Return on Ad Spend (ROAS)
Date created: Nov 4, 2020 • Last updated: Nov 12, 2020
What is Return on Ad Spend?
Return on Ad Spend (ROAS) is a marketing metric that quantifies the total revenue generated for every dollar spent on advertising. In other words, ROAS measures the effectiveness of your advertising efforts by comparing total ad spend on campaigns to the revenue from those campaigns.Alternate names: Return on Advertising Spend
How to calculate
For example, Corey’s Cyclery spent $2,500 on advertising in the month of July through their PPC, Affiliate, and Display Campaign. The campaign resulted in $10,000 in revenue. Therefore, the July ROAS is equal to $10,000 / $2,500 or $4, which means that for every dollar spent the business generated $4 in revenue. This is equivalent to a return of 400%.
Return on Ad Spend
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What is a good Return on Ad Spend benchmark?
ROAS does not have a single definition of “good” as it is influenced by profit margins, operating expenses and can even be channel, campaign, or tactic dependent. However, it is generally better to have a higher ROAS.
More about this metric
Return on Ad Spend measures the effectiveness of your advertising spend as a percentage or dollar value. ROAS can be used as an aggregate metric to measure the overall performance of a campaign, or as a measure of performance of individual campaign tactics. Either way, this metric gives you better insight into which campaigns or campaign groups are delivering the greatest return and which require optimization or reallocation.
Often confused with the larger umbrella term ROI, ROAS can be considered an advertising-centric or tactic-specific evaluation metric as part of the wider ROI definition. In other words, while ROAS measures the advertising specific costs to deliver a set campaign, ROI is a more global business metric that takes into account additional costs to derive its quantification and is generally applied to larger strategic initiatives.
Nevertheless, there are a few individuals that also like to include the costs to produce and deploy the ads. In such cases, the formula would be adjusted to be: (Revenue - Costs) / Ad Spend. However, these costs are often more volatile and difficult to capture accurately, which adds further complexity for little incremental benefit.