Think you got SEO all figured out? Think again.

Think you got SEO all figured out? Think again.

 

 

Late last year, Google confirmed the use of RankBrain, the new, and incredibly powerful, AI machine learning algorithm. What a lot of people might not realize, however, is just how fast the SEO industry is changing because of it.

 

So what exactly is RankBrain?

RankBrain is a machine learning AI system, which helps Google process search results and provide more relevant search results for users. According to Google, RankBrain is the third most important factor in the ranking algorithm along with links and content.

 

If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.

 

How does it work?

RankBrain interprets the user searches to find pages that may not have contained the exact words that were used in the user search query. When offline, RankBrain is given batches of past searches and learns by matching search results. Once RankBrain’s results are verified by Google’s team the system is updated and goes live again. So you see, the system is continuously learning, and gets smarter every time you search for something new.

 

How can I stay ahead of the changing SEO curve?

Every time Google’s rankings shift in a big way, data scientists and CTOs claim they “have a reason!”. So they perform regression analysis – go through months of ranking data leading up to the event, and see how the rankings shifted across all websites of different types. They then point to a specific type of website that has been affected (positively or negatively) and conclude with high certainty that Google’s latest algorithmic shift was attributed to a specific type of algorithm (content or backlink, etc.) that these websites shared.

 

However, that isn’t how Google works anymore! Google’s RankBrain, a machine learning or deep learning approach, works very differently.

 

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Within Google, there are a number of core algorithms that exist. It is RankBrain’s job to learn what mixture of these algorithms is best applied to each type of search results. This means that, in each search result, Google has a completely different mix of algorithms. You can now see why doing regression analysis over every site, without having the context of the search result that it is in, is supremely flawed.

 

For these reasons, today’s regression analysis must be done by each specific search result. We can then focus on improving that particular part of SEO for sites for those unique search results. But that same approach will not (and cannot) hold for other search results. This is because RankBrain is operating on the search result (or keyword) level. It is literally customizing the algorithms for each search result.

 

Get on Google’s “good side”

What Google also realized is that they could teach their new deep learning system, RankBrain, what “good” sites look like, and what “bad” sites look like. Similar to how they weight algorithms differently for each search result, they also realized that each vertical had different examples of “good” and “bad” sites.

 

When RankBrain operates, it is essentially learning what the correct “settings” are for each environment. These settings are completely dependent on the vertical on which it is operating. So, for instance, in the health industry, Google knows that a site like WebMD.com is a reputable site that they would like to have near the top of their searchable index. Anything that looks like the structure of WebMD’s site will be associated with the “good” camp. Similarly, any site that looks like the structure of a known spammy site in the health vertical will be associated with the “bad” camp.

 

But what about sites that have many different categories?

A good example of these types of sites are the How-To sites. Sites that typically have many broad categories of information. In these instances, the deep learning process breaks down. Which training data does Google use on these sites? The answer is: It can be seemingly random. It may choose one category or another.

 

For well-known sites, like Wikipedia, Google can opt-out of this classification process altogether, to ensure that the deep learning process doesn’t undercut their existing search experience (aka “too big to fail”). But for lesser-known entities, what will happen? The answer is, “Who knows?”.. So the best piece of advice here is – Stay Niche!

 

For a more detailed explanation on how RankBrain functions, check out this article. If you would like help with SEO for your business, get in touch with our experts today!

 


Anisha Sawant

 

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