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 collectedto 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.