SEO vs Machine Learning Algorithms
The way Google ranks pages in its search results today is much different from the way it ranked them two years ago. Machine Learning Algorithms have changed the game of SEO completely.
How Machine Learning Algorithms Impact SEO
In early 2015, Google began its initial rollout of their new ranking algorithm: RankBrain. RankBrain is a machine-learning artificial intelligence system that helps process search results as part of Google’s ranking algorithm. As of June 2016, RankBrain is being used for all Google queries.
But how does machine learning impact rankings exactly? That’s the big question.
SEO (Search Engine Optimization) used to be all about building links and using the right keywords, but not over using them. Links and keywords still matter, but machine learning has transformed the traditional SEO ranking model into something new.
A searcher enters their query. Google returns a set of relevant organic search results that are largely based on conventional ranking factors. Machine learning then becomes a “layer” on top of this. It becomes the final arbiter of rank — quality control, if you will.
It’s like Google is saying, “Great, I’ve successfully crawled and indexed this page. The page exists on a strong domain (it has a high level of expertise, authoritativeness and trust). The content is optimized, understandable, relevant and matches the searcher intent. BUT do any humans click on the result and engage with it?” This is when the content centric search and semantic search algorithms come into play.
SEO New Ranking Model
This last sentence is the key.
“Perfect SEO” is pretty imperfect if you’ve created content that ranks on search engines but doesn’t get any clicks.
It doesn’t matter how many links you have pointing at your page or if it’s optimized with all the right keywords — if the engagement is too low, then you’re out.
Of course, you won’t be out immediately. Google will continue auditioning your page for relevant queries… for a time. But if it fails to attract engagement, it will continue to die a slow death. It could lose 3 percent of traffic per month — so small you don’t even notice it until it’s too late. Eventually, your page will simply fall out of ranking contention.
To quickly review, before RankBrain rolled out, you may have had pages that ranked well but really didn’t deserve to. Even though they had low engagement, it didn’t hurt your organic traffic in a noticeable way.
Why Machine Learning is the Future of SEO
Machine-learning is the future to SEO. The relationship between time on page and organic search traffic is changing. Something algorithmic is happening and in real time.
Conventional SEO ranking factors (e.g., relevant content, keyword alignment, links to your domain, domain strength) determine how the SEO.
Clearly, you want to have as many pages as possible with excellent, unicorn-level engagement metrics. These will be your most valuable pages — and should pass Google’s machine test.
You also want to find your most at-risk content because if you don’t meet the minimum engagement, you’ll be out.
How to Utilize Machine Learning to Your Site's Benefit
Clearly, you'll want to have as many pages as possible with excellent, "unicorn-level" engagement metrics. These will be the most valuable pages — and should pass Google’s machine test.
You also want to find your most at-risk content because if you don’t meet the minimum engagement, you’ll be out.
Again, this is just my theory at this point, based on some pretty compelling examples — but nothing involving Google’s algorithms can be 100 percent conclusive.
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