Tactical Keyword Research in a RankBrain World
Posted by Dr-Pete
Summary: RankBrain represents a more advanced way of measuring relevance, built on teaching machines to discover the relationships between words. How should RankBrain change our approach to SEO and specifically to keyword research?
This story starts long before RankBrain, but the action really kicked in around May of 2013, when Google announced conversational search for desktop. At the time, voice search on desktop may have seemed like a gimmick, but in hindsight it was a signal that Google was taking natural language search seriously. Just a few months later the Hummingbird update rewrote Google’s core engine, and much of that rewrite was dedicated to dealing with natural language searches.
Why should you care about voice? For most sites, voice is still a relatively small percentage of searches, and you’ve got other priorities. Here’s the problem, illustrated by the most simplistic Google algorithm diagram I’ve ever created…
If there were two algorithms – one for text search and one for voice search – then, yes, maybe you could drag your feet. The reality, though, is that both text and voice search are powered by the same core algorithm. Every single change Google has made to adapt to natural language searches impacts every search, regardless of the source. Voice has already changed the search landscape irreversibly.
Natural language in action
You may be skeptical, and that’s understandable. So, let’s take a look at what Google is capable of, right now, in 2016. Let’s say you wanted to find the height of Seattle’s iconic Space Needle. As a seasoned searcher, you might try something short and sweet, like this…
“Space Needle height”
Google understands this question well enough to attach it to the corresponding Knowledge Graph entity and return the following:
The corresponding organic results appropriately match the informational query and are about what we’ve come to expect. Google serves this search reasonably well.
“What is the height of the Space Needle?”
Let’s try to shake off our short-form addiction and try a natural language version of the same search. I won’t repeat the screenshot, because it’s very similar, as are the organic results. In 2016, Google understands that these two searches are essentially the same.
“How tall is the Seattle Space Needle in meters?”
Let’s try another variant, switching the “What” question for a “How” question, adding a location, and giving it a metric twist. Here’s what we get back:
Google understands the question and returns the proper units. While the organic results vary a bit on this one, reflecting the form of the question, the matches remain solid. Natural language search has come a long way.
Build great concepts!
This all may be a bit alarming, from a keyword research perspective. Natural language searches represent potentially thousands of variants of even the simplest queries. How can we possibly operate on this scale as search marketers?
The popular notion is that we should stop targeting keywords and start targeting concepts. This approach has a certain logic. The searches above …read more
Source:: Moz Blog