Welcome to another episode of the Mammoth Growth podcast! In this episode, Data Consultant and former VP Data of FREENOW Dr. Tim Wiegels joins EMEA President Stuart Scott and one of our Consultants, Paddy Doran, to discuss the privacy-related changes coming in iOS 17 and their impact on marketers and data professionals.
Tim, Stuart, and Paddy discuss two major changes to the privacy landscape courtesy of Apple: link tracking protection and privacy manifests. With link tracking protection, Apple will start cutting UTM link parameters that may identify users when they open links from mail, messages, or Safari private browsing. Paddy notes that users can already opt in to link tracking protection on iOS 17 beta, and that in the coming months this could affect user tracking and targeting. Paddy then points out that you can think about privacy manifests as an extension of an app’s “nutrition label” in the Apple App Store, where apps need to disclose the data they collect and how they use it. Third-party SDKs will also need to create privacy manifests, increasing transparency and accountability.
The hosts also discuss the challenges and opportunities these changes present, such as the end of fingerprinting / probabilistic attribution and the role of Mobile Measurement Partners in managing privacy and data. Tim then makes a key observation, that as users’ privacy concerns and Apple converge towards heightened privacy protections, “...that we might not need MMPs anymore because if you push something to the Apple App store, they will be your MMP.”
On the topic of bias in marketing attribution, Tim relates a quick story about setting up mobile attribution during his work with FREENOW. Since they thought only a maximum of 30% of their users on iOS had opted into tracking, they considered using these 30% of iOS users and 100% of their Android users to build their mobile marketing attribution heuristics. But they ultimately decided against this approach. They realized that this large sample size contained mostly Android users, but they knew most of their revenue was coming from iOS users. “So really using this large chunk of non-revenue generating users to predict the revenue generating users didn't make sense,” Tim and his team at FREENOW concluded. With this anecdote, Tim reveals the difference between building a marketing attribution model on enough data vs building one with the right data.
Tim, Paddy, and Stuart emphasize the importance of adopting incrementality testing and uplift modeling to understand the impact of marketing efforts and make data-driven decisions. Paddy advises companies to be careful about plugging gaps with user-level data, since this will likely provide only short-term relief and can quickly turn into a game of whack-a-mole. Tim concludes the conversation by asserting that companies can weather the coming privacy apocalypse by focusing on their KPIs instead of fixating on minute fluctuations in user activity.
Thanks for listening!
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