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Machine Learning In SEO Industry
Non-traditional SEO Tactics
As we progress into 2016, traditional SEO tactics like meta tags, link profiles, robots.txt, H1 optimization, canonicalization, and more are going to be disrupted by new trends in the search industry. One such developing trend is machine learning, a form of artificial intelligence that enables computers to learn without being programmed by a human. In machine learning, computers adapt and grow in response to outside forces such as human interactions, social media, etc.
Self-driving cars are an illustration of machine learning – they are meant to respond to their environment. The cars are programmed, but the programming has gotten them to the point where they can process stimuli and effectively make decisions in real time to maximize safety, fuel efficiency, and so on.
Another example of machine learning can be found on Facebook, which has changed from the EdgeRank algorithm to a new system that is meant to observe user behavior and prioritize news feed content for each individual user based on what they prefer to see. For example, users who watch a lot of videos will see many more videos in their news feeds than users who rarely engage with video content. The newer algorithm also learns who a user’s closest friends are and shows them more of their friends’ posts.
Google uses machine learning technology as well. They employ it to constantly improve and refine their users’ search experience. While machine learning is bringing changes to the search industry, it is not a new concept. SEO is a part of everything in the business world – it’s ubiquitous. Google’s RankBrain algorithm has been adapting itself to searches for a while now.
Back in 2007, link spam was rampant because Google’s algorithm favored websites that had many links to other sites across the Internet. But all of that has changed in the last three years; nowadays, content is king. Search engines aim to give the user what they want, a process which goes much deeper than using simple keywords. Rather, search engines focus on whole phrases and more recent content and reward websites that are up-to-date and informative. Machine learning was first used in 2012, when Google utilized it to optimize advertising. Since then, it has been incorporated into their search algorithm to determine site ranking factors. Increased user engagement is what matters most to these machines, so SEO practitioners and business owners need to emphasize serving the user by providing quality information on their websites.
Even with the rise of machine learning, SEO best practices will not change overnight. The changes will be gradual and adaptive; there is no need to panic about robots taking over the world. Artificial intelligence and machine learning are still here to serve humans and human interests. They learn what humans want so that they can give it to us.
The bottom line is, SEO practitioners should continue optimizing their sites for human use. Happy users are the ultimate end goal. This is where user experience (UX) designers come into the picture; they can help SEOs by performing research, user testing, etc. When building and maintaining any website, the emphasis should be on content that users will enjoy, appreciate, and/or find useful.
While machine learning is making our computers and algorithms smarter, there is no cause for alarm because we all have the same goal: attracting more users and retaining them in the future.