Structured Thinking About Semantic Search
Following a March 15 Wall Street Journal article, “Google Gives Search a Refresh,” the topic of semantic search has again become a hot-button issue for SEOs and webmasters. In that article, author Amir Efrati refers to coming changes across Google results pages, largely derived from enhancements in its core semantic search capabilities, as “among the biggest in the company’s history and could affect millions of websites that rely on Google’s current page-ranking results.”
If this “new” news is to be believed, then Google appears primed to make good on its promise to better understand both the Web and the intent communicated by its user base through the queries entered. But is this really news?
Semantic search, which according to Wikipedia is the process through which search technologies “improve accuracy by understanding searcher intent and the contextual meaning of terms as they appear in the searchable dataspace,” has been around for a while. Even over the course of the past year, Google has been assigning semantic meaning to content items that have been marked up with the microdata format advocated by schema.org. Recently, Danny Sullivan wrote an extensive piece on Google’s history with semantic search, and how this latest news appears to be little more than Google PR at work.
So while this may not be an earth-shattering announcement, it does warrant investigation because Google has brought attention to it. Is there a bigger story here than meets the eye?
Google Knowledge Graph
Beyond schema, which is a Webmaster’s tool to communicate semantic instructions to the engines, Google is building what it calls the Knowledge Graph, a collection of information sources that help discern a user’s specified intent with each individual query, even providing for answers directly on the search engine results page where warranted.
In the healthcare space (my new playground), Google “Symptom Search” is a great example of the Knowledge Graph in action. Enter into Google any symptom you may be experiencing (for example, “headache”), and Google will pull data from the Knowledge Graph to direct you to possible health conditions. The traditional ten blue links have been deemphasized in favor of possible answers to the user’s direct question. These types of interactions appear to be the future of search -- scary territory for SEOs who are accustomed to keyword-level optimization practices.
Is SEO “Dead”?
Every few months a new article is written proclaiming the death of SEO. In fact, it happens so frequently that it’s become something of an online meme within the SEO community. It’s easy to dismiss those pieces as largely hyperbole at work, but one caught my attention as being very timely and applicable to SEO in a Knowledge Graph environment. With “The Rise of Content Strategy – What To Do About Google Killing SEO,” James Mathewson teed up the challenges SEOs now face with semantic search:
“How do SEOs traditionally optimize pages? By advising their clients to put keywords in strategic places on a page. When Google goes to semantic search, it won’t be as much about keywords at all, but on the meaning of the words you use. This might be the biggest SEO killer of all. If tuning our content for keywords our users care about is no longer an effective strategy, what is left for SEOs?”
Mathewson goes on to advocate for a new flavor of SEO practitioner, the “content strategist.” I agree completely with that view, and see three things that SEOs need to do right away in order to prepare for a semantically driven future in search:
1) Become a content strategist – technical on- and off-page factors will continue to see a decline in importance. The most compelling and desirable content will win.
I can’t help but think how this new thinking gels perfectly with the concept of storytelling and content curation through social media channels. This construct would be the ideal ying-yang relationship to content marketing across search and social channels.
2) Answer questions through content – keyword research will take center stage, and new software applications will undoubtedly be introduced that look to mine intent from raw keyword clusters. Understanding intent will become crucial during this research phase, because content will need to be crafted to specifically answer the questions posed through user queries.
3) Rally around standards like schema – a legitimate Knowledge Graph may one day render schema obsolete and unnecessary, but it’s the best we have to work with today. And an early adopter opportunity still exists in every industry vertical. By employing schema today, you will become better positioned for semantic search 1.0 and will be at the forefront when future enhancements are introduced.
According to Amit Singhal, who heads Google Search, these initial forays into semantic search and Knowledge Graph in particular represent “baby steps.” Singhal says there’s a “long road ahead.”
The best advice seems to be: Get on board now.