A high-level primer on IDFA
Updated: May 24
At Lumikai we’re often asked about IDFA, and what the imminent changes in Apple’s policy mean for the broader ecosystem. While there have been a lot of detailed analyses geared towards developer best practices, here we lay out an easy-to-digest, high-level overview of the key changes and how they will impact the mobile gaming business.
What is IDFA?
The Identifier for Advertisers (IDFA) is a random device identifier that Apple assigns to its devices, which can be used for tracking and identifying a user without revealing their personal information. Since users spend most of their time on apps, not on the web, IDFAs took the place of cookies in the iOS mobile advertising world. By allowing advertisers to identify when their ads create results, IDFA has helped optimize ad campaigns through targeted advertising, attribution, and improved user acquisition.
In essence, IDFA allows advertisers to do the following:
1. Enforce frequency capping to limit ad fatigue and annoyance
2. Deliver relevant and personalised ads through behavioural data
3. Retarget lapsed customers based on past actions on other platforms
4. Attribution to measure ad-campaign performance and subsequently devise optimization procedures
Apple’s New Privacy Norms
Starting with iOS14, Apple introduced the App Tracking Transparency (ATT) framework. According to the new privacy framework, apps will need to receive permission from users in order to access the device’s IDFA. Essentially, iOS devices will by default not grant permission to track their IDFA- and the user will have to explicitly grant permission to do so. A user may expect to see a pop-up as shown below:
The message is customizable (known as a Usage Description String), which means that developers can try to persuade their users to opt-in. These new changes are expected to be introduced with the launch of the iOS 14.5 beta update.
What are the expected implications?
Globally, it is expected that only around 20% of users will opt-in for information tracking.
With the tracking capabilities of IDFA significantly reduced, advertisers will lose the ability to show ads that are relevant, and at the right time. Additionally, the lack of attribution capabilities will prevent marketers from accurately measuring ad-campaign success, thereby also preventing them from optimizing these campaigns. Effectively, as Casey Campbell at Gameloft very succinctly puts it- this represents a shift from a deterministic model of advertising to a probabilistic model. In other words, the chances of reaching the right customer with ads have now greatly reduced.
Briefly, the following implications of the new norms are expected:
Reduced Click-Through Rates (CTR) due to ineffective advertisements
eCPMs to drop by 30–40% on non-IDFA supply
Lower conversions leading to a reduction in ad spends
Ineffective and costly User Acquisition (UA) on iOS and other Apple devices
Users who have opted-in for tracking will become a prized commodity- cost of impressions with the identifier will rise by 40–50%
Reduced monetisation through in-app advertisements manifesting through lower Return on Ad Spend (ROAS)
Increased cost of in-app purchases to counteract the loss in ad revenue
Publisher bias towards Android, where the Google Play Services for Android (GPS ADID) is expected to continue working
Increased adoption of Apple’s SK Ad Network (SkAN, for short)- more on this later
Since these changes strictly apply to Apple users, it is worth analysing the scope of these new norms. Global iOS penetration is only around 27%. Regions like India, where iOS penetration is only 2.74%, are unlikely to be affected. Marketers targeting regions such as the United States (61% iOS), Canada (53% iOS), and the United Kingdom (52% iOS) are likely to face the majority of the challenges.
What does this mean for game developers?
Game developers who develop apps for iOS will be most affected. As mentioned earlier, the lack of tracking will lead to lower ROAS, poor attribution, and ineffective user acquisition. Apart from the obvious effects, however, there are some nuances to keep an eye out for:
Equalizing Effect in Terms of Attribution: Attribution services are expensive, and not everyone has them. But with the deprecation of IDFA, ad attribution will become less of a differentiating factor. The knowledge gap between small studios and big studios will reduce- allowing small studios to be more competitive. However, bigger studios and publishers will probably look to build out analytics and attribution within their games ecosystem.
Casual and Hypercasual Studios: In spite of their heavy reliance on ad revenue, casual and hypercasual studios might just be the least affected. Their business model relies on a large number of users who provide high value as a group- and not on singular high-value users. With the shift towards probabilistic targeting, there is greater value in showing many ads per user- which suits these genres.
Over-reliance on Targeted Ads: Studios with an over-reliance on targeting ads to a small, high-value user base will likely suffer the most. The lack of attribution capabilities will affect their ability to truly measure campaign success and optimize for higher ROAS.
Importance of Data Science: With the shift towards probabilistic targeting, it will become crucial for game studios and developers to understand how to deal with and analyze data in the aggregate.
First-Party Data Collection: Publishers and large game development studios can collect first-party data through their games network. For example, Gameloft asks for standard demographics like age and gender when a user installs their game. It also identifies details such as in-game language settings, player’s device, operating system, etc to contextually understand its audience. Such first-party data can be very valuable and might serve as a competitive advantage for larger studios and publishers.
Acceptance of Probabilistic Targeting: It has become crucial now to be able to analyse data in the aggregate. As mentioned earlier, with a lack of granular data, comes the need to understand the science of aggregate data. We are likely to see more investment and innovation in this space as the search for an effective workaround gains momentum.
Use of SkAN as an Alternative: Apple has offered the SkAdNetwork (SkAN) framework as an alternative to IDFA. SkAN is a framework for privacy-preserving mobile install attribution- it aims to measure conversion rates of app install campaigns (CPIs) without compromising users’ identities. The whole attribution process is conducted by the App Store and attested by Apple’s servers, and the results are then sent off to the ad network sans user identifiers and temporal information. As a result, the SkAN framework does not provide user-level data or real-time data. According to the Apple Developer Program License Agreement, SkAN cannot be used for deriving data from a device for the purpose of uniquely identifying it (this includes collecting information on device configuration, user’s web browser, user’s location, and user’s network). Any app that is found to be referencing SDKs (such as Ad Networks, Attribution, etc) that engage in the practice of fingerprinting will be rejected from the App Store.
Optimize for Opt-ins: Developers should look towards adjusting their user experience in order to optimize for opt-ins. As mentioned earlier, the Usage Description String can be modified to the developer’s liking. As a result, there is scope to optimize the messaging so as to improve the opt-in rate for IDFA tracking.
Collect your own Data: It is now worth allocating some resources to collecting first-hand, in-app data from users- which can then be put through a predictive or contextual modeling process to generate insights on users. This might lead to advertisers aligning more closely with developers- leading to a win-win situation for all.
Shift from Personalization to Gamification: In lieu of personalization, marketers can leverage gamification to get users to engage with ads. Creating an ad that entertains, informs, and rewards behaviors is a lot more effective than a static ad that may or may not be useful to a viewer.
It is worth noting that Apple successfully fended off an attempt by marketers in France to block the new privacy norms. Further, China has rolled out its China Advertising ID (CAID) as an alternative to the IDFA.
A high degree of user opt-out is inevitable after the changes in IDFA roll out, forcing an iOS-ecosystem wide shakeup of how developers and publishers attract, optimize, attribute, and retarget users.
These changes are in line with Apple’s broader philosophy of putting user privacy first and are likely here to stay. Developers will need to adapt and evolve. While this will cause some short-term disruption, it also creates opportunities for newer, nimble developers customizing their product strategy and UA stacks for the post-IDFA world. And developers focused on the Indian market will be somewhat insulated from the changes, with iOS users representing under 3% of the domestic ecosystem.
In some respects, these changes also force a return to the fundamentals of building trust with users over time through quality of product — loyal users are more likely to share data willingly and create organic network effects that drive user acquisition and retention.
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