Semantic search launched in 2013 with the release of Google’s Hummingbird update. Since then, Google’s search engine has become more complex. The integration of ML, with RankBrain, and NLP, with B.E.R.T. has enabled the search engine to better understand the context of a query and deliver more personalized and targeted results.
In this video, I share what SEOs need to do today to thrive in the age of Semantic Search. I’ll discuss the importance of creating machine-readable content using structured data and the power of leveraging linked open data to help search engines better understand your content.
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Sign up for our course on Schema.org: https://simplifiedsearch.net/
An Introduction to Structured Data: How Markup Helps Search Engines Understand Context: https://www.youtube.com/watch?v=uwCR9We3JHw
How to Use Schema.org to Create and Add Structured Data to Your Website: https://www.youtube.com/watch?v=xQeRA-Ojq5c
Introducing BERT: Google’s Artificial Intelligence Algorithm: https://www.youtube.com/watch?v=Rs_jyNKKt9s
Table of Contents
As I said in the opener, we’re going to be discussing semantic SEO, how it applies to SEO strategy today, how it’s a little different from things that we’ve been doing in the past, and what we can do today in order to make sure that our sites are optimized so humans and machines have a semantic understanding of our content.
What is Semantic SEO?
Search Engine Journal defines semantic search engine optimization as “the process of building more meaning into the words you use in your content.” The content on our websites is typically mainly for humans. A lot of the content is human-readable only. So, it makes it difficult for a search engine or a crawler to process that information and understand the context. There has been, for a very long time, a large gap between what computers can understand and what people can understand. But, over the last few years, a number of advancements have taken place. As Google has continued to build and expand its knowledge graph, they’re starting to understand things at a much deeper level.
Semantic search is about adding structure and meaning to the content. It links the data together so that computers can better understand what we’re saying. When we look at this image from a Google image search, we see that the term Jaguar is put in as a query.
Now, this search isn’t that old, but even right now, the search engine is having a little difficulty understanding the context of that search. It’s not sure if I want to see a vehicle or a South American jungle cat. Right now, the search engine is trying to decide, so it’s showing us both. And it’s going to change the results based on what I click and what I engage with.
Understanding the Entity
The benefits of the semantic web are helping those crawlers understand the logical links between the queries and what we really understand or what we’re expecting from that. What it’s looking at is something called an entity and the connection between entities. I’ve done a video on what entities are so you can check that out, but what an entity is, is it’s a thing that exists inside of itself. And it’s something inside the database that Google can say, okay, a Jaguar is a car, or a Jaguar is a jungle cat. And understanding that entity in the context of the relevant keywords around it will help it better understand exactly what the user is trying to see and search. This is important because a car dealership doesn’t want to earn high search volume or topical authority in the animal rankings.
In the search algorithm today, the crawlers are looking at these terms and they’re breaking them down and understanding them and then classifying the specific terms as an entity, using the knowledge that it has about that to make a connection. Semantic search is not new. It’s actually been around since about 2013 with the release of Hummingbird. This was Google’s first attempt to really return more meaningful answers and begin to understand search intent in the context of a query.
Again, as we’ve talked about, it’s about creating those relational connections in context. Hummingbird is the base engine behind the search algorithm. But then, we’ve had some algorithm updates recently, in the last few years, which pushed this context and this understanding a little bit further.
Tools for User Intent
And the first one was RankBrain, which we all know was a machine learning algorithm. Again, it’s all about understanding context. In 2019, Google released BERT, which is a natural language processing tool that was the most advanced of its kind. It’s still the most advanced out there right now. It helps understand the word in context. It’s understanding both what’s coming before and after those entities in order to create a deep understanding.
Then, what these tools do is they go out to the linked open web and look at linked open data and understand what these entities mean. What do these words mean? What is the context of them? It’s pulling in all of this information that has been stored for tens and tens of years and now applying it back to that search query to better understand what the user is looking for. This new approach has radically changed the way that search engines show results specifically in the rich features, like the featured snippet, the people also asked box, the knowledge panel, things of that nature. Those can be influenced very much by a better understanding of the entities on your page from search engines using semantic SEO.
Optimize for People and Machines
Today’s SEOs have to optimize for people and machines. You can’t ignore one or the other. You have to optimize pieces of content around the search terms that your target audience is using and create relevant content that engages them and meets their needs. This is why I still focus a lot on empathy and understanding, and the psychological side of our users, because we have to understand why they’re searching, what they’re searching for, and what they’re expecting out of the searches. But then, we also must apply that knowledge to the search engines, and understand what they’re looking for, and optimize around entities, and create connections with the knowledge graph and linked open data to create that deeper meaning within our content that the machines themselves can understand. We really have to take a look at both of these profiles and personas when we’re approaching SEO today.
So, best practices are still in play. Internal link structure and backlinks still play a role. It’s still something that will add value to your site that will show that your site has authority and trustworthiness, and still an important factor when it comes to search. Keywords and search intent are essential. We look at the funnel, understanding how people move through the funnel. We have to play a role. We have to do our keyword, our topic research and understand the trends. We need to understand what people are looking for, and how they’re searching for those solutions. We have to have unique high-quality content. We can’t just create long-form content because it’s long-form and think it’s going to rank. It has to be unique. It has to be of high quality. It has to meet and address the needs and the intent of the users.
But, if you want to earn visibility today, you have to first understand how machines interpret entities, understanding, at least at a base level, how natural language processing works, how the search engines are looking at your entities within your piece of content, what they understand about the relationships between entities, and how they interpret the main focus of your content.
You also need to leverage structured data. That’s something we’ve talked about quite a bit on this channel, and how we can structure our content, structure our pages, and add those other layers of information that are for the machines to better understand the content and the context of what we’re trying to say.
Lastly, you need to be able to connect your content with linked open data. Linked open data are these massive database resources that Google uses and pulls from within the knowledge graph to better understand what things are, what entities are, and creating the connections between entities, helping them understand, again, the context of what you’re saying in your content.
Optimizing Pages for Semantic SEO and Topics
Semantic SEO helps make your content readable by search engines. But, don’t forget you need to make sure your content matches user intent and answers their queries around your core topics. You also need to make sure you have the linking structure and the content is organized in such a way that contributes to your site’s authority. Using a topic-based search strategy in tandem with semantic SEO will ensure that both machines and humans discover your content. I encourage you to dive deeper into how to optimize pages for semantic SEO here. You may also be interested in learning more about topic-based SEO here.
You’ll need to take time to explore long-tail keywords as well as semantically related terms to ensure the highest content quality. The more keywords your content ranks for, the more possible user queries you have the opportunity to earn.
How Can You Leverage Semantic SEO?
If you want to begin to leverage semantic SEO strategies, check out my course on schema.org markup for rich results. This course is going to help you begin to implement structured data, structured elements on your site. And it’s going to give you a deeper understanding of how schema markup works and how the semantic web works so you can apply these things into your website today.
If you’ve got any questions on the content that we spoke about today, linked open data, semantic SEO, or any other advanced SEO tactics, let us know. And, if you’ve got any questions about structured data in general or schema.org, we can also continue that conversation with you. And until next time, Happy Marketing.
Editor’s Note: This article was originally published in August 2020 and has been updated with fresh content.