Learn about the 3 stages of SEO Automation

The SEO industry has a problem of overwhelming lack of resources and this problem become more visible at the enterprise level where data sets are vast, dense, and complex which makes it more difficult to make sense of the data and act accordingly. There are also a great number of SEO tools to find out the SEO issues, but there are those tools that lack the ability to “do SEO”. Marketers will be able to reduce the time from data to insights to action if they automate the SEO. The main challenge that enterprises face is getting things done.

A survey done by Distilled in 2016 has found that the majority of SEOs didn’t see their recommendations implemented for nearly 6 months after they were requested. The Head of SEO at Great Learning, Ramesh Singh has commented “What SEO function/task do you most wish you could do faster and at a bigger scale than you can now?”, which also echoes the same problem.

On the other hand, Google has become more intelligent by using machine learning and AI to serve users the most relevant information in the most effective way. There is too much data for a human to work on it. This is why automation works around the clock and can generate insights that would otherwise take hours to reach. 

Most SEO’s face human limitations in their ability to sort through data and act on insights at the level that’s required today. Wherein AI and machine learning can do it with proficiency. If you are thinking about taking the benefits of automation, then you need to start with the basics before moving on to automated insights and after that, you will be able to get automated execution.

At the beginner level, automation will start from pulling together data sets and knowing what to do with that data. In the intermediate part, SEOs will be able to prioritize their time where it counts and let the technology surface site-specific, actionable insights for them. In the last part, SEO automation is executed and tested.