I remember watching Minority Report back in 2002 with a smile on my face. Like many other techies fascinated with the future, I was so intrigued by the “gestural interface” navigation techniques that Tom Cruise was using (moving those multiple screens around!) and when and how they would one day become a reality. Couldn’t wait to live in a world where diverse data sets are connected and aggregated to provide a response to our interests.  Twelve years later, the maturation of the tablet market, significant advances in wearable and mobile technology, voice-directed search, and innovations like Google Glass portend a near future where answers are provided to questions we express by looking, pointing, or merely thinking. And though search optimization as an industry has been around 20 or 30 years, back to the early days of the Web, the industry’s now matured to the point where relationships, concepts, and descriptive object-aligned metadata is driving the next wave of information retrieval. As a marketer, it’s important to master Semantic Web optimization as the next frontier in the search marketing space.

Google’s Hummingbird algorithm ushered in the semantic search era in a more deliberate and mature way. The Semantic Web was defined during the last century. Moreover, the effort continued through work done by the World Wide Web Consortium (W3C) and Schema.org communities. As a result, search engines have now amassed enough data to be able to consistently deliver results through structured data sets. What we see today in global search results is still a small glimpse of what’s to come when structured data is rolled out more fully.

Prior to Hummingbird, keyword strings typically drove results via unstructured pathways. In turn, the structured authorship of articles has pushed its way into the entity-based search algorithm, driven by RDF and schema markup. Google’s shift to “entity search” has maneuvered our focus to schema, snippets, and OpenGraph. If there’s one thing Hummingbird has taught us, it’s that the age of Semantic Web optimization driven by structured authoring is now here.

At the Search Marketing Expo in March, Google’s Matt Cutts confirmed the search engine’s Author Rank (AR) is currently in place. Speculation persists about whether AR is being used as a confirming signal or as a ranking factor, and what strength of author influence is needed to impact results. The takeaway though is that SEO, social, and Web development teams shouldn’t ignore structured authorship.

So far, anecdotal research has shown a lack of even-handedness when it comes to administering common authorship standards. As a result, we see a reduction in “first class authorship” in the display of SERP rich snippets. However, we’re in a nascent period, folks. There will be more refinement of structured authoring, and this next era will be one where we move away from strict human readability toward precise machine readability. From an organic SEO standpoint, semantic search implies

  1. A departure from a focus on keyword sets to intent/context/semantic tactics
  2. A move from strict ranking focus onto traffic focus
  3. Focusing more on the audience needs and engaging content than on specific keyword usage
  4. Voice and mobile search becoming even more reliant on data structured correctly
  5. Localization and personalization that pushes SERP ranking to obsolescence

Search marketers have been adapting their strategies to account for implicit signals such as geolocation and search history, and with good reason. IP-specific search results have become the norm since the Hummingbird release. We’re no longer tied to stand-alone SEO for each property. Our global search strategies must provide context through an ecosystem that includes third-party publications, social activity, and other contextual signals.

The industry is migrating from an XML data-retrieval mode, one that is serialized, to a semantic mode, which is “graph” based. Linked data and content has always provided context for spiders to interpret and assemble. However, structured authoring takes it step further, enabling engines to easily index and attribute content while it’s distributed across multiple properties. Without Semantic Web optimization through structured authoring, context is missing, which makes your assets harder to find. And this standard and expectation will only progress.

Today, we ask, “How do I create relevant entities that provide data in response to a well-refined query seeking narrow results?” Semantic Web optimization is the answer.

I’ll talk more about how to deploy Semantic Web optimization in future posts.