Sometimes mistakenly called Return on Investment (ROI), Return On Ad Spend (ROAS) is a commonly used measure to track advertising campaign performance. However, there are several problems with this measure and using it as a Key Performance Indicator (KPI) can lead to misleading results.
Below I provide a definition for ROAS, a few common problems with it, and a solution to measure campaign profit.
The formula for ROAS is
So if our campaign were to generate $10,000 in sales from a $5,000 campaign spend, then our return would be:
This would be a fine result providing that we could deliver the product or service at a profit for less than the remaining $5,000 that we didn’t spend on advertising. But what if it actually cost us $8,000 to purchase the items and deliver them? In that case our 200% ROAS brings us a loss of $3,000 rather than the profit that it seems to suggest.
It’s possible to compensate for this by aiming for larger ROAS values but this brings us to the next problem – large numbers.
It takes a lot more effort for most people to determine the differences between sets of large numbers. For example, take the following sets of numbers:
120% - 1,225% - 1.2
150% - 1,521% - 1.5
125% - 1,249% - 1.3
232% - 2,318% - 2.3
43% - 432% - 0.4
The last column is much easier to identify the differences between the results. This is due to a number of factors, including the complexity of the numbers, and the additional information such as the commas and percentage signs.
Typically for any website selling a product, ROAS must be 500% or more for advertising to boost profits (assuming a minimum of 20% profit margin on the total sale). So large numbers are likely to be needed and analyzing these on a regular basis may end up in the too-hard basket.
Ryan Humm’s recent article on the WebTrends blog stated this problem very well. Like any percentage-based metric, the magnitude of the result in real dollars must be presented in close context to the percentage figure.
After all an impressive ROAS figure of 500% could be the result of either of the following two calculations:
My recommendation is to avoid ROAS as a measure where it is possible to measure actual profit, cost per lead or any more informative measure. If you have to use ROAS, then it must always be shown in context with the actual revenue and campaign costs in direct proximity.
To help you measure your actual profit, Panalysis has created a calculator that does the heavy lifting. The calculator integrates with Google Analytics to extract your e-commerce data, load in your product and advertising costs and calculate your profit. You can find this calculator at http://www.panalysis.com/resources/campaign-profit-calculator.aspx
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