Apple is changing the way digital ads work. Are advertisers prepared?
Apple is turning the privacy settings of its mobile ecosystem upside down. When it releases its app tracking transparency framework (ATT) with iOS 14.5 on April 26, it will shut down a data stream that app developers, measurement companies and advertisers have used to link user behavior across apps and mobile websites – a move that could transform the digital advertising industry. The update will disable the Identifier for Advertisers (IDFA) enabled by default on Apple devices, which gives app publishers access to user-level data, and users must give apps explicit access to it. With in-app prompts asking users: [app name] to track your activity across other companies’ apps and websites? ”Opt-in rates are likely to be low.
We anticipate Apple’s ATT initiative will deal a huge blow to the targeted advertising that is critical to the business models of online content publishers like Facebook, Google, and many news outlets. But while large digital content providers will feel the impact of ATT, the large proprietary data sets they have amassed can protect them long term. Smaller businesses like ecommerce companies that rely on targeted advertising to reach customers and mobile measurement providers that collect and organize app data are likely to have a harder time – a point Facebook tried in a campaign responding Apple policies are changing.
With the introduction of ATT, Apple is rethinking the role advertising plays in its ecosystem. The move will allow the company to have tighter controls over users’ app experiences and content curation. It will also allow Apple to push ahead with the rollout of its own targeted advertising solution – its internal ad tracking services use friendlier language than third-party apps require, and new commercials have recently been rolled out in the App Store. Establishing itself as the market leader in the field of data protection can strengthen the brand and have a lasting positive effect on hardware sales.
While ATT could be the most impactful change to the digital advertising ecosystem yet, other restrictions on user privacy are on the horizon. Developments like private click measurement (PCM), Google’s Federated Learning of Cohorts (FLoC), the end of third-party cookies in Chrome, and government data protection regulations like GDPR and CCPA all point to a new privacy-centric era on the horizon. That means advertisers and advertising companies have to learn to play by new rules – and fast. Here’s how to prepare for the changes.
What changes ATT
Apple’s new approach to data protection poses a clear problem for advertisers who depend on targeted advertising – i.e. most digital advertisers – as it is becoming much more difficult to meaningfully link user behavior between apps and mobile websites in the iOS ecosystem. Depending on the likely low opt-in rates, this represents a major challenge for advertising targeting algorithms, which are currently performing well by not only observing which advertisements users see and click on, but also who then goes on to take relevant actions on the advertiser’s website or app.
Overall, it can be assumed that ATT makes advertising far less relevant to consumers and far worse off for advertisers – with the exception of advertising delivered by Apple’s own personalized advertising system. It also lowers the accuracy of ad metering across iOS apps and mobile websites. Many industry insiders expect Google to make a similar change to the Android ecosystem at some point in the future, effectively making digital advertising less relevant across the board and making its measurement much less granular and precise. * These changes in the digital measurement landscape are declining some the innovations made possible by digitization, namely precise measurement through attribution at the user level and advertising experiments.
To help advertisers cope with the data availability restriction introduced by ATT, Apple offers a measurement solution called SKAdNetwork (SKAN), which makes performance data available at the campaign level. However, not only is the number of campaign slots available per advertiser limited, SKAN also adds a random time delay when observing performance events such as purchases or shopping cart additions and restricts how and how many such events can be observed per campaign .
SKAN falls into the area of differential privacy, an approach to marketing measurement that uses statistical methods to avoid inferences about the behavior of individual users and still allow the behavior to be linked across different digital properties. It is likely that differential privacy will become more common. Other technology companies such as Google are also investing heavily in such technologies, but there may still be a long way to go before they are widely accepted and introduced as a new data protection-safe measurement approach.
In the meantime, more traditional measurement solutions that are privacy-safe by default are likely to gain in importance. For example, Marketing Mix Models (MMMs) have been developed on and for aggregate advertising and sales data that has been observed over time and does not require lower-level linking of tracking data. You use the natural variation in a company’s marketing mix or, if possible, an explicitly induced randomization over time and / or geographical course to measure advertising impact. As evidence of the likely renaissance of MMMs in marketing measurement, Facebook released an open source computer package that enables advertisers to implement MMMs with guidance.
How you can adapt
So what should advertisers and advertising companies do? We believe that internalizing the following strategic viewpoints can help organizations cope with this changing data protection landscape.
1) Use privacy methods like differential privacy (Apple) and federated learning (Google). These are the primary means by which large platforms are bringing a new level of privacy for consumers – companies that plan ahead should develop advertising technologies that are tailored to them.
2) Understand that workarounds for new data protection regulations are not a viable, long-term solution. It may seem relatively cheap or easy to develop solutions that preserve advertising workflows and measurement schemes by secretly violating platform guidelines – with device fingerprinting or server-to-server conversion management – but this approach only delays the inevitable pain of adjustment. A company should invest in real solutions, not in gimmicks that exploit loopholes or rely on incomplete enforcement of rules, especially since the data protection landscape is currently mainly determined by large platforms that mostly operate according to their own rules.
3) Move advertising metering away from deterministic, user-centric models. Instead, use more holistic macro-level models that look at fluctuations in ad spend and revenue over time to map efficiency to channel-specific ad campaigns. This approach requires sophisticated data science expertise, and it can be difficult to properly tune these types of models, but a measurement solution that relies on statistical sophistication is more robust and durable than one that relies on the precision of user identity. Tools such as MMMs not only provide insights from easily available and verifiable data such as income and advertising expenditure, but also enable traditional advertising channels such as television and out-of-home to be included in the advertising media mix at trade fairs.
4) Deepen your understanding of your audience and rely less on niche products. The products that suffer most from the loss of identifier-based ad targeting are those that target niche audiences and depend on very high monetization rates or very extreme monetization rates of a small segment of the customer base. Building a broader product is one strategy for overcoming the degradation in advertising effectiveness: the more people adopt your product, the less targeted your ads will have to be to reach customers.
5) Get more creative and use it as a differentiator. Without the targeting features unlocked with device identifiers and behavioral histories, advertisers can focus on ad design to increase their ads’ uptake with potential customers. Novel, creative, and attractive ads can’t completely replace the inefficiencies of digital advertising by hiring ad identifiers, but they can help reach the most relevant segment of a target audience by permeating general, unassuming advertisements from competitors. With precision targeting largely removed from the advertiser’s toolbox, the ad creative can be used to highlight the most appropriate parts of the broader audience that the ads will be served to.
* Correction: An earlier version of this article stated that Google announced a similar move in the Android ecosystem. Google has not publicly announced this change.
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