How Machine Learning Will Influence the Future of SEO

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Back in the old days of Search Engine Optimization (“SEO”), a simple change like adding a keyword tag meant something – you could usually make it to the top of the SERPs by using the same keyword over and over in the website’s title or keyword tag. That was back when exact match results were the only ones returned from consumers’ searches, and crawlers like Google spent 99 percent of their time crawling and indexing instead of actually cataloging and evaluating the content’s quality and relevance.

After those times, SEOs spent their time trying (mostly in vain) to interpret the newest iteration of Google’s search algorithm, trying to guess the magic code. Despite the mountains of SEO tips, and “best practices” online cheat sheets available today, there is still a mystery surrounding what exactly gets a website to the top search result.

Martech recently conducted a survey of 150,000 different SERPS, and based on a simple scoring model, the majority of the top three results didn’t follow even half of the best practice rules commonly found in the ranking feature lists. They extracted 83 features from each of the SERPS (page speed, content length, link scoring, content density, social signals, etc.) and used different models in an attempt to reverse-engineer the algorithm.

Unfortunately, the extracted features failed to provide any meaningful explanations as to why certain results landed in the top of the SERPS, and others failed to do. In fact, websites that were in the top of the SERPS were just as poorly optimized as those in later pages.

So why is it impossible to reverse-engineer Google’s search results?

As Google’s RankBrain gets smarter in understanding users and their intent, it’s also learning to better understand content, information and if that content will provide the right answer, not only to the query, but also the individual user. With the algorithm now truly understanding the query intent on a linguistic level, it can deliver new kinds of results that are correlated and weighed in a way that a human brain can’t even begin to predict. This dramatically changes both technical SEO and content SEO.

Previously, technical SEO was the purview of techies that fixed links, optimized title tags, and ensured correct markups. However, now that work needs to be completed at the beginning of a website build and audited and monitored by a web team on an ongoing business.

Instead, the true technical SEOS of the future need to understand more than just HTML and XML; they need to understand how machine learning works, how Google handles data and weighs inputs, and how to understand and train models. The next generation SEO practitioner will be closer to software developer and statistician than a web designer.

With advances in machine learning, the next frontier of content marketing will revolve around machine learning models and linguistic analysis; content will be scored to ensure it truly answers the consumer question, instead of just telling a brand story.


Are you looking to improve your company’s online presence? Investing in SEO services and social media management can help bring in new customers by making your business easy to find. Contact pm@telxweb.com for more information on helping your business grow with search engine optimization. 


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