classifiers. These are things that are known on the web that can be defined. And then we can add them to our site to say, this is exactly what we mean. As we go through our content, WordLift will crawl our content for us. Then it'll start to highlight things that it can see. It's using natural language processing in order to do this. Now over here, I can see that some of these may not be as useful to my piece of content, so I don't have to click them. I click and add the ones that are helpful, that are useful to adding that context and those terms, those entities that I want to be part of my Knowledge Graph.

Now, each of these is then stored with a unique URL into my site's vocabulary. That is injected into this page as structured data, so schema.org markup, and it's pointing to these linked open URLs that can be used by the crawlers to understand context and also show that this is what I mean when I'm talking about the specific concept. This is how we mark it up on the backend, but now let's take a look at what it looks like on the front end from a user standpoint, as well as a little bit underneath of how the crawler sees that structured data.

Here we have the article on the front end, and you can see that we've got links here. There are these little icons that pop up, which are summarizing the information that we have. If a user is going through this article and they want to know more about structured data, they can click on the link or they can hover over and WordLift is providing them this summary of some context here on the page. This is how we can use it for user information. It tells them right here what structured data is. They're not having to click into anything. Now there is that link there, if they want to go to the page itself, but then we're also displaying it for them on the front end, which is a really cool thing for users where they can just hover through this whole thing and get all the context they need.

But here's where the real magic happens. If we pull the RDF information from behind the page, it's going to show us the linked open data and the Knowledge Graph that's being built underneath our website, leveraging WordLift. You can see here that we've got entities and each of these entities have their individual URLs. These individual URLs are describing the different things that we're talking about on our website. The different concepts that we've covered in here, whether it be application software, or featured snippets, or Google image search, you'll see here that we've got titles for each of these entities, we've got alternate names for each of these entities, we've got a description, and then we've got the same as links. These are the linked open data sets that we're attaching these concepts to that allow the search engines and the crawlers to better understand the content under our site. This is the rich data that we're able to put into a knowledge graph that the search engines can read. This is machine-readable information. This is built for the machines themselves and allows them to better understand the concepts of our website. And as you can see here, it's leveraging schema.org vocabulary to mark these up within the RDF file.

Instead of building this out yourself, which you obviously can do, WordLift really helps to smooth it out. There are other things that we can do to leverage it further, to make our Knowledge Graph even richer. That's where structured data comes in. We've done a lot of videos on this channel about structured data, but what I've also done is created a very easy approachable course, whether you're somebody who's been doing structured data for a while, or if you have no idea what structured data is, and you're just getting started and you want to start earning these rich features, not just a Knowledge Panel, but also FAQs and image search and all the other ways that we can mark up our information to help the machines better understand it and earn those more powerful positions in search.

I've created this course to walk you through it step-by-step. We have a generator, we've got multiple ways for you to add it to your site and make sure that you can get the results that you're looking for. And to make it even easier for you, we've decided to give everybody on YouTube that's watching this video a 25% off.

Get access to the course today at learn.simplifiedsearch.net. If you have any questions, please let me know. Comment below. We'd love to continue to help you out on your journey. And until next time, Happy Marketing.

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Ryan Shelley, CPBI

By Ryan Shelley, CPBI

Ryan is passionate about helping companies make a more personal connection online with their customers and prospects. He is a regular contributor to Search Engine Land, the largest and most popular SEO news site on the web. His works have also been featured on the HubSpot Blog, Business2Community and by LinkedIn Marketing Solutions.

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