ROAS stands for Return on Ad Spend. It's a ratio that tells you how much revenue you generate for every dollar you spend on advertising. You calculate it by dividing the revenue from ads by the amount you spent on those ads. If you spend $100 on ads and make $300 in sales, your ROAS is 3:1.
Companies use ROAS because they need to know if their advertising actually makes money. Without this measurement, you're spending blindly. You might think an ad campaign is working because people are clicking or engaging, but if it's not generating more revenue than it costs, you're losing money. ROAS cuts through vanity metrics and shows the bottom line impact.
The metric helps you decide where to put your advertising budget. If Facebook ads give you a 4:1 ROAS and Google ads give you 2:1, you know where to spend more money. You can also use it to test different ads, audiences, or campaigns against each other. It's not perfect—it doesn't account for long-term customer value or brand awareness—but it gives you a clear picture of immediate financial returns.
Return on Ad Spend (ROAS) is a widely used metric that measures the revenue generated for every dollar spent on advertising. While valuable for budget allocation decisions, ROAS has significant limitations that marketers must understand to make informed decisions about their advertising effectiveness.
The Benefits of ROAS Measurement
ROAS provides marketers with immediate, actionable insights into campaign performance and budget efficiency. It offers a straightforward way to compare the relative performance of different channels, campaigns, and time periods using a simple revenue-to-spend ratio. This simplicity makes ROAS particularly valuable for quick decision-making and communicating results to stakeholders who need clear, digestible metrics. Additionally, ROAS can be calculated at various levels of granularity, from individual ad sets to entire marketing programs, providing flexibility in analysis and optimization.
The Drawbacks of ROAS Reliance
However, ROAS suffers from fundamental attribution problems that can severely mislead marketing decisions. Platform-reported ROAS often inflates performance by crediting conversions that would have happened anyway, without distinguishing between correlation and causation. For example, a customer searching for "Nike running shoes" who clicks on a Nike ad was likely already intending to purchase, yet the platform claims full credit for that conversion. ROAS also fails to capture cross-channel effects and longer-term brand building impacts, potentially undervaluing channels that drive awareness but don't immediately convert. Furthermore, ROAS doesn't account for customer lifetime value differences or incremental vs. baseline sales, leading to optimization toward easy conversions rather than true business growth.
A Real-World Example
Consider a hypothetical fitness apparel company spending $100,000 monthly on Meta ads with a reported 4:1 ROAS ($400,000 in attributed revenue). The marketing team feels confident about performance and increases spending. However, when they run an incrementality test using geo-holdouts, they discover that their true incremental ROAS is only 2.5:1 – meaning 37% of their attributed revenue would have occurred without the ads. This revelation shows they were overspending by $25,000 monthly on Meta while potentially underinvesting in other channels that appeared to have lower ROAS but actually drove more incremental growth. The incrementality test reveals the platform was taking credit for customers who were already planning to purchase, leading to misallocated budget and missed growth opportunities.
ROAS (Return on Ad Spend) is calculated by dividing total revenue generated by total advertising spend, expressed as a ratio or percentage. For example, if you spend $10,000 on YouTube ads and generate $34,000 in revenue, your ROAS is 3.4:1 or 340%. However, platform-reported ROAS often inflates performance—YouTube campaigns in Haus's study showed platform metrics underreported true impact by 70%, with actual incremental ROAS (iROAS) being 3.4x higher than reported figures.
Platform-reported ROAS measures correlation, not causation, often crediting ads for conversions that would have happened anyway. Incremental ROAS (iROAS) measures only the additional revenue directly caused by your advertising. For instance, Javy Coffee discovered their top-of-funnel Meta campaigns were 13x more incremental than bottom-funnel campaigns despite similar platform-reported performance. This distinction is critical—a campaign showing strong platform ROAS might have an incrementality factor of only 0.6, meaning 40% of attributed conversions weren't actually incremental.
The most reliable way to measure true ROAS is through geo-based holdout testing, where you expose one group to ads (treatment) while withholding ads from a similar control group. For example, a fitness brand testing Instagram ads might find their treatment group converts at 5.2% versus 3.8% for the control group, revealing 36.8% incremental lift. This method accounts for omnichannel effects—YouTube ads in the Haus study drove 99% additional sales lift beyond direct-to-consumer impact when including Amazon and retail channels.
Effective ROAS measurement requires proper test design and timing considerations. YouTube's impact improved by 79% during post-treatment observation windows, highlighting the importance of measuring delayed effects rather than immediate attribution. Set appropriate test durations based on your sales cycle—high-AOV products need longer observation periods. Use incrementality factors to calibrate platform metrics: if TikTok reports 1,000 conversions but your test shows an IF of 0.6, only 600 were truly incremental, requiring you to adjust your target platform CPA from $150 to $90 to achieve true performance goals.
