The introduction of the SKAdNetwork (SKAN) framework by Apple has significantly altered the landscape of mobile app marketing and attribution. With the deprecation of Identifier for Advertisers (IDFA), app marketers now face challenges in accurately measuring ad campaign performance and user acquisition. Navigating the post-attribution landscape requires a well-thought-out SKAN implementation strategy. In this guide, we will explore effective strategies to navigate SKAN and ensure continued success in app marketing campaigns.
Understand SKAdNetwork and Its Limitations
First and foremost, app marketers must fully comprehend the workings and limitations of the SKAdNetwork framework. SKAN provides limited data compared to traditional attribution methods. It offers aggregate data, and postbacks are delayed for user privacy reasons. Marketers must adjust their expectations and metrics accordingly to adapt to this new environment.
Update App and SDKs
To implement SKAN, ensure that your app and mobile attribution SDKs are updated to support SKAdNetwork. Work closely with your attribution provider to ensure a seamless transition to SKAN. Verify that all necessary components are in place to collect and handle SKAdNetwork data effectively.
Embrace Contextual Advertising
With SKAN's limitations in tracking individual user-level data, contextual advertising becomes crucial. Focus on delivering ads that are relevant to the app's context and content. Contextual targeting can improve engagement and conversion rates, even in the absence of precise user-level targeting.
Utilize Conversion Value Optimization (CVO)
Conversion Value Optimization (CVO) is a critical aspect of SKAN implementation. With limited post-install data, CVO allows you to assign specific values to different post-install events. This information is crucial for understanding user behavior and optimizing campaign targeting and bidding.
Rely on First-Party Data
Leverage your app's first-party data to gain insights into user behavior and preferences. Use in-app analytics to understand user interactions, retention rates, and conversion paths. This data can be valuable for refining your marketing strategies and optimizing user acquisition.
Focus on User Retention and LTV
With SKAN's focus on aggregated data and delayed postbacks, measuring individual user attribution becomes challenging. Shift your focus to user retention and lifetime value (LTV) metrics. Understanding how user cohorts behave over time can help optimize your marketing efforts for long-term success.
Optimize for Incremental Metrics
Instead of relying solely on user acquisition metrics, consider incorporating incremental metrics into your analysis. Measure the lift in app installs and conversions driven by specific ad campaigns to gain a more comprehensive understanding of campaign effectiveness.
Diversify Marketing Channels
Diversifying your marketing channels can mitigate risks associated with SKAN's limitations. Explore different ad networks, social media platforms, and channels to reach your target audience. A multi-channel approach ensures broader visibility and reduces reliance on any single attribution method.
Navigating the post-attribution landscape with SKAN implementation requires adaptability and a data-driven approach. Understanding the limitations of SKAdNetwork, updating app and SDKs, embracing contextual advertising, utilizing CVO, relying on first-party data, focusing on user retention and LTV, optimizing for incremental metrics, and diversifying marketing channels are essential strategies for success. By adapting to the changes brought about by SKAN, app marketers can continue driving effective user acquisition and maintaining growth in the evolving mobile app marketing landscape.
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