What is iROAS?

Reported ROAS divides the revenue a platform attributes to itself by what you spent. iROAS divides the revenue that would not have existed without the advertising by the same spend. The difference is incrementality, and on lower-funnel channels it is usually the majority of the reported figure — a platform counts every conversion that touched its ad, including the customers who were already coming.

The gap is widest exactly where reported ROAS looks best. Branded search, retargeting and remarketing all reach people who have already demonstrated intent, so a high proportion of their attributed conversions would have occurred regardless. Published experiments have repeatedly found near-zero incremental return on branded search while attribution reported figures many times higher, which is why a channel's apparent efficiency is a poor guide to whether it is worth funding.

It cannot be computed from attribution data at all, and this is the point most worth understanding. Attribution allocates credit among touchpoints that appear in observed conversion paths; it has no view of what would have happened without them. Establishing incrementality requires withholding the advertising from someone — a geo experiment, a conversion lift study, or ghost ads — or a model calibrated against one of those.

The number that matters for budget decisions is the marginal iROAS rather than the average, and the two are routinely conflated. Average iROAS tells you what the whole spend returned. Marginal iROAS tells you what the next pound returns, which because of diminishing returns is always lower. A channel averaging 4.0 can have a marginal return below 1.0 at current levels, meaning it is profitable overall and unprofitable to increase — a distinction that decides whether to scale or hold.

Two practical cautions on reporting it. An iROAS estimate comes from an experiment with a confidence interval, and geo tests produce wide ones, so a point estimate quoted without its range overstates what is known. And it is measured over a window: a campaign that pulls purchases forward looks incremental during the test and nets out over the quarter, which is what the cooldown period in a geo test exists to catch.

An advertiser measures three channels with geo experiments and compares the results against what the platforms reported. Gross margin is 38%, so break-even marginal iROAS is 2.63.

The ranking inverts completely, which is the ordinary result rather than a dramatic one. Branded search reports 11.4 and delivers 0.9 — it is capturing customers who were already searching for the brand, and the attribution system faithfully credits every one. Prospecting social reports 2.1 and delivers 3.4, because it reaches people who had not yet decided and much of its contribution never shows up in a last-touch path. Against a 2.63 break-even, only prospecting social is clearly worth scaling. Two cautions before acting. The intervals are wide — branded search could plausibly be anywhere from 0.2 to 1.6 — which is honest for geo measurement and means these are directional rather than precise. And these are average iROAS figures from a specific spend level; the marginal return on increasing social is lower than 3.4, so the scaling decision needs a [scale-up test](/glossary/scale-up-vs-scale-down-test) rather than an extrapolation.