Looks can be deceiving – this statement could apply to a variety of different situations, including your marketing data. We understand the importance of data-driven decision making in the online space, but sometimes the numbers don’t tell the entire story.
In this post, we’ll examine an area that may warrant extra attention from your analytics team – how to compare earnings per lead (EPL) across different networks.
When you’re deciding which network to use for a given offer, there’s a good chance you might run a split test between two networks, to compare which one performs best. But when you’re analyzing the results, it’s important to realize that the numbers don’t always speak for themselves.
For example, let’s say 1,000 leads ping to both Network 1 and Network 2 in your split test. But, let’s also say that 100 of the leads in each sample were from California. Some networks don’t buy in California, because they cannot service the state, and this can affect the proper interpretation of the data. When calculating total EPL for these networks, you’d need to include these leads in your calculation, even if the network excludes them.
Imagine the total revenue for these two hypothetical networks looked like this:
- Network 1 – $1800
- Network 2 – $1750
If Network 2 doesn’t serve California, and they exclude those 100 leads from their total, then they would divide the revenue by 900 to calculate EPL. If you divide Network 1 by 1000, and Network 2 by 900, you get misleading results:
- Network 1 EPL – $1.80
- Network 2 EPL – $1.94
Looking at this data, a publisher might falsely believe that Network 2 has a higher EPL. But if you adjust for the 100 California leads that Network 2 did not include in their original calculations, you get a different result entirely:
- Network 1 EPL – $1.80
- Network 2 EPL – $1.75
Clearly, in this case, Network 1 is the superior network in terms of EPL. That’s why it’s important to pay attention to the specific details of each network you test, so you don’t end up making decisions based on faulty data.
Data-driven decision making is one of the backbones of any online industry. Thanks to our technology, we can analyze patterns and trends much more quickly and efficiently, and it’s important to use this knowledge to your advantage. But even more critical is understanding that you can’t just blindly trust your data without close examination. If you keep this fact in mind, you may very well discover new ways to improve the margins of your business.
