Consumers had to proactively opt out of Consumer Email List sharing their IDFA. Although this may seem like a minor change, it is a big step forward, giving Consumer Email List users greater control and visibility over the data that applications can access and use. However, it also poses a challenge for marketers when it comes to measuring and analyzing the Consumer Email List performance of mobile marketing campaigns. For example, without IDFA, an advertiser loses access to user-level data, making it difficult to measure campaign ROI.
Also, the loss of IDFA will make it much more Consumer Email List difficult to run remarketing campaigns. Given this change, what kind of alternatives does AppsFlyer propose? At AppsFlyer we have developed SK360 , a set of tools to help marketers Consumer Email List continue to deliver exceptional experiences to their customers, without compromising Consumer Email List user privacy. Many of these solutions are based on machine learning and help marketers use aggregate data instead of user-level data.
For example, although Apple has launched its Consumer Email List own privacy measurement solution for developers and vendors, SKAdNetwork , measurement is limited to specific activity that occurs in the first 24-72 hours. How can advertisers make Consumer Email List critical campaign decisions based on such limited data? The answer lies in predictive technologies that will allow advertisers to take advantage of the first signs of engagement in the first 24-72 Consumer Email List hours and therefore predict long-term campaign performance.