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ROAS and marginal ROAS Benchmarks for Google, Facebook, Instagram and TikTok
What are the average ROAS values across channels, and why are they often underreported? We break down the differences with real benchmarks for major channels.
Measuring advertising effectiveness is critical for marketers, but it’s not always simple. At the core is return on ad spend (ROAS), a metric showing how much revenue you generate for every dollar spent on ads.
On the surface, ROAS looks simple to calculate, but in practice, it’s often misunderstood, inconsistently measured, and sometimes underreported.
Different attribution models and measurement frameworks can paint very different pictures of the same campaign, leading to confusion about what’s truly driving performance.
In this post, we explain what ROAS and marginal ROAS mean, why it’s often reported inaccurately, ROAS benchmarks vary depending on the methodology you use, and how to get a more accurate view of advertising effectiveness.
Here’s what you’ll find:
Return on ad spend is a key metric that measures the revenue generated for every dollar spent on advertising. It helps businesses understand whether their campaigns are profitable and how efficiently their ad budgets are being used.
For example, if you spend £1,000 on a campaign and it generates £5,000 in revenue, your ROAS is 5:1 (or 500%). That means, for every dollar invested in advertising, you’re earning 5 pounds back.
While ROAS tells you how effective your advertising is overall, marginal ROAS (mROAS) goes one step further.
Instead of looking at the total return, it measures the incremental revenue generated by the next dollar of ad spend. In other words, it answers the question: “If I increase my budget, how much additional revenue will that extra spend bring in?”
This distinction is important because advertising returns don’t scale linearly. As budgets increase, returns often diminish, making marginal ROAS a more precise metric for optimising budget allocation across channels and campaigns.
Businesses generate revenue through many avenues, paid ads, organic search, offline activity, and outbound sales. When these influences overlap, isolating the true return from advertising becomes far more complex than the formula suggests.
The complexity becomes even more clear when you look at the measurement approaches marketers typically rely on, such as multi-touch attribution (MTA) and marketing mix modeling (MMM).
MTA is inherently click-based, tracking user journeys across touchpoints that lead to a measurable click before conversion. While effective for lower-funnel, intent-driven campaigns, MTA tends to undervalue upper-funnel channels like TikTok or Facebook prospecting, where ad impressions influence buyer behavior without generating immediate clicks.
These impression-driven contributions are often invisible in MTA’s framework, leading to ROAS figures that understate the channel’s true impact.
MMM, on the other hand, relies on statistical modeling to measure the incremental effect of all marketing activity over time. By capturing both click-based and impression-driven engagements, MMM provides a more complete view of how ads generate awareness and demand.
It also helps deduplicate revenue that multiple platforms might otherwise claim credit for. The result is a fairer, often higher, picture of ROAS, one that better reflects the actual contribution of each channel to overall business growth, though it does sacrifice the granularity that MTA provides.
To show how each methodology shapes results, here’s a table of ROAS benchmarks across different methodologies:
| Channel | Last Click ROAS | Data-driven impressionROAS | MMM ROAS | MMM marginal ROAS |
| TikTok Prospecting | 0 | 2.86 | 2.1 | 1.4 |
| Facebook Prospecting | 0 | 2.55 | 4.1 | 2.6 |
| Instagram Prospecting | 0 | 2.35 | 2.3 | 1.2 |
| Google Pmax | 0.6 | 0.87 | 2.3 | 0.9 |
| Google Non Brand | 0.4 | 0.8 | 1.2 | 0.4 |
The differences are striking. Depending on the model you use, the same channel can look like a loss or a growth driver. Here’s why these numbers vary so much:
If you’re not meeting industry ROAS benchmarks or you want a clearer picture of your results, try these proven strategies:
Each measurement method tells a different part of the story. Last click shows which campaigns and channels push people over the line.
DDA + impression modelling fairly weights click paths while factoring in impression influence.
MMM takes it further by capturing incremental impact over time and adjusting for saturation so you know where the next pound works hardest. Combining these perspectives gives you a holistic view of channel performance.
Looking at ROAS in a single platform, like Meta or Google Ads, creates a siloed view. Customers move across multiple channels, so crediting one platform rarely reflects reality.
Blended ROAS, powered by attribution and MMM, solves this. Attribution shows the click path and how channels work together, while MMM consolidates everything and reveals diminishing returns across the full mix.
Not all conversions happen via the same method. Beyond form fills, customers engage through calls, live chat, social media, email, and even offline events. If you’re only tracking one type, you’re missing key revenue drivers.
Capturing every conversion source ensures your ROAS calculations reflect true performance, and helps justify more ad spend where it works.
Getting an accurate picture of ROAS isn’t as simple as plugging numbers into a formula. Different attribution models, from last-click to MMM, can tell completely different stories.
While last-click undervalues upper-funnel channels, MMM and impression-based models reveal the real incremental impact of your ads. Marginal ROAS goes even further, showing where your next pound works hardest.
Our platform combines multi-touch attribution, impression modelling, and MMM so you can see what’s driving revenue across the entire funnel, not just the last click. Book a demo today and start making smarter budget decisions.
A “good” ROAS depends on the channel, campaign type, and measurement model. For example, a typical Facebook prospecting campaign can see a marketing mix modelling (MMM) ROAS around 2.6, while Google Performance Max campaigns average 0.9 MMM ROAS. Benchmarks vary, so it’s important to compare against your own costs and margins rather than a single number.
A 2x ROAS can be considered solid for some channels, like Instagram prospecting (MMM ROAS ~1.2) or Facebook prospecting (MMM ROAS ~2.6), but may be low for highly efficient channels like Google Non-Brand (MMM ROAS ~0.4). Always consider your profit margins and campaign objectives alongside ROAS.
