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Can we machine-learn Google’s machine-learning algorithm?
As Google becomes increasingly sophisticated in its methods for scoring and ranking web pages, it's more difficult for marketers to keep up with SEO best practices. Columnist Jayson DeMers explores what can be done to keep up in a world where machine learning rules the day.
Google’s rollout of artificial intelligence has many in the search engine optimization (SEO) industry dumbfounded. Optimization tactics that have worked for years are quickly becoming obsolete or changing.
Why is that? And is it possible to find a predictable optimization equation like in the old days? Here’s the inside scoop.
The old days of Google
Google’s pre-machine-learning search engine operated monolithically. That is to say, when changes came, they came wholesale. Large and abrupt movements, sometimes tectonic, were commonplace in the past.
What applied to one industry/search engine result applied to all results. This was not to say that every web page was affected by every algorithmic change. Each algorithm affected a specific type of web page. Moz’s algorithm change history page details the long history of Google’s algorithm updates and what types of sites and pages were impacted.
The SEO industry began with people deciphering these algorithm updates and determining which web pages they affected (and how). Businesses rose and fell on the backs of decisions made due to such insights, and those that were able to course-correct fast enough were the winners. Those that couldn’t learned a hard lesson.
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