Eliminate SKAdNetwork campaign uncertainty | AppsFlyer
AppsFlyer PredictSk Protect SK360 Suite

Eliminate SKAdNetwork campaign uncertainty with predictive analytics

Apple’s iOS 14 introduced new and much-needed developments into the mobile ecosystem, specifically in terms of user privacy.

The introduction of Apple’s SKAdNetwork as an attribution protocol also created an air of uncertainty to many advertisers. Changing standard attribution flows and introducing limitations of available data to measure campaign and user LTV.

AppsFlyer is proud to be the first MMP to introduce predictive analytics as a part of our SK360 suite for complete iOS 14 campaign optimization.

AppsFlyer PredictSK allows advertisers to complete quality measurement – translated into an accurate user LTV prediction value scaled from 1-10. This user-level score is delivered within 3 days of the user’s install, giving advertisers everything they need to make educated decisions and optimize their campaigns while taking all desired events into account

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How does PredictSK solve SKAdNetwork’s limitations?

One of SKAdNetwork’s limitations is the very short window advertisers are expected to rely on for measuring campaign performance. With only 24 hours of user activity to work with, optimization is nearly impossible. With PredictSK, advertisers will be able to leverage early signals of engagement (first 24-72 hours) to predict long-term campaign performance.

PredictSK puts mobile attribution in SKAdNetwork on ‘auto-pilot’, removing the measurement and timing barriers and allowing advertisers to maintain and strengthen their competitive edge in this new reality. PredictSK, AppsFlyer’s predictive analytics solution for SKAdNetwork will be officially rolled out in the spring, in line with Apple’s ATT enforcement, as part of the company’s SK360 suite. 

Who is PredictSK for?

PredictSK provides the most value to app advertisers who have a rich measurement integration with AppsFlyer – one that best represents their user value through measurable in-app events.

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