SKAdNetwork iOS attribution is Apple's privacy-preserving way of telling advertisers which campaigns drove installs, without revealing who the individual user is. Since App Tracking Transparency required apps to ask permission before tracking users across other companies' apps, many iPhone users decline, so marketers increasingly rely on SKAdNetwork and its newer counterpart, AdAttributionKit, for a large share of iOS measurement.
This category explains how these frameworks work and what to do about them. Our guides cover the basics of App Tracking Transparency and its effect on user-level data; how SKAN 4 introduced multiple postbacks, coarse and fine conversion values and crowd anonymity tiers; how AdAttributionKit, introduced with iOS 17.4, builds on the same ideas and supports re-engagement; how to design a conversion value schema that reflects real revenue signals; and how MMPs and ad networks interpret this data.
These are technical topics, so we explain them for marketers, not engineers, and link to Apple's developer documentation for the definitive details. Appryze's founder has run iOS campaigns through these changes across Google, Meta and Apple Search Ads. Our app marketing page shows how we handle iOS measurement for clients.
App Tracking Transparency is an Apple framework that requires apps to ask users for permission before tracking them across apps and websites owned by other companies, including access to the device advertising identifier. If a user declines, the app cannot use that identifier, which limits user-level ad attribution on iOS.
A conversion value is a number an app sets after install to signal what the user did, such as completing onboarding or making a purchase. Apple sends it to the ad network in a delayed, anonymized postback. Advertisers design a schema mapping values to meaningful actions or revenue ranges.
Not strictly; an app can implement SKAdNetwork directly and ad networks receive postbacks. In practice, most advertisers use an MMP to manage conversion value schemas, collect postbacks across networks, decode the data and present it alongside other attribution sources in one dashboard.
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