SKAN postbacks versus MMP revenue: keep the units on different rows

SKAN conversion values and MMP revenue can describe overlapping purchases without being the same estimator. This lab refuses to add them.

Define the calculation before using it

Enter MMP-observed revenue for opted-in or otherwise MMP-attributed users, SKAN-mapped revenue from conversion-value buckets, and the overlap the team is willing to treat as the same purchasers. Subtract overlap once if a combined view is required; otherwise report the two series separately.

Work through the synthetic example

A synthetic week with 8,000 MMP revenue units, 5,000 SKAN-mapped units and 3,200 labelled overlap is 9,800 if combined once—not 13,000. The SKAN figure still depends on the studio’s conversion-value schema, privacy thresholds and coarse conversion windows.

Use the artifact and preserve its assumptions

Open the editable calculator to change the inputs and inspect the sensitivity view. The CSV records synthetic inputs and expected outputs; the JSON fixture keeps the equations available for reproduction. These calculations have been checked against the stated example. No measured campaign data is included.

The sensitivity rows vary only overlap by 20% below and above the entered value. They are scenarios, not confidence limits or a forecast distribution. A row outside the model’s constraints is labelled rather than turned into a plausible-looking result.

Evidence and limits

Apple documents conversion values and postbacks as privacy-preserving attribution signals. Mapping those values to revenue is a studio schema, not an Apple revenue export. See SKAdNetwork, especially “SKAdNetwork overview / conversion values”.

The overlap input is an assumption. Apple’s SKAdNetwork documentation does not publish a studio’s revenue. Do not treat SKAN mapped value as MMP D7 revenue.

Background: SKAN Conversion Value Mapping, Revisited for 2025 and Reading an MMP dashboard without fooling yourself. These existing articles provide context; the present calculation does not verify every archived claim.

Draft prepared 19 September 2026. Synthetic teaching example; human editorial and specialist review pending. No actual campaign outcome or recommended industry default is claimed.