Crowd anonymity, or Apple’s new way of ensuring users DON’T stand out from the crowd, refers to the protection of individual user data by aggregating it within a larger group of users, making it impossible to distinguish or identify single users within the data set. This approach ensures that while advertisers receive useful information about user behavior, the privacy of each user is preserved.
Within the SKAdNetwork framework, crowd anonymity is crucial in balancing the scale between user privacy and marketing attribution. It ensures that while advertisers can track the performance of their ad campaigns in terms of conversions and app installs, they do not receive granular data that could compromise user privacy.
The SKAN 4.0 framework establishes tiers of crowd anonymity. Each tier reflects a different level of user aggregation required before data is shared with advertisers. Lower tiers represent smaller groups and thus provide less specific data, while higher tiers, which aggregate data from larger groups, allow for more detailed reporting without compromising anonymity.
The crowd anonymity tier will have a say in the following conversion postback elements:
Tier 0: At this lower end of crowd anonymity, the install count is low and therefore doesn’t meet the privacy threshold. As a result, you’ll get:
Tier 1: Also sits at the lower end of crowd anonymity, but with enough installs to meet the privacy threshold. In this tier, you’ll get:
Tier 2, at a higher crowd anonymity level, you’ll get:
Tier 3, at the highest crowd anonymity level, you’ll get:
Or you can refer to these pictures for a better summary
If all of those things seem hard to understand and work with, do not worry - Airbridge supports both SKAN 3.0 and SKAN 4.0. For SKAN 4.0 specifically, Airbridge can help you receive and decode the conversion data from all three SKAN 4 measurement windows, together with pinpointing the best campaigns for each postback data tier.
Airbridge SDK can get your app updated, or you can establish a SKAN 4 setup via Airbridge to leverage features such as the Lock window, coarse conversion values and the source ID for more precise targeting and better web-to-app campaign development.