Google’s Rank Brain Algorithm

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Day 1 of last week’s sold-out SMX Advanced conference featured a Q&A with Google spokesman, Gary Illyes. Covering a series of hot-button SEO topics in 2016, attendees of the conference gleaned insights into Google’s elusive Artificial Intelligence (AI) system, RankBrain.

SEOs started hearing about RankBrain in early 2015, and by October, had Bloomberg confirmation of its use “for roughly 15% of queries”. Eight months later, the AI system is used for “100% of Google searches” making the need to optimize all the more important.

But First: What Is RankBrain, and How Does It Tie Into The Hummingbird Algorithm?

RankBrain is a machine-learning AI system used by Google to make semantic sense of users’ complicated or ambiguous search queries. (Machine learning essentially means that a computer is able to teach itself how to do something, rather than being taught by humans or following detailed programming. There are plenty of every day examples of this as outlined by Builtin.com).

Rank Brain was born out of Google’s 2013 Hummingbird update that aimed to incorporate semantic search into its search engine. It’s not a replacement of Hummingbird, but rather a component of the Hummingbird algorithm as a whole.

“Hummingbird is the overall search algorithm, just like a car has an overall engine in it.

The engine itself may be made up of various parts, such as an oil filter, a fuel pump, a radiator and so on. In the same way, Hummingbird encompasses various parts, with RankBrain being one of the newest.” – Search Engine Land

Machine-Learning Artificial Intelligence… Sounds Creepy (But It’s Not).

Despite RankBrain’s post-apocalyptic Sci-Fi name, it’s really not that creepy.

All that’s really meant by “machine learning AI” is that the algorithm is designed to recognize and store patterns in user searches between what is typed and the actual intent. When a similar query is searched in the future, this stored information is applied to serve the most helpful results to users. All of RankBrain’s learning is done offline. By feeding the AI system batches of historical searches, it is able to make future semantic-predictions from the information. Searchengineland.com describes it as a kind of a “learn-offline-test” cycle.

RankBrain works in stark contrast to Google’s older methodologies, which relied heavily on exact and partial match keyword queries.

Let’s look at an example.

Example: The Query “How Do I Get to Wpromote?”

Without using the actual keywords “directions to Wpromote”, Google still understands that I want driving – or walking, biking, or public transportation – directions from my current location.

Indeed, Google’s top result when I type this in a local map appears in search results that offers all of these options to me.

Without typing in the actual keyword “directions”, Google understands that I likely want help getting to my destination

This is thanks to its “Rank Brain” algorithm, which uses offline machine learning to improve the quality of search results for Google users.

Cool, so Let’s Talk About Ranking Signal Influence & How To Optimize.

RankBrain is now Google’s third-most important PageRank signal. So yeah, going out of your way to optimize for this is important. Here are three tips for getting started:

1. Seriously, stop keyword stuffing.

RankBrain’s strong emphasis on semantic meaning versus traditional exact match keywords makes it even MORE difficult for black hat SEO tactics to perform well on SERPs.

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2.  Move your focus (even more) on the user.

I’m talking about both in UX design and in custom content. Google cares about providing quality results to its users. If you do this, your site will be rewarded with higher rankings. Plus, your customers will be happy too!

3. YES! Keywords are still hugely important.

Google’s algorithm is constantly improving its understanding of user intent, which has lead many SEOs to emphasize a more topic-based research strategy over traditional keyword research.

The fact is, there are still noticeable differences in SERP results with even tiny tweaks to long-tail keywords (i.e., search marketing agencies in LA vs.  search marketing agencies in Los Angeles). Rand Fishkin, Co-Founder of Moz, suggests using both topic and keyword-based strategy in order to yield the best results. He refers to this a hybrid model“.

Conclusion

RankBrain is a machine-learning AI system used by Google to make semantic sense of users’ complicated or ambiguous search queries. This is a major advancement in Google’s algorithm in order to better help users find information they are looking for. Rank Brain doesn’t negate the value for search engine optimization whatsoever. Instead, SEO’s should begin leaning into a hybrid model of optimizing websites for both keywords and topics.

Republished from original website I wrote for, Wpromote.

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