<b>Why does your attribution model say one thing and your geo holdout say another?</b>

<b>Why does your attribution model say one thing and your geo holdout say another?</b>

Because they answer different questions, and conflating them is the most expensive mistake in measurement.

<b>Two distinct questions</b>

— Attribution asks: <i>among the conversions that happened, how should credit be divided across touchpoints?</i> It is a descriptive accounting exercise over observed paths.
— Incrementality asks: <i>how many of those conversions would NOT have happened without this spend?</i> That is a causal question, answerable only by comparing a treated group to a counterfactual.

<b>What the studies show</b>

Incrementality tests — geo holdouts, randomized PSA experiments, ghost-bid auctions — repeatedly find that channels rich in <i>captured demand</i> (branded search, retargeting, lower-funnel social) are heavily over-credited by attribution models. Meta's own conversion-lift work and multiple academic PSA studies show platform-reported conversions running several multiples above true incremental lift in many accounts.

<b>The nuance</b>

This does not make attribution useless. Attribution is a fast, daily, granular allocation tool. Incrementality is slow, coarse, and expensive but causally honest. They operate at different cadences and resolutions.

<b>What to actually do</b>

— Use incrementality to <i>calibrate</i> your attribution model: derive scaling factors per channel from experiments, then apply them to your daily attributed numbers.
— Re-run calibration quarterly; incrementality decays as saturation and creative fatigue shift.

Bottom line for practitioners: attribution divides the pie, incrementality tells you how big the pie actually is. You need both, and you should never let the cheap one overrule the expensive one on questions of true value.