Overview

SKAdNetwork (SKAN) is Apple's privacy-centric tool for attribution of mobile app installs and related events.

What is SKAdNetwork?

The SKAdNetwork (SKAN) is an API from Apple designed to help advertisers measure the success of ad campaigns while maintaining user privacy. Apple installs this framework on devices with iOS 14 and later. It allows registered networks to receive data about user installs in response to ads, albeit in an anonymized and aggregated format.

SKAN reports conversions to ad networks, enabling them to attribute installs without resorting to using the device’s ID. It uses a conversion value that measures user engagement levels within a specific time frame. After a user installs an app, the app can use SKAN to update the conversion value, indicating that the user performed a certain level of activity.

Formula

SKAdNetwork (SKAN) uses a 6-bit conversion-value, an integer that ranges from 0 to 6The app can update this conversion value for a short period after installation. The final value recorded is reported back to the ad network.

Example

Assume an ad network serves an ad for a hotel booking app. A user sees the ad and installs the app. If this user makes a booking within 24 hours, the app records this in the conversion value, which then sends back to the ad network.

Why is SKAN important?

  • User Privacy: SKAN upholds users’ privacy by not directly linking ad-to-user action. It allows the continued tracking of ad campaign effectiveness without violating user privacy rules.
  • Enhanced Advertising: Conversion values from SKAN intentions help advertisers optimize their campaigning strategies.

Which factors impact SKAN?

  • Time-Decay Models: Using advanced time-decay models can maximize the usefulness of the limited data from SKAN.
  • Incrementality Testing: Complementing SKAN data with incrementality testing can improve campaign optimization.

How can SKAN be improved?

  • Delay in Reporting: The SKAN data is reported with a delay, which can affect the real-time decision-making process.
  • Aggregated Data: As data provided by SKAN is aggregated, this limits the possibility of granular analysis.

What is SKAN’s relationship with other metrics?

The conversion value from SKAN could potentially relate to similar e-commerce metrics like customer lifetime value (CLTV) and average order value (AOV). It can also tie to app metrics, such as user engagement levels and retention rates. It allows e-commerce analysts to understand user behavior related to ad campaigns while upholding privacy norms.

Free essential resources for success

  • Brands to Grow in a Third-party Cookie-less Future

    Checklist for Brands to Grow in a Third-party Cookie-less Future

    Shift your marketing approach with a practical guide to first-party data and advanced measurement.

  • A Guide To Marketing Effectiveness Measurement For Ecommerce Brands

    A Guide To Marketing Effectiveness Measurement For Ecommerce Brands

    Turn fragmented data into clear insights that improve ecommerce marketing performance.

  • Made to Measure Seasonal Marketing With Data-driven Success

    Made to Measure: Seasonal Marketing With Data-driven Success

    Build smarter seasonal strategies by connecting data insights directly to execution and performance.

Discover more from Lifesight

  • The BFCM Trap: Waiting Until Q3 Kills Your Q4

    Published on: May 11, 2026

    The BFCM Trap: Waiting Until Q3 Kills Your Q4

    Start testing in Q2 or risk gambling your entire Q4 on unproven channels when costs are at their peak.

  • Agentic Unified Marketing Measurement Manifesto

    Published on: May 5, 2026

    The Agentic Unified Marketing Measurement Manifesto

    Why marketing measurement, in the age of AI agents, needs a new standard.

  • Building the AI Agent Brain

    Published on: April 29, 2026

    Building the AI Agent Brain

    Context Graphs with Self-Improving Memory. A Production Architecture with Spanner Graph, Hindsight, Vertex AI, and ADK