How Machine Learning is Changing the Face of Search

Generally Google doesn’t spring to mind when considering competition in the world of digital marketing because it seems to dominate whatever it touches.

Aside from that however, the realm of digital marketing has always been an extremely competitive landscape, with certain exceptions of course. Established brands with long standing trust frequently held the top SERP positions, while new domains had to take a place at the back of the line. Black hat SEO made it possible for webmasters to play the system and produce high ranking for substandard content. In the recent past, SEO providers and webmasters could apply trending keywords and simple heuristics to achieve rank regardless of content quality or relevance.

These concepts were entirely changed by the Hummingbird update and the unveiling of RankBrain.
These two things should be changing the SEO world’s ideas about how to achieve success as well. Although many SEO providers understand how important RankBrain is, or at least will be in the future, they still cling to the conventional strategies that worked a decade ago.

It’s time to rethink your views about search engine optimization and there are several SEO strategies and machine learning applications that can help you stay competitive in this constantly changing landscape.

How Machine Learning is Changing Search

RankBrain is, according to Google, the company’s 3rd most important factor in ranking. It is used to decipher the context of searches that it hasn’t received before. It distinguishes the context by comparing semantically similar keywords with similar searches from the past and delivering the results that are most relevant.

Through the use of machine learning, patterns can be found and user engagement data analyzed. Through this data, an algorithm can be used to evaluate user intent. This allows results to be filtered more effectively and gives users a better overall experience.

As of today, conventional signals still apply in ranking the best results. With each relevant search however, machine learning is able to analyze which of the pages involved are getting the most favorable user signals and deliver the best results for meeting user intent. It is important to remember however, that machine learning is a slow process. The result would be slow changes in ranking that are based on a growing amount of data from the SERPs.

In the more competitive niches, increased user engagement and content quality will steadily overshadow conventional signals and level the playing field. In lower volume searches, the conventional ranking signals will remain as the standard until sufficient data is gathered and user intent can be determined.

Humans aren’t being Replaced Yet

Not to worry, automation isn’t going to replace humans in the near future. Machine learning can be used to help boost marketing campaigns, but the actual creation and execution will ultimately rely of human intelligence. The same rules still apply to SEO.

Provide a good user experience
Provide solid content boosted by good keywords
Employ natural language
Personalize the journey

The big difference may be in how we provide these things to potential buyers. The technologies that are being developed every day can potentially allow for great improvement in the competition for SERPs and allow today’s digital marketer to deliver a much stronger product.

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