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Technical SEO in the age of semantic search and Google
Contributor Ryan Shelley explains that technical SEO is more important than ever -- but for long-term ranking success, understanding how Google processes data is key.
“Does technical SEO even matter anymore?”
“If I just write a lot of content, I’ll drive traffic right?”
“Is keyword research even worth the investment?”
These are common questions I am asked and see asked across the web all the time. In an era that has proclaimed the death of search engine optimization (SEO) nearly every year and continues to proclaim “content is king,” a foundational principle shouldn’t be forgotten. In my opinion, it’s still important to talk about SEO.
While Google has made major shifts in the way they understand and deliver results, the idea that technical SEO is no longer relevant is absurd. My goal is to give you a better understanding of how semantic search and artificial intelligence (AI) thrive and need technical SEO to help them deliver better results for the end users.
When Google quietly rolled out the Hummingbird algorithm in 2013, semantic search came with it. Hummingbird was more than a simple algorithm update; at its core, it was a fundamental shift in the way Google would deliver results to their users.
Hummingbird was the culmination of 15+ years of data and user analysis, as well as testing and tweaking in order to deliver a substantial search experience for Google. No longer would content creators and users blindly try to guess each other’s keywords to create relevant connections.
The goal of semantic search was to leverage the massive amount of data that Google has collected to deliver contextually appropriate answers to the world’s questions. Here are three core elements that made this shift so unique:
- Hummingbird takes the entire query into account, not just the keywords.
- It takes the user, their search patterns, history and other variables into account.
- It takes into account the device type, time of day and location.
In order to deliver the right results as quickly as possible, Google created semantic search. At its core, the purpose of semantic search is to create a relational connection by delivering contextualized content.
The impact on SEO
While there was a significant shift in the way results are delivered, the basics of SEO still apply. Links are still important, keywords still matter, on-page optimization is still essential. When things change, it’s easy to assume “what was” no longer works. But what semantic search has really done is made it harder for those who use less-than-ethical tactics to rank.
When you hear the word “semantics,” it’s easy to get sucked into the association of this term and linguistics. But that assumption is not entirely accurate. Yes, content plays a big role, but so does everything else on your site that a crawler can read and index.
I see this all the time in the digital marketing space today. Marketers and site owners think if they just write a lot of decent content, they will rank and get found. Sadly, that is not how it works.
With semantic search, Google is moving from “strings to things.” This means they want to create more natural connections. But here’s the kicker: The algorithm cannot derive meaning and understanding on its own.
I think the biggest problem in SEO today is that we assume the algorithm knows more than we do. We seem to forget that it’s an algorithm and not a human. Like any data-driven program or artificial intelligence, it needs structured data to learn.
When we hear terms like artificial intelligence and machine learning, it is easy to think of self-educating robots that seek out information on their own. This is not how semantic search, RankBrain or any other aspect of the algorithm works. It requires education to become intelligent.
Google search is the most widely used big data tool in the world. To optimize our sites, we need to have a basic understanding of data entities.
Data entity refers to any person, place or thing data can represent or any data classification that links to other data classifications in relationships. Entities enable Google to understand how concepts and information fit together. When indexing a site, Google looks at the “person, place or thing” the site is about and makes connections to related content or entities in order to derive meaning.
When looking to make sense of your site and content, Google not only compares the entities on your site with each other, they also compare your site with trustworthy and authoritative sites across the web with the same entities. I know all of this seems a little heavy and complicated, but it is important to know what steps to take to ensure Google sees your site as trustworthy and authoritative.
How technical SEO helps
Technical SEO can help your site in the age of semantic search in a number of ways:
- Titles & meta. Your title is one of the first things crawled on your web pages. Providing a clear and focused title helps the crawler understand the content on the page. It helps set the tone and begins the process of entity relationships. Meta descriptions are not part of the ranking algorithm, but with semantic search, I believe they do hold more weight. Crawlers read and index your descriptions. Good descriptions not only help click-through rates but also give a short overview of the crawled page. This data is taken into account when the search engine is trying to understand the context of your page.
- Site structure. Having a well-defined and logical site structure is extremely important. Not only does this help your users find the content they need more quickly, but it also helps crawlers understand how your content is connected. Taking the time to develop a good structure will help ensure your site is indexed fully and the search engines have a good idea about your site subjects.
- Structured data. Structured data is metadata that is implemented to help search engines understand content and context. The most common way of structuring data is with the implementation of schema. Semantic search is all about structured data; the whole idea of indexing entities is built around structured data and schema. In the age of semantic search, adding structure to your site’s data is essential for success.
While many believe semantic search is all about more and better content, that is simply not that case. Yes, content is important, but I can argue that technical SEO is also more important than ever. Marketers, site owners and SEOs need to take the time to understand how Google processes data and find ways to help the search engines understand our sites’ content and why it’s beneficial to users.
Those who take the time to get this right will reap the benefits for years to come.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.