A Visual Blog

In previous posts, I’ve tried to explain the reasons behind the frustrating fact that some report data just won’t ever match. This week’s topic is a no-brainer. To best describe why reports created by pulling data from different data sources won’t match other reports, let’s see it visually.

So, why is this a problem? Say you haven’t configured your web analytics to track your PPC, or maybe an agency is managing your PPC, but you have not given them access to your web analytics, so you must rely on the data the search engines provide. Inevitably, someone in your organization is going to want a roll-up or an executive summary of all the engines. The result is then the creation of a report from disparate data sets.

The problem – each vendor report is not aware of the other vendors. So, in the example below, each vendor report will claim credit for the entire purchase and claim all of the revenue.

As you can see, this greatly overvalues the conversion and creates an unrealistic view of the performance.
If you do try to compare the compiled report to your web analytics, there will be a problem as to how web analytics will credit that sale, as you can see below.

The real need is to conceptually ‘divide up’ the order and revenue and give everything credit.

By thinking about dividing up credit, you more accurately value the contribution of each advertising source. With this accurate and comprehensive picture, you can really optimize your spending, ensuring that you focus your spend, time and attention on what truly is working. What you may then find clicks (and impressions) that occur at the very beginning of the ‘funnel’ are getting the credit they deserve, so you may be able to increase bids on your more general keywords or show true ROI on banner impressions.