When understanding the basics behind SEO there is usually a general theory that increased rankings will translate into increased revenue. Is this always the case? Maybe, maybe not. We must first understand how we achieve revenue-generating conversions.
The problem with many SEO campaigns is that only rankings and traffic are the core focus. And frankly that is all many SEO companies report on. Let’s take a look at Eric Peterson’s Web Analytics hierarchy of needs model to better understand the full spectrum of what is really important to complete the life cycle of effective online marketing solutions.
In this graph you can see that most campaigns focus on data such as ranking movements for keywords and the resulting boosts in traffic. But what is this data telling us and how can we better understand what insights the data is providing?
Data can be exported into excel models or used in various analytics tools that will help you understand what is going on. This is where you can really dig into each keyword (both broad and long tail) to comppare conversion rates and how that effects revenue. That is why we need to really interpret the data and look for those key insights.
For example, let’s say your website sells shoes. You have two keywords ranking on page one of Google: “men’s running shoes” and “men’s sport shoes”. Consider what it would mean of “men’s running shoes” was generating 50 conversion per month in position number 3, and “men’s sport shoes” was generating the same number of conversion in position number 7. That could possibly tell you that if you focus on increasing the ranking for “men’s sport shoes” then you could potentially drastically increase those conversion for that term.
The idea is to have a system that is sophisticated enough to follow the path from rankings and traffic all the way to conversions and true ROI. Once you have this system in place you can dial down on each keyword (and long tail variations) and assess conversions/revenue per keyword. There are many different tools that can be used each step of they way, but it really takes a lot of manual testing and experimentation to get it right.