5 Ways Machine Learning Should Change the Way You Do SEO

Machine learning is already changing the way we optimise for search engines and things look ready to quickly develop in 2018. If you’re not already preparing to power your search marketing efforts with machine learning, then now is the time to get familiar with the technology and implement it into your workflow.

It’s not only a case of adapting for Google and the other platforms you depend on, as they become increasingly powered by machine learning. It’s also about making the most of your data and stripping out the inefficiencies of your existing marketing strategy.

Perhaps the biggest impact we’ve seen from machine learning so far is the automation of SEO analysis at a scale that far outperforms that which people can do on their own. SEO has become more and more burdensome over time, with ever-increasing complexity and need for analysis. Machine learning means that continual, consistent analysis can be running in the background, working at depth and scale; and leaving you more time for implementation and creativity.

You don’t need to spend time running the same reports and analysis every week or month anymore. These reports can be automated and all you need to do is address any issues or opportunities they detect. In fact, you can even automate many of these fixes while you’re at it.

By automating repetitive tasks with machine learning, you can more time on creating content that guides users along the consumer journey. After all, this is where your priorities should really be in the first place.

Aside from freeing up resources to focus more on content, machine learning can help identify decide the kind of content to create for specific goals and user intents.

For example, machine learning can be used to answer the following questions:

We’re not talking about individual pieces of content either. We’re talking about a consumer journey built up from hundreds or thousands of pieces of content and a wide range of user interactions – something that’s incredibly difficult for a human to view and analyse as a single entity.

However, machine learning can process this entire roadmap and provide you with valuable insights. It can tell you that users respond better to a certain kind of blog post after signing up to your email newsletter, for example. Or highlight a piece of content that’s actually adding friction rather than encouraging conversions.

As things stand, your typical marketing strategy caters for traffic from search, social and third-party sites with email marketing and paid advertising nurturing leads along the way. Mapping out the consumer journey across these platforms can be tricky enough but we’re facing a near future where platforms like Google Assistant, Alexa and various other platforms claim their place in the consumer journey.

It’s not only the growing number of platforms you need to think about, but how people use them and access content. When people turn to Google Assistant with a voice search, they’re not going to get a full list of SERPs in return for their query. In many cases, they won’t even visit a website to complete their task (e.g.