Ways that Machine Learning Impacts SEO

Ways that Machine Learning Impacts SEO

When it was revealed last year that Google was using a machine learning tool called RankBrain to contribute to search engine results, it caused somewhat of a commotion in the SEO world because everyone was wondering what type of impact it would have. At present though, the tech industry seems to be focused on machine learning (ML) and bots.

Bots and Machine Learning

Technically, bots are a subset of machine learning known as NLP (Natural Language Processing), and it's believed that ML trends and AI-bots will continue having a substantial impact on SEO in years to come.

The original definition of ML is defined as: “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E." ML isn't by any means new. In fact, it was initially proposed in 1959 as “the ability to learn without being explicitly programmed." In short, ML is where machines have the ability to predict using data models. These data models learn from data, which is being produced continually.

What ML Means for SEOs

Although keywords are a SEOs most influential tool at present - with many SEOs relying exclusively on them for ranking purposes - the introduction of ML to the mix means that they will become less and less effective over time. The Penguin and Panda algorithm updates were also based on machine learning systems that had been designed. As the core ranking systems of search engines are upgraded with newer alternatives, they will continue becoming smarter.

Self-Updating Search Algorithms

It seems like Google's main objective is to apply ML in such a way that its search algorithms will be able to learn and update themselves automatically - and this is where the impact will be felt the most. From the perspective of SEOs, the most noticeable impact is that there would more than likely be far fewer updates such as the ones last year that saw Google ranking sites on smartphones and tablets according to how 'mobile-friendly' they were. That update was implemented by people and it happened without much warning. With ML-based search algorithms, it will most likely evolve somewhat more gradually.

A Welcome Gesture for Reputable SEOs

Machine learning should be a welcome gesture for SEOs who are working reputably because it will give them license to continue doing good work. Google has always said that websites need to meet its technical requirements and contain as much relevant information as possible. This means that sites need to provide useful content and not just keyword-stuffed articles. ML will most likely soon make it even more essential for these guidelines to be met.

Evidence suggests that keyword stuffing has already lost importance. A MarketingProfs study noted, “The correlation between keywords and high search rankings has decreased across the board. More and more high-ranking sites are not using the corresponding target keywords in the body, description, or links, the analysis found. Sites are also using keywords less in URLs themselves, with only 6% doing so in the 2015 study."

Google Will Understand Better

Thanks to the introduction of ML, keywords will simply not be necessary anymore because Google will be able to better understand which sites are the most authoritative for a particular phrase – regardless of whether they use it or not - because the search giant will actually be able to understand the content on each site.

There is in fact an excellent reason why Google continues to pop out major algorithm updates such as Panda, Pigeon and Penguin. Believe it or not, it isn't being done 'just to frustrate SEOs;' instead, it is all about the search company securing its already dominant market share in search by providing the best possible end results for website visitors so that they don't have to still search elsewhere. Each and every algorithm change has been performed with this particular goal in mind, and the introduction of ML has been performed for the same reason.

With every single search now being individualized, it enables users like you to see results that are 100% unique to you - even though you may not have figured out why this is the case.

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