The introduction of iOS 14's privacy regulations has created unprecedented attribution challenges for marketers: fragmented data, duplicate attribution, and difficulties in evaluating channel performance. These obstacles have made marketing decisions increasingly complex. AppsFlyer's recently launched SSOT (Single Source of Truth) feature aims to address these issues, potentially becoming a reliable solution for iOS marketing attribution. This article examines SSOT's principles, setup process, and practical effectiveness.
The Growing Need for Unified Attribution Standards
The concept of "Single Source of Truth" (SSOT) isn't new. In information science, it refers to a practice of building information models and associated data schemas that ensure each data element is stored in a single location, enabling data normalization. Essentially, it establishes consistent standards across all data dimensions.
For mobile marketing, especially when using diverse advertising channels, unified attribution standards are crucial. Consider the confusion when different platforms—ad networks, third-party measurement tools, and internal BI systems—use varying definitions for user sources. Discrepancies might include cases where an ad platform shows purchases that third-party platforms don't register, or when installation counts differ between platforms. These inconsistencies often stem from varying attribution logic, data delays, or time zone differences. Without standardized metrics, marketers struggle to accurately assess channel performance and make informed decisions.
From an advertiser's perspective, establishing consistent definitions for user sources and purchasing behavior enables faster strategy adjustments, ultimately improving marketing efficiency and ROI.
Post-iOS 14 Attribution Challenges and SSOT's Approach
iOS 14's privacy updates introduced the SKAdNetwork (SKAN) framework, which enhances user privacy but complicates attribution. SKAN employs anonymous attribution with coarse-grained data and reporting delays. Meanwhile, traditional IDFA (Identifier for Advertisers) attribution offers more detailed insights but requires user consent, limiting data coverage. The coexistence of multiple attribution methods has exacerbated data fragmentation and duplicate attribution issues.
AppsFlyer's SSOT feature addresses this by combining SKAN and AppsFlyer's attribution models to deduplicate user data, providing advertisers with a unified standard. Essentially, SSOT resolves the core problem of duplicate activations that occur when users meet both SKAN and AppsFlyer attribution criteria.
How SSOT Works: Deduplication Based on Conversion Values
SSOT's core mechanism uses Conversion Value (CV) for attribution deduplication. The process involves three key steps:
- First Open Attribution: When a user first opens the app, AppsFlyer attempts attribution. If successful, the SDK marks the user via CV value and reports it normally.
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CV Reporting and Attribution Marking:
After receiving the CV value from iOS, AppsFlyer checks the
af_attribution_flagto determine whether the user activation is duplicate. - Deduplication: Based on this mechanism, SSOT identifies and excludes duplicate attributions, yielding more accurate data.
Note that SSOT currently doesn't account for reinstall deduplication—previous users aren't filtered through this mechanism.
Setting Up SSOT: A Straightforward Process
Implementing SSOT requires just a few simple steps:
- Enable SSOT: Navigate to the Overview panel in AppsFlyer and toggle the "Single source of truth" option.
- Reset CV Values: Follow system prompts or manually access the "SKAN conversion studio" to reconfigure CV values. Enabling SSOT reserves one CV value for attribution marking, requiring adjustments to comply with iOS requirements.
- Wait for Data Updates: Save the SSOT report and allow at least five days for data to populate. The SSOT view requires at least one SKAN report within this period to display properly.
SSOT in Practice: Improved Accuracy and Insights
AppsFlyer's data shows that SSOT reduces attribution to organic traffic while increasing non-organic traffic counts. This suggests SSOT better distinguishes between organic and non-organic sources, preventing misclassification and offering clearer channel performance insights.
In practical use, SSOT consistently reduces organic traffic metrics while boosting non-organic metrics across various sub-channels. These adjustments indicate more accurate attribution that better reflects actual user behavior.
Future Developments: Room for Enhancement
Currently, the SSOT panel doesn't support ROI-related metrics, though AppsFlyer plans to introduce this functionality in future updates. Additional improvements—such as more granular attribution analysis and reinstall deduplication—could make SSOT an even more powerful tool for iOS marketing evaluation.
In summary, AppsFlyer's SSOT offers a promising approach to post-iOS 14 attribution challenges. By combining SKAN and AppsFlyer models with CV-based deduplication, it provides marketers with more reliable data for performance assessment and strategy optimization. While SSOT has room for growth, its potential in iOS marketing attribution is significant.