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SKAN vs. Traditional Mobile Measurement Partners: Pros and Cons

SKAdNetwork (SKAN) and traditional Mobile Measurement Partners (MMPs) are two approaches to app attribution and measurement in the mobile advertising ecosystem. Each method has its own set of pros and cons. Let's explore them!

SKAdNetwork (SKAN)


  1. Privacy-Focused: SKAN prioritizes user privacy by limiting the amount of data shared with advertisers and aggregating attribution information. It helps address privacy concerns and ensures compliance with regulations like Apple's AppTrackingTransparency (ATT) framework.

  2. Fraud Prevention: SKAN incorporates fraud prevention measures to minimize attribution fraud, providing advertisers with more reliable attribution data.

  3. Standardized Attribution: SKAN provides a standardized attribution model across different advertising platforms, reducing discrepancies and making it easier to compare performance across channels.

  4. Conversion Value Optimization: SKAN allows for conversion value updates, enabling marketers to track and optimize specific post-install events and user actions within their apps.

  5. App Store Integration: SKAN is directly integrated into the App Store, ensuring a consistent attribution process for all apps on iOS.


  1. Limited Data: SKAN provides limited data compared to MMPs. It focuses on aggregated attribution insights, which may restrict in-depth user-level analysis and audience segmentation.

  2. Attribution Delays: SKAN attribution is not instantaneous and can have delays of up to 24-48 hours. This delay may impact real-time optimization strategies and campaign decision-making.

  3. Limited Cross-Channel Attribution: SKAN primarily focuses on attribution within the Apple ecosystem. It may not provide comprehensive cross-channel attribution for campaigns that span multiple platforms.

Traditional Mobile Measurement Partners (MMPs)


  1. Granular Data: MMPs offer more granular data and insights compared to SKAN. They provide user-level data for detailed analysis, audience segmentation, and advanced attribution models.

  2. Real-Time Attribution: MMPs offer real-time attribution, providing immediate feedback on campaign performance and enabling quick optimization decisions.

  3. Cross-Platform Attribution: MMPs can attribute and measure campaigns across different platforms and advertising networks, offering a more comprehensive view of cross-channel performance.

  4. Advanced Features: MMPs often provide additional features like cohort analysis, deep linking, audience targeting, and advanced analytics, empowering marketers with more sophisticated tools for campaign optimization.


  1. Privacy Concerns: Traditional MMPs rely on third-party tracking methods that may raise privacy concerns and require user consent, which can be affected by changing privacy regulations and user preferences.

  2. Reliance on Device IDs: Traditional MMPs heavily rely on device identifiers (e.g., IDFA on iOS, GAID on Android), which can be limited by user opt-outs or restricted by platform changes.

  3. Attribution Discrepancies: Discrepancies in attribution data can arise due to technical limitations, differences in attribution methodologies, or discrepancies between MMPs and ad networks.

It's important to note that the choice between SKAdNetwork and traditional MMPs depends on privacy requirements, campaign goals, data needs, and platform considerations. Some advertisers may opt for a hybrid approach, leveraging both SKAN and MMPs to gain the benefits of both methodologies while addressing specific needs and privacy considerations.

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