SKAN, or StoreKit Ad Network, is a framework created by Apple to address user privacy concerns while still allowing app developers and advertisers to measure campaign performance for iOS apps. Here’s a breakdown of how it works:
Privacy focus:
- SKAN eliminates user-level identifiers like IDFA, preventing individual user tracking.
- App downloads are attributed based on conversion values set by the advertiser, providing aggregated insights without revealing individual user data.
Attribution process:
- User clicks on an ad: The ad network sends a cryptographically hashed token to the App Store along with basic campaign information (advertiser, campaign ID, ad network).
- App Install: If the user downloads and installs the app within a specific timeframe (depending on click type), the App Store sends a conversion postback to the ad network.
- Postback details: The postback includes the conversion value set by the advertiser (representing app engagement level) but no user-level data.
- Limited attribution windows: Click-through attribution happens within 24 hours, while view-through attribution has three windows (0-48 hours, 3-7 days, 8-35 days).
SKAN versions:
- SKAN 3: The base version, providing basic conversion value postbacks.
- SKAN 4: Introduced in iOS 16.1, offers up to three postbacks per campaign and supports remarketing attribution.
- SKAN 5: Announced but not yet released, promises additional features like campaign spend allocation and cost per install estimates.
Benefits of SKAN:
- Privacy-compliant: Respects user privacy without compromising measurement needs.
- Aggregated insights: Provides valuable campaign performance data without revealing individual user information.
- Multiple conversion values: Helps understand user engagement levels beyond just installs.
Challenges of SKAN:
- Limited data: Lacks user-level insights valuable for personalization and targeting.
- Delayed reporting: Postbacks can be delayed for up to 24 hours, impacting real-time analysis.
- Attribution complexity: Multiple conversion values and windows require careful interpretation.
Overall, SKAN is a significant step forward in balancing user privacy with app campaign measurement needs on iOS. While it presents challenges due to its privacy-first approach, understanding its mechanics and limitations is crucial for app developers and advertisers to adapt their strategies and optimize their campaigns in the new privacy landscape.