You don’t need me to tell you that change is the only constant in search marketing. Now, people are becoming more sophisticated in their searching, using longer queries, more precise terms, and more contextual info.
In a prior article, I talked about how search marketers can systematically adapt to change. I laid out a road map for responding in a structured way by analyzing stages in the search impact lifecycle.
But what about changes that haven't happened yet?
One of the biggest challenges facing search marketers today is structuring your website for best practices to limit future impact from the next Panda, Penguin, or Hummingbird. While lots has been written on these changes, lately an excellent post on the future of content marketing, today I want to take a wider focus and zoom out - like an astronaut looking down at Earth - to get a bigger view.
What we see is a world that's rapidly spinning away from search as we've known it for 15 years. In the old world, search was literal - based on exact matches between user searches and keywords. Even with tweaks like Panda and Penguin designed to weed out spam and deliver relevant results, the keyword was still king.
People are becoming more sophisticated in their searching, using longer queries, more precise terms, and more contextual info in their queries. Clearly, there's exponentially more content on the Web than there was even five years ago, and this means the needle-in-a-haystack science of algorithms must become more sophisticated in finding the most effective answers for queries. The expanding use of mobile and voice technologies are also changing how we search.
We've arrived at a place where literal matching by itself isn't good enough. In response, we're moving toward a new normal: semantic search. It's an idea that's been in the works for a long time and was described by the Web's creator Tim Berners-Lee in 2001 but is only recently going live in a way that affects regular users.
Webster's Online Dictionary defines semantic this way: "Of or relating to the meanings of words and phrases."
That's exactly what semantic search is about: figuring out the meaning of words and phrases as they are used in different contexts and for different purposes. It's more than just a matching system.
I like this quick and dirty definition from Search Engine Journal:
Semantic search is the process of typing something into a search engine and getting more results than just those that feature the exact keyword you typed into the search box.
Semantic search will take into account the context and meaning of your search terms...the assumptions that the searcher is making when typing in that search query.
Looking at Google alone, the move toward outward-facing semantic search began in 2012 with the Knowledge Graph. This is Google's technology for serving up popular facts about "entities" like people, places, and things and how they relate to each other. Two other semantic Google features are Voice Search and Google Now.
Most recently, Google's semantic function took a huge leap forward last August when the Hummingbird algorithm came out. I wrote about this in a prior article.
As part of looking at intent and context, Hummingbird personalizes the search experience based on each user's geographical location, search history, social activity, and other cues. This means that two people might get very different results from the same search query. In fact, localization and personalization may eventually make ranking as we've known it obsolete as results become more akin to true 1:1 marketing.
The actual hummingbird is a good metaphor for where Google wants to go with its capabilities: it's fast and precise. Because Google wants to deliver the most precise results quickly, good content is still key to organic search. And technical SEO still matters because all the epic content in the world won't get you anywhere if your site is slow, has bad architecture, or malfunctions.
In all of this, it's important to note that keywords still matter but conceptual search, schema.org alignment, site architecture optimization, and a user-centric content layout will matter more over the long-term. For some queries, an exact match is still the most appropriate one but semantic search deepens the options, depending on the kind of questions people ask.
In future posts, I'll be talking a lot more about what the evolution to semantic search means for marketers and SEOs.
For now, though, keep this in mind: The Knowledge Graph, Hummingbird, Schema.org, and Google's other semantic technologies are just the first steps in the direction of full-blown semantic search. All the major search engines, as well as academics, Web designers, and many others are already building more and better semantic technologies. This horse has left the barn, and there's no going back.
So, to return to the question of preparing for the future - we can't know exactly what search engines will do next, but we can be pretty sure of the big picture.
To prepare for change, think semantic strategy. Specifically, begin with the end user, the analytics, social, behavioral, and search data (paid, organic, and site search) you have on their interests, and drill in further to what's unique to their persona. We will all continue learning together as search changes and adapts to user needs.
Image via Shutterstock.
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Dave Lloyd is Senior Manager of Global Search Marketing at Adobe Systems where he leads a global team delivering organic and site search strategy and aligns closely with all other digital and media channels. As part of the Global Demand Generation organization, his team uses the Adobe Marketing Cloud to deliver on KPI-driven results including worldwide subscriptions, trials, sales leads, and revenue-based metrics. In his prior role at Cisco, he oversaw global SEO strategy for all products. He is Google-certified, with 14 years in digital marketing, and a Business degree from U.C. Davis. He's spoken at AdTech, SMX, Adobe Summit, BrightEdge Share, and DMA events.
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