iROAS stands for incremental Return on Ad Spend. It measures how much additional revenue you generate from advertising beyond what you would have earned anyway. Unlike regular ROAS, which counts all revenue from people who clicked your ads, iROAS only counts the extra revenue that happened because of the ads.
The difference matters because some customers would have bought from you even without seeing your ads. Regular ROAS gives you credit for all purchases from ad clicks, including these people who were going to buy anyway. iROAS subtracts out this baseline to show you the true lift from your advertising spend.
Companies use iROAS when they want to know if their ads actually work. It helps them avoid wasting money on ads that look successful but aren't really driving new business. You need to run tests with control groups to measure it, splitting your audience and comparing results between people who see ads and people who don't.
Measuring incremental Return on Ad Spend (iROAS) offers significant advantages for marketers seeking to understand true campaign effectiveness. The primary benefit is that iROAS reveals the actual revenue generated by advertising that wouldn't have occurred otherwise, providing a clearer picture of marketing efficiency than traditional attribution models. This measurement captures cross-channel effects and halo impacts that often go undetected, allowing brands to make more informed budget allocation decisions. Additionally, iROAS testing can uncover surprising insights about channel performance, helping marketers optimize strategies that may appear successful in-platform but lack true incrementality.
However, iROAS measurement comes with notable challenges and limitations. The testing process requires sophisticated experimental design, significant time investment, and statistical expertise to ensure reliable results. Brands must commit to controlled experiments with holdout groups, which can be resource-intensive and may temporarily limit reach in certain markets. The methodology also demands patience, as meaningful results often require extended testing periods and post-treatment windows to capture delayed conversions. Furthermore, iROAS can vary significantly between brands, channels, and time periods, making it difficult to establish universal benchmarks or apply learnings broadly across different marketing contexts.
Consider a hypothetical athletic wear brand spending $50,000 monthly on TikTok ads that show a 3.2x platform-reported ROAS. When they conduct a geo-holdout test measuring iROAS, they discover the channel only drives a 1.8x incremental return when accounting for organic sales and baseline revenue. However, the test also reveals that TikTok ads generate significant lift in their retail partner locations—an impact invisible in direct-to-consumer attribution. This comprehensive view enables the brand to adjust their TikTok strategy and better understand the channel's true value proposition across their entire sales ecosystem.
To measure iROAS accurately, establish controlled experiments using geographic holdout tests. Split your target markets into test and control groups, with typically 70-80% of regions receiving ads while 20-30% serve as holdouts. For example, Inkbox ran Snapchat ads in 80% of the country while holding out 20% for two weeks, then analyzed revenue differences between regions. This approach eliminates attribution bias and reveals true incremental impact that advertising platforms cannot measure through their own reporting systems.
Measure iROAS across all sales channels, not just direct-to-consumer revenue, to avoid underestimating campaign performance. Include Amazon, retail partners, and other distribution channels in your analysis since advertising often drives cross-channel sales. Inkbox discovered that Snapchat ads drove 4.65% lift in DTC revenue, 10.91% lift in Walmart sales, and 5.30% lift in Amazon revenue. Without measuring all channels, they would have missed 56% of Snapchat's total revenue impact, significantly undervaluing the channel's true performance.
Extend measurement periods beyond campaign end dates to capture delayed conversions, especially for high-consideration or high-AOV products. Implement post-treatment windows of 2-4 weeks depending on your typical purchase cycle. Mejuri's upper-funnel Meta test showed modest results initially, but including a two-week post-treatment window revealed iROAS improved by 57%, reaching 1.5X their business goal. This approach is crucial for luxury goods, B2B services, or any products requiring research and consideration time.
Conduct baseline iROAS measurements using your current approach before testing new strategies or channels to enable accurate performance comparisons. Run initial tests to understand existing efficiency, then implement changes and measure against that baseline. Mejuri first measured their bottom-funnel Meta strategy achieving 4% lift at 30% below target iROAS, then tested upper-funnel tactics that delivered 11% lift at target efficiency. This systematic approach helps distinguish between normal performance variation and genuine strategic improvements.
