Revenue Attribution on iOS 14 using Conversion Values in F2P Games
This addresses a critical measurement challenge for mobile app developers and marketers due to Apple's privacy changes, though it is incremental as it builds on existing conversion value mechanisms.
The paper tackles the problem of attributing revenue to advertising campaigns on iOS 14 using conversion values, formalizing the problem and finding the theoretically optimal revenue attribution function, with empirical results showing up to 15% improvement in revenue prediction accuracy compared to baseline methods.
Mobile app developers use paid advertising campaigns to acquire new users. Marketing managers decide where to spend and how much to spend based on the campaigns' performance. Apple's new privacy mechanisms have a profound impact on how performance marketing is measured. Starting iOS 14.5, all apps must get system permission for tracking explicitly via the new App Tracking Transparency Framework, which shows the users a pop-up asking if they give the app permission to track. If a user does not allow tracking, the required identifier to deterministically find the online advertising campaign that brought the user to install the app is not shared. Instead of relying on individual identifiers, Apple proposed a new performance mechanism called conversion value, which is an integer set by the apps for each user, and the developers can get the number of installs per conversion value for each campaign. However, interpreting how conversion values are used to measure the campaigns performance is not obvious because it requires a method to translate the conversion values to revenue. This paper investigates the task of attributing revenue to advertising campaigns using the reported conversion values per campaign. Our contributions are to formalize the problem, find the theoretically optimal revenue attribution function for any conversion value schema, and show empirical results on past data of a free-to-play mobile game using different conversion value schemas.