Post-iOS14 Blended Attribution Modeler
Correct platform over-reporting into a true blended ROAS you can bank on.
Your platforms claim 5.25× but true blended ROAS is 3.75×, about 40.0% of over-reporting from overlapping attribution. Apply a ~29% haircut to platform numbers when you scale.
Every platform takes credit for the same conversion, so summed platform revenue routinely exceeds real revenue. Blended, backend-anchored ROAS is the honest number.
About this calculator
Since Apple's App Tracking Transparency rollout, ad platforms lean harder on modeled and probabilistic attribution, and the practical effect is that every platform tends to claim credit for the same conversions your other channels also claim. This calculator compares the sum of what your platforms report against your real backend revenue, quantifying exactly how much of that claimed revenue is double-counted overlap rather than genuinely incremental spend.
How to use it
- Enter platform-claimed revenue, the sum of revenue every ad platform reports across all your channels.
- Enter actual revenue from your backend, store, or finance system for the same period.
- Enter total ad spend across all channels.
- Read the true blended ROAS versus platform-reported ROAS, the over-reporting percentage, and the double-counted revenue figure.
Methodology
Platform-reported ROAS is platform-claimed revenue ÷ ad spend, and true blended ROAS is actual backend revenue ÷ ad spend, the same denominator, two different revenue numerators.
Over-reporting is how much platform-claimed revenue exceeds actual revenue, expressed as a percentage, and double-counted revenue is that same comparison in currency, claimed minus actual.
A correction factor is derived as true blended ROAS ÷ platform ROAS, giving you a single multiplier to discount platform-reported numbers toward reality when comparing across periods or making budget decisions.
Anything above roughly 15% over-reporting is flagged as inflated. This threshold is a practical planning heuristic, not a precise statistical cutoff, some overlap between platforms is normal and expected even with clean tracking.
FAQ
They compute similar math but for a specific reason: this tool is framed around the post-iOS14 tracking problem specifically, comparing what platforms claim in aggregate against verified backend revenue to isolate the double-counting effect that modeled, probabilistic attribution introduced. Use it when you specifically suspect platform over-reporting from privacy-driven attribution changes, rather than as a general MER check.
With less device-level tracking available, platforms shifted toward modeled conversions and broader attribution windows to fill the gap, which increases the odds that a single sale gets attributed, and counted as revenue, by more than one platform simultaneously.
Apply it as a rough discount when a platform reports a ROAS or revenue figure for planning purposes, treating the raw platform number as the reliable one leads to over-scaling budget on inflated numbers. Recompute the correction factor periodically since the gap tends to drift as channel mix and platform attribution methods change.
Usually, yes, if the gap is large and consistent across many periods. A modest, stable gap can simply reflect normal multi-touch overlap. A gap that keeps widening, or is unusually large versus your historical baseline, is the stronger signal that attribution has genuinely degraded and platform numbers need heavier discounting.