April 29, 2021

Apple Is Changing How Digital Ads Work. Are Advertisers Prepared?





Summary.   

The rollout of Apple’s new privacy settings is upending the rules of digital advertising on the iOS platform. By limiting advertisers’ ability to track user behavior, Apple is forcing them to adapt to a new paradigm — and fast. As other tech companies may soon follow suit, this disruption is an opportunity for advertisers to prepare for the coming era. They should embrace new privacy preserving approaches; know that privacy workarounds are a short-term strategy at best; transition away from user-centric models; invest in better understanding their audience; and use ad creativity as a way of differentiating themselves from rivals.

Apple is turning the privacy settings of its mobile ecosystem upside down. When it releases its app tracking transparency (ATT) framework with iOS 14.5 on April 26, it will shut off a stream of data that app developers, measurement companies, and advertisers have used to link users’ behavior across apps and mobile websites — a move that could reshape the digital advertising industry. With the update, the “identifier for advertisers” (IDFA), which has been activated by default on Apple devices and provides access to user-level data to app publishers, will be switched off and users will need to grant apps explicit permission to access it. With in-app prompts asking users, “Allow [app name] to track your activity across other companies’ apps and websites?” opt-in rates will likely be low. 

We anticipate that Apple’s ATT initiative will deliver a major blow to targeted advertising, which is crucial to the business models of publishers of online content such as Facebook, Google, and many news outlets. But while large digital content providers will feel the effects of ATT, the large proprietary datasets they’ve amassed may protect them in the long term. Smaller companies, such as e-commerce operations that rely on targeted advertising to reach customers, and mobile measurement providers, which collect and organize app data, will likely find it harder going — a point Facebook has tried to bring home in a campaign responding to Apple’s policy changes.

Through the rollout of ATT, Apple is re-imagining the role that advertising plays within its ecosystem. The move will allow the company to more tightly control users’ app experiences and content curation. It will also allow Apple to push adoption of its own target advertising solution — its in-house ad tracking services use friendlier language than what is required of third-party apps and it recently introduced new ad spots on the App Store. Establishing itself as a leader in privacy can serve to strengthen its brand and have lasting positive effects on its hardware sales to boot.

While ATT might be the most impactful change to the digital advertising ecosystem to date, more restrictions around user privacy are in the offing. Developments such as private click measurement (PCM), Google’s Federated Learning of Cohorts (FLoC), the end of third-party cookies in Chrome, and governmental privacy regulations such as GDPR and CCPA all point to a new privacy-centric era on the horizon. That means that advertisers and advertising firms need to learn how to play by a new set of rules — and fast. Here’s a primer on how you can be prepared to navigate the changes.

What ATT Changes

Apple’s new approach to privacy presents a clear problem for advertisers who rely on targeted advertising — in other words, most digital advertisers — in that it will make it much harder to meaningfully link user behavior across apps and mobile websites in the iOS ecosystem. Depending on opt-in rates (which, again, are expected to be low), this presents a major challenge for advertising targeting algorithms that achieve their current good performance by observing not only what ads users view and click on, but also who then proceeds to take relevant actions on the website or in the app of the advertiser.

Overall, ATT can be expected to make ads substantially less relevant for consumers and to make them perform substantially less well for advertisers — except for ads delivered by Apple’s own personalized ads system. It also reduces the precision of advertising measurement across iOS apps and mobile websites. Many industry insiders expect Google to make a similar change in the Android ecosystem at some point in the future, effectively rendering digital advertising less relevant across the board and its measurement much less granular and precise.* These changes in the digital measurement landscape roll back some of the innovations that became possible through digitization, namely precise measurement through user-level attribution and advertising experiments.

To aid advertisers in navigating the limitation in data availability introduced by ATT, Apple is offering a measurement solution called SKAdNetwork (SKAN) that makes performance data available at the campaign level. However, not only is there a limit on the number of available campaign slots per advertiser, SKAN also adds a random time delay on the observation of performance events such as purchases or cart-adds and restricts how and how many of such events can be observed per campaign.

