SKAdNetwork and iOS Measurement

Scale iOS with privacy-centric attribution

Fill the gaps that SKAdNetwork (SKAN) leaves behind with a single deduplicated view of iOS performance.

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Branch Dashboard showing SKAN and non-SKAN installs combined by ad partner, with attribution discrepancy analysis of duplicated installs

WHAT IT SOLVES

Get better insights from every iOS user

Bring every iOS measurement method into one deduplicated, privacy-preserving view.

Put your budget behind the iOS campaigns that earn it

Combine SKAN postbacks with network data and cost to see iOS return on ad spend (ROAS) by network, campaign, ad set, and sub-publisher.

Get better data from your conversion models

Configure conversion value schemas that capture your most predictive down-funnel signals in each SKAN postback.

Unify iOS data in one deduplicated view

See paid and organic iOS measurement data in one report, with deduplicated events and metrics across every measurement method.

Expand iOS coverage for non-SAN partners

Measure iOS performance for ad networks that don’t have their own aggregate solution, with privacy-safe measurement that works alongside SKAN.

core capabilities

Every iOS measurement method, working together

Branch dashboard for setting up and editing events for ad conversion tracking

SAN aggregate measurement solutions

Track iOS performance across every self-attributing network’s (SAN’s) aggregate solution with independent attribution that deduplicates and measures across iOS methods.

Privacy-safe aggregate measurement

Measure the iOS users who opt out of tracking and credit their conversions to the right source, so fewer installs get lost to organic.

Web-to-app attribution

Build journeys that use context and intent to create personalized experiences free from App Tracking Transparency (ATT) restrictions.

Transparent analytics 

See the reasoning behind every attribution decision and compare all iOS measurement methods side by side.

BEYOND SKAN

Attribute more iOS installs with predictive measurement

Branch’s proprietary attribution model, Predictive Aggregate Measurement (PAM), measures the iOS users who opt out of tracking. PAM applies predictive modeling to aggregated data, with built-in privacy controls that protect individual identities, to give you granular, timely insight SKAN alone can’t provide.

Our customers say it best

We’ve been trusted by more than 100,000 brands since 2014 to deliver flawless customer journeys. 

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More ways to measure

Combine SKAN data with mobile, web, and cross-platform attribution to understand what’s really driving growth.

Mobile attribution

Attribute every install and in-app event back to the campaign that drove it.

Cross-platform attribution

Connect touchpoints from every channel with conversions on any platform.

Identity resolution

The cross-platform, cross-device identity foundation behind better measurement.

Frequently asked questions (FAQs)

How does SKAdNetwork work?

SKAdNetwork (SKAN) is Apple’s privacy-preserving framework for measuring iOS ad campaigns. When an ad drives an install, Apple sends delayed postbacks to the ad network with campaign details and conversion values, without exposing user-level identifiers. Branch’s SKAN Conversion Center helps you set up SKAN, map app events to conversion values, and view SKAN results alongside your other attribution data.

What are SKAdNetwork conversion values?

SKAN conversion values tell you what users do after installing your app, such as completing onboarding, making a purchase, or starting a subscription, without identifying anyone. SKAN 4.0 supports fine-grained values from 0 to 63 and coarse values of low, medium, or high, depending on Apple’s privacy thresholds.

How do you handle SKAN 4.0?

Branch fully supports SKAN 4.0, including its three postback windows and coarse and fine-grained conversion values. In the SKAN Conversion Center, you can map events and revenue ranges, use conversion-value locking and anchoring, and analyze postbacks in Branch’s SKAN reporting. How much detail Apple returns still depends on its privacy thresholds.

How does ATT/IDFA opt-out impact measurement?

When users opt out through Apple’s App Tracking Transparency prompt, apps can’t use their IDFA for cross-app tracking, which makes it harder to connect ads to installs and conversions. SKAN covers some of that gap with limited detail. Branch’s Predictive Aggregate Measurement (PAM) adds modeled, aggregated insights for opted-out users who would otherwise show up as unattributed.

See what your iOS data has been missing

Join the 3 billion-device network already running on Branch.