A couple of years ago, I was invited to speak at the SMX Advanced conference in Seattle on the topic of SEO and competitive intelligence. It is an area of SEO I’m passionate about, not only because it is one of the most difficult things in SEO to scale and do right, but also because it is one of the foundations of a good SEO program.
Before I dive into outlining one of the advanced approaches to SEO analysis that I shared at the conference, it’s important to understand the genesis of the approach.
Before I was building the machine-learning algorithms behind our Enterprise SEO platform, I spent a number of years building and running an Enterprise SEO consulting firm and agency. We were a small team (less than 15 people at the time), but we were growing quickly.
One of the biggest challenges we faced was being able to scale the task of conducting in-depth research into a client’s situation as quickly and as consistently as possible — irrespective of the team member working on it. From learning about the client’s business lines and the terminology used in their industry to understanding the key industry players/competitors/influencers in the space, research formed the basis of all our planning and tactics for the client.
When running an agency (in-house or external), you have to figure out processes that are repeatable and scalable. This is the hallmark of teams that excel at delivering stellar results versus those that fail despite a tremendous amount of effort. Since research forms the bedrock of any good SEO team, getting good at doing it right was essential to our growth and success.
Research (and analysis) is a complex and time-consuming task, whether it’s keyword research, influencer research or even competitive research. The problem with any kind of research is that the quality of research “depends.” It depends on.Read More…
Source : Search Engine Land