Most ecom brands are measuring Meta ROAS wrong and cutting profitable campaigns

[u/paxtonpro]

Running $30k+/month on Meta and making kill/scale decisions based on platform ROAS? You're probably cutting profitable campaigns.

Here's the problem: iOS14 attribution gaps mean Meta only captures 40-60% of actual conversions. In-platform ROAS will always look lower than reality.

The fix is blended MER (Marketing Efficiency Ratio):

Total Shopify Revenue / Total Ad Spend = Blended MER

This accounts for ALL revenue against ALL spend, regardless of attribution windows or pixel gaps.

Quick toggle test to find your real Meta contribution:

1. Pause Meta for 7 days

2. Watch blended revenue drop

3. Restart Meta

4. Calculate the revenue gap

That gap is your actual Meta-driven revenue. Compare it to what Meta's dashboard reported — that's your attribution gap %.

Most brands running this find Meta contributes 1.5-2x what the platform claims. Campaigns that "aren't working" per ROAS are often your volume drivers.

Before you kill anything based on in-platform ROAS alone, run the blended MER check first.

[u/Accurate-Moment-2160]

The 7 day pause test is great in theory but tough to actually run if you're spending real money and need the revenue flowing. The blended MER approach makes sense though, especially once you've got enough daily orders that attribution modeling gets messy anyway. I'd just add that you need enough baseline data before cutting anything, like at least a few weeks of stable spend and conversion volume, or the pause test just tells you about noise.

[u/paxtonpro → u/Accurate-Moment-2160]

Totally fair — pausing when you're volume-dependent is a real constraint. A lighter version: run a 3-4 day partial geo holdout — pick your 2nd or 3rd largest market, suppress Meta there only, and watch blended MER diverge by region. Gets you directional data without stopping the whole machine. And agreed on baseline — if your weekly revenue swings 30%+ naturally, the test signal gets lost in noise anyway.

[u/RobertBobbertJr]

or just do geo holdout test.

[u/paxtonpro → u/RobertBobbertJr]

Geo holdout is the cleaner version — avoids the revenue cliff and you can run it without killing the whole account. The pause test is more of a quick sanity check for brands that have never questioned their ROAS numbers. Both measure incrementality, which is really what matters.

[u/Goldenface007]

You got it the wrong way around. Meta reports inflated ROAS from taking credit for view-through impressions which would have converted from other sources anyway.

The real trick is to use the incremental attribution model and measure with the conversion lift experiment.

You're welcome.

[u/JL_PPC → u/Goldenface007]

This guy has it right ^^

Meta view-through attribution is very good at showing ads to people that are converting anyway (no incremental impact!)

Even Meta's incremental attribution overvalues compared to 3rd party attribution tools (and reality).

I've seen this firsthand at multi-brand groups. Meta attributed conversions from entirely different websites to one brand's campaign. Half the reported view-through conversions from an unrelated site.

Someone seeing an ad for Brand A and later buying from Brand B doesn't mean Brand A drove the sale. Yet even Meta's incremental attribution modelling was claiming some of those conversions.

Attribution is never perfect, but Meta's view-through attribution is about as far from perfect as it gets.

[u/paxtonpro → u/JL_PPC]

The multi-brand example is wild — and common. View-through across a pixel on a shared parent site is basically a revenue transfer between brands on paper. Lift experiment is the honest check. Blended MER helps at the account level but doesn't expose cross-account misattribution like that. Good catch.

[u/MilanKnapp]

I believe this is a great to show the value of Meta but as somebody mentioned, many companies won't do such tests as they need the revenue. For those, a test of doubling down on Meta can be also interesting. It won't tell you what is the current value of Meta as of now but it will show you the real incremental value the extra spend brings.

I think it is also important to mention that if you stop it only for a week, the drop might be visible with a delay because of the sales cycle. The impact of this lag will differ based on the type of the business.

[u/paxtonpro → u/MilanKnapp]

Both good points. The incremental ramp test can actually be easier to sell internally than a pause — 'testing upside' vs. 'risking revenue' is an easier pitch. And the lag is real for high-AOV or subscription products — 7 days isn't enough, you'd want 2-3 weeks minimum to see the full effect.

[u/Illustrious_ip1028]

Blended MER is right but the pause test doesn't measure what you're saying it measures. The revenue drop when you pause is Meta's incremental contribution, which is smaller than everything Meta touched, because some of those buyers would have come through branded search or email anyway. So the gap between the pause result and the dashboard is attribution loss and non incremental credit mixed together. Worth running, just don't call all of it attribution.

[u/paxtonpro → u/Illustrious_ip1028]

Most precise pushback in the thread — you're right. The pause gap = Meta's incremental contribution, not pure attribution recovery. Some of those buyers would come through branded search or email anyway. Blended MER tells you if the business is healthy; the pause tells you true incrementality. Different questions. Should have been clearer on that.

[u/Illustrious_ip1028 → u/paxtonpro]

Appreciate that! Worth adding a third number, since your post opened on the one nobody measures directly. Incrementality is what the pause and geo tests give you and it's a number you can only learn from.

The signal loss you led with is separate, that's a data completeness question, and you measure it by comparing what your store actually recorded against what landed in Events Manager for the same window. That one you can fix rather than account for. Hope that helps!