Anonymous user-level data: In-app event and revenue data.The AlgoLift by Vungle probabilistic attribution model ingests four sets of data as described and visualized below. Second, our probabilistic attribution method doesn’t collect IP addresses for users-to-attribution-source matching as fingerprinting does. 20% probability from organic, 30% from a Facebook ad campaign, etc.), using only the data provided by SKAdNetwork, ConversionValue, and anonymous user-level app data. Instead, our method creates a probability distribution of where a user is likely to have come from (e.g. This is critical in understanding how the AlgoLift by Vungle probabilistic attribution differs completely from fingerprinting. Let’s dig in.įirst, our probabilistic attribution model doesn’t attempt to make a one-to-one attribution match between user and attribution source the way fingerprinting does. We’ll explain how the AlgoLift by Vungle Apple-compliant probabilistic attribution model has several fundamental differences and flat out doesn’t equal fingerprinting. In this blog post, we’ll discuss why the industry needs to move past discussions around fingerprinting as a solution for measurement and discuss types of probabilistic attribution that don’t track individual users. This is because an identifier (ID) is created to attempt to track a user without receiving user permission to do so, as Apple’s privacy FAQs stated: “you may not derive data from a device for the purpose of uniquely identifying it.”īut what’s currently stuck in the collective ad tech industry’s subconscious is the notion that “probabilistic attribution” is another word for “fingerprinting.” Although fingerprinting is a type of probabilistic attribution solution, it’s not compliant with the privacy rules set forth by Apple. Probabilistic attribution is a statistical solution for providing a probability distribution of all the campaigns that are likely to have generated an install. In the context of mobile marketing, fingerprinting is the practice of attempting to one-to-one match an individual mobile user to an acquisition source through IP address (predominantly) along with other device attributes such as device name, device type, OS version, and mobile carrier.įor months since Apple announced the deprecation of IDFA in summer 2020, mobile marketers have wondered if fingerprinting would be allowed after the release of iOS 14.5.Īpple answered in their privacy FAQs in January 2021 with an emphatic no. if the ad is on mobile web), or because the user has restricted access to the IDFA through Limit Ad Tracking (LAT). This is either because there is no IDFA available (i.e. Historically MMPs have used an alternative method called fingerprinting to track these users when the MMP SDK is unable to access the device IDFA. In early spring, Apple’s identifier for advertisers (IDFA) for iOS will hit the endangered species list after the public release of iOS 14.5, leaving mobile marketers without a way to deterministically attribute through mobile measurement partners (MMP) users who don’t give permission to access their IDFA.

Does not equal sign apple