tech seo boost

This year’s TechSEO Boost, an event dedicated to technical SEO and hosted by Catalyst[1], took place on November 29 in Boston.

Billed as the conference “for developers and advanced SEO specialists,” TechSEO Boost built on the success of the inaugural event in 2017[2] with a day of enlightening, challenging talks from the sharpest minds in the industry.

Some topics permeated the discourse throughout the day and in particular, machine learning was a recurring theme.

As is the nature of the TechSEO Boost conference, the sessions aimed to go beyond the hype to define what precisely machine learning means for SEO, both today and in future.

The below is a recap of the excellent talk from Britney Muller, Senior SEO Scientist at Moz, entitled (fittingly enough) “Machine Learning for SEOs.”

What is machine learning? A quick recap.

The session opened with a brief primer on the key terms and concepts that fit under the umbrella of “machine learning.”

Muller used the definition in the image below to capture the sense of machine learning as “a subset of AI (Artificial Intelligence) that combines statistics and programming to give computers the ability to “learn” without explicitly being programmed.”

definition what is machine learning

That core idea of “learning” from new stimuli is an important one to grasp as we consider how machine learning can be applied to daily SEO tasks.

Machine learning excels at identifying patterns in huge quantities of data. As such, some of the common examples of machine learning applications today include:

  • Recommender systems (Netflix, Spotify)
  • Ridesharing apps (Uber, Lyft)
  • Digital Assistants (Amazon Alexa, Apple Siri, Google Assistant)

This very ubiquity can make it a challenging

Read more from our friends at Search Engine Watch