In the last few years, organizations have been making big investments in digital analytics, but there are still uncertainties about the return on analytics (ROA). While companies are increasing their spend in digital analytics tools and people, we should remember that this only half of the equation. The second half of the digital analytics problem is calculating its impact.

ROA is the positive impact on the organization's profits for the increase in spending in digital analytics. The key here is calculating improved profits thanks to digital analytics minus the original profits that you were getting, multiplied by the period it was used, all divided by the cost of digital analytics. It's very similar to the ROI calculation.

Here's a hypothetical illustration of ROA quantification: You're an online retailer who sells outdoors gear, and manage a digital marketing monthly budget of $340k,
with $3.9mm in monthly sales, for a 1,047% ROI. But, you realize that your current paid search campaigns can still be optimized. Consequently, you invest $36,000 in a media optimizer software to find hidden data insights to improve your paid search marketing efforts, and after 3 months your sales increase to $5mm per month. Obviously, the improvements were made by the whole digital marketing team, but they hadn't been pinpointed until you started using the new software.

Using the calculation logic mentioned above, 12 months of media optimizer software driven analytics will get you a 5,294% return.

CMOs will soon start scrutinizing the impact of digital analytics – as a result of all the money being spent on analytics – demanding to understand what all these tools, services, and people do for the bottom-line. ROA qualification can be you answer to that.