SKAN falls within the sphere of differential privacy, an approach to marketing measurement that uses statistical methods to make it impossible to infer any individual user’s behavior while still allowing linking of behavior across different digital properties. Differential privacy is likely to become more prevalent. Other tech companies, such as Google, are investing significantly into such technologies as well but there may be a long way to go before wide acceptance and adoption as a new privacy-safe measurement approach.

In the meantime, more traditional measurement solutions that are privacy-safe by default will likely stand to gain in relevance. For example, marketing mix models (MMMs) were developed on and for aggregate advertising and sales data observed over time and do not require any linking of lower-level tracking data. They make use of natural variation in a firm’s marketing mix or, where possible, of explicitly induced randomization over time and/or geographies to measure advertising effects. Bearing testament to the likely renaissance of MMMs in marketing measurement, Facebook published an open-source computational package that allows advertisers to implement MMMs in a guided manner.

How You Can Adapt

So what should advertisers and advertising firms do? We believe that internalizing the following strategic viewpoints can help businesses navigate this changing privacy landscape.

1) Embrace privacy preservation methodologies like differential privacy (Apple) and federated learning (Google). These are the primary means by which large platforms are ushering in new privacy protections for consumers — firms that are planning ahead should build advertising technology that aligns with them.

When privacy policy changes, the biggest pain point for advertisers is infrastructure upgrades. This sea change should be seen as an opportunity to invest in new and innovative technologies that not only comply with platform regulations but do so in a way that is forward looking. New restraints on the data that can be used for measurement and analysis can create competitive advantage in moments of dramatic change, when competitors are reticent to invest or adapt.

2) Understand that workarounds to new privacy regulations are not a viable, long-term solution. It may seem relatively cheap or straightforward to build solutions that preserve advertising workflows and measurement schemas by sneakily contravening platform policies — using device fingerprinting or server-to-server conversion management — but taking this approach merely delays the inevitable pain of adaptation. A firm should make investments into real solutions, not gimmicks that exploit loopholes or are predicated on rules not being fully enforced, especially since the privacy landscape is currently mostly dictated by large platforms that mostly operate according to their own rules.

3) Transition advertising measurement away from deterministic, user-centric models. Instead, use more holistic, macro-level models that look at variations in ad spend and revenue over time to attribute efficiency to channel-specific ad campaigns. This approach requires sophisticated data-science expertise, and these types of models can be difficult to tune properly, 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 like MMMs not only provide insight from data that is readily available and affirmable such as revenue and ad spend, but they also allow for traditional advertising channels such as television and out-of-home to be included in the advertising media mix and accommodated for in measurement.

4) Deepen your understanding of your audience and rely less on niche products. The products that suffer most in the loss of the identifier-based advertising targeting are those that target niche audiences and depend on very high rates of monetization participation, or very extreme levels of monetization from a small segment of the customer base. Building a more broadly appealing product is a strategy for overcoming the degradation of advertising effectiveness: The more people that are receptive to your product, the less targeted your ads must be in order to reach customers.

5) Get more creative and use it as a means of differentiation. Absent the targeting capabilities that are unlocked with device identifiers and behavioral histories, advertisers can focus on ad creative as a way to increase the reception their ads receive with potential customers. Novel, creative, and attractive ads can’t fully replace the efficiency lost in digital advertising from the deprecation of advertising identifiers, but it can help to reach the most relevant segment of an audience by penetrating through generic, nondescript advertising from competitors. With precision targeting largely removed from the advertiser’s toolbox, ad creative can be used as a way to stand out to the most appropriate portions of the broader audiences to which ads will be exposed.

Apple’s ATT framework may be the most economically impactful and brazen change to privacy policy in years. It won’t be the only one, however. As this step is likely the start of a new era rather than an outlier event, we recommend using the opportunity to brush up on privacy technologies such as differential privacy and federated learning and to sustainably revamp your marketing measurement toolkit.
*Correction: An earlier version of this article stated that Google had announced a similar move in the Android ecosystem. Google has not publicly announced this change.

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