Welcome to the democratization of content and information.
RankBrain is the super smart three month-old brainchild of five Google engineers and a deep-learning expert. What’s come to fruition after an arduous year of research and development (along with Google’s five year-long movement toward A.I.), is Google’s recent incorporation of Artificial Intelligence into their latest 2013 algorithm update, Hummingbird.
RankBrain now handles 15% of search queries by organizing vast amounts of language into mathematical equations, called vectors, which the computer can “understand” and make connections with. This means Google can better understand a search query and tie it to relevant, quality results, regardless of how often it’s searched for or how new the search is.
Greg Corrado, a senior research scientist at Google, told the Washington Post that while RankBrain is just one of hundreds of signals that determine rank, it has quickly become the third most important, and by turning off this feature it “would be as damaging to users as forgetting to serve half the pages on Wikipedia”.
For a deeper learning experience, read a post by Kristine Schachinger and learn more about Hummingbird, entity search (how an algorithm recognizes combinations of and the order of words), and Google’s new A.I., RankBrain.
What This Means for Search Results
Google is now able to make connections across the meanings of search queries using RankBrain’s pattern recognition learning skills (rather than human work to connect synonyms with each other) so that when something is not searched for often, or is a new search, RankBrain can still make a great guess as to what content will appeal most to those searchers.
This is because RankBrain is a learning machine, which means as time goes on it will become better and better at identifying what content is best for any keyword based on pattern recognition across language used in the pages that have been indexed. This is how semantics will be determined by populations at large, rather than Google engineers and other Google-hired persons. Long live semantic search!
Here’s an example:
Before, using entity search (along with the human work that went into connecting synonyms), Google could connect the hypothetically uncommon search query “How many ENT doctors does it take to fix sinusitis” more closely to a page that says:
“FAQ: How many Otolaryngologists will I need to visit to clear my sinusitis?
Answer: It should only take one skilled Otolaryngologist to help you with your sinusitis and allergy problems.”
then to a page that says:
“..when I ask a patient how many years they’ve been experiencing sinusitis, and ask “how long does it take” for them to start noticing a change in symptoms after taking… as part of a team of experienced ENT doctors…”
Now, Google can connect “How many ENT doctors does it take to fix sinusitis” with other related language based on the patterns it’s identified across indexed pages and therefore connect this search with results that fit those same language patterns. So perhaps the page that would rank would say:
“…each of our highly skilled Otolaryngologists are certified by the American Board of Otolaryngology (ABO) and will be able to handle any sinusitis problems you may be experiencing. This includes…”
What This Means for Investing in SEO
So, now that Google’s so clever, is it all over for SEO? Heck no! If you know how to gain insight into your audience and their needs using keyword research and can translate this into content that they’ll love – you’ll excel as a top competitor in the search results; it’s a good thing that as Google’s A.I. learns, it will continuously give us better information in order to do just that.
Here’s a little glimpse of TopRank Marketing’s approach to integrating SEO and Content Marketing in a way that keeps us competitive in a quickly-changing SEO environment.
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