SKAdNetwork (SKAN)

App Tracking Transparency (ATT) is Apple's privacy framework, introduced with iOS 14.5 in April 2021, that requires apps to request explicit user permission before tracking their activity across other companies' apps and websites. When an app wants to access a user's IDFA (Identifier for Advertisers) for targeted advertising or cross-app attribution, it must display a system prompt asking the user to opt in. Industry-wide opt-in rates have hovered around 20–35%, meaning the majority of iOS users are now untrackable via traditional deterministic methods. ATT fundamentally disrupted mobile attribution and user acquisition by limiting the data available for campaign optimization, audience targeting, and performance measurement. This shift forced the industry to adopt new attribution frameworks like SKAdNetwork, invest in first-party data strategies, explore probabilistic modeling, and seek alternative monetization channels — such as web-based funnels — that operate outside the ATT-restricted ecosystem. For subscription apps, ATT's impact on attribution accuracy has made it significantly harder to measure true LTV by acquisition channel, increasing the importance of predictive modeling and server-side analytics.

Mobile attribution is the process of connecting app installs and in-app actions to specific marketing campaigns, ads, or channels that drove them. It enables marketers to understand which advertising efforts deliver results, optimize ad spend across channels, and make data-driven decisions about user acquisition strategies.

A postback (also called a server-to-server callback or S2S callback) is a server-side communication mechanism used to send conversion data from one system to another without relying on client-side tracking. In mobile attribution, postbacks are the primary method by which Mobile Measurement Partners (MMPs) communicate install and event data back to ad networks. When a user installs an app and the MMP attributes that install to a specific campaign, the MMP fires a postback to the relevant ad network containing the attribution details (campaign ID, ad group, creative, conversion timestamp, etc.). This enables the ad network to optimize its algorithms and allows the advertiser to measure performance. In the SKAdNetwork framework, Apple sends postbacks directly from the device to the ad network, bypassing the MMP entirely for initial attribution. Postbacks are also used in web-to-app flows to communicate web conversion events to advertising platforms — for example, when a user completes a subscription purchase on a web checkout page, a server-side postback can be sent to Meta or Google to feed their optimization algorithms with conversion signals.

IDFA, short for Identifier for Advertisers, is a distinct and unpredictable alphanumeric code that is assigned to each iOS device by Apple. Advertisers use this identifier to deliver targeted ads and measure the effectiveness of their advertising campaigns. With the changes to Apple's privacy policy, app developers are now required to explicitly ask for user permission to track their IDFA. Users can choose to opt out of IDFA tracking by turning on the "Limit Ad Tracking" (LAT) option in their device's settings.

A Mobile Measurement Partner (MMP) is a third-party analytics platform that provides independent attribution, analytics, and measurement services for mobile app marketing campaigns. MMPs track which ad clicks and impressions lead to app installs and post-install events, providing a unified view of marketing performance across multiple ad networks and channels. Major MMPs in the mobile ecosystem include AppsFlyer, Adjust, Branch, Singular, and Kochava. MMPs play a neutral intermediary role — since they are independent from both the advertiser and the ad networks, their attribution data is considered unbiased. Core MMP capabilities include last-touch attribution, multi-touch attribution, fraud detection, deep linking, audience segmentation, SKAdNetwork management, and cohort-based analytics. In the post-ATT landscape, MMPs have evolved to offer probabilistic modeling, predictive analytics, and aggregated measurement solutions that work within Apple's privacy constraints. For subscription apps, MMPs provide critical insights into which channels and campaigns deliver subscribers with the highest LTV, enabling marketers to shift budget toward the most profitable traffic sources.