Say farewell to device ID dependency with privacy-preserving measurement
The mobile marketing landscape has seen a seismic shift in recent years due to the evolving privacy landscape. As traditional measurement and attribution methodologies undergo continuous transformation, mobile marketers face a unique set of challenges. As a result, a number of aggregated measurement solutions and methodologies have come into the spotlight to provide a holistic view of marketing performance and privacy-centric attribution.
A seismic shift in how we approach measurement
In the early days of mobile advertising, marketers heavily relied on tracking device-level data to measure the effectiveness of their campaigns. However, mounting concerns about user privacy led to significant changes in how data could be collected and utilized.
Apple’s announcement of iOS 14 back in June 2020 marked an instrumental shift in the industry with its App Tracking Transparency (ATT) framework, as well as Google's restrictions on third-party cookies. These changes fundamentally altered the mobile app landscape–limiting the ways advertisers could measure user interaction. This pivotal moment rattled the mobile marketing industry as we knew it, forcing a reevaluation of how user privacy was handled and redefining the approach to mobile advertising measurement.
Speaking at MAU Vegas 2023, Katie Madding, Chief Product Officer at Adjust pointed out that, “Within this industry every year we see some sort of new change. When Meta was called Facebook they were going to be removing device IDs from our callbacks. Then, we had iOS with the change of deep linking to Universal Links. We had GDPR, then SKAdNetwork, and now we have Google Privacy Sandbox. With that comes opportunities as well as challenges.”
From the initial announcement to the eventual enforcement of ATT with the release of iOS 14.5 in April 2021, the industry was thrown into a whirlwind of adaptation. Adjust stood resilient, collaborating closely with Apple, partners, and clients to facilitate a seamless transition. In this period, the focus shifted from strict attribution and deterministic data to a more balanced approach, with comprehensive analysis inclusive of aggregated data marking a new era in mobile measurement.
Winnie Wen, VP of User Acquisition at Jam City, pointed out the impact on marketers. “In the last few years we’ve faced a number of challenges. As a performance marketer, there’s never been a dull moment. But none of the changes have been as disruptive as the ATT roll out. We lost the ability to hyper-target the audience we want to go after. And more importantly, we lost the ability to measure ROAS,” states Winnie.
“This poses a new challenge as a performance marketer in terms of, ‘What do we do now?’ It sets the stage for re-evaluating and re-assessing everything we thought we knew. We had to come up with a new strategy in terms of how we’re going to navigate and execute UA on iOS in a more effective and profitable manner.”
Enter: Privacy Sandbox on Android
Google then entered the conversation with the announcement of Privacy Sandbox on Android–its own multi-year initiative designed to enhance user privacy while still providing personalized ad experiences. The initiative limits the sharing of user data with third parties and aims to preserve user privacy on Android devices, all while ensuring that apps can continue offering free content and services through advertising.
The current direction for Privacy Sandbox on Android differs from Apple's SKAdNetwork (SKAN) in several ways, including a larger scope, earlier postbacks, multiple report types, and event data coming from Google rather than the network. The eventual public rollout will have a significant impact on the mobile advertising industry, with both users and app publishers now able to opt-in to participate in the beta launch. Adjust has continued its commitment to leading privacy changes as an early tester of this initiative, collaborating with Google to help evolve advertising solutions that balance user privacy and advertiser insights.
New measurement methods rise to the forefront
In response to the challenges brought about by these new privacy frameworks, mobile marketers are shifting their focus from sole attribution to also gaining insights from aggregated data sources.
Aggregated data analysis refers to the process of examining and interpreting data that has been collected, summarized, or combined into a larger, more generalized form without the need for device-level data.
Media mix modeling: A statistical analysis method that employs data science techniques to evaluate and predict the impact of marketing activities on a business's return on investment (ROI). MMM considers both dependent variables like engagements and conversions and independent variables like ad spend across various channels, allowing marketers to incorporate external factors and offline and digital marketing efforts. Deep dive: MMM.
Predictive analytics: A data analysis approach harnessing artificial intelligence (AI) and machine learning to create models that provide marketers with estimates for future outcomes based on specified variables, enabling them to anticipate user behavior and make informed strategic decisions based on data trends.
Incrementality testing: An assessment of the real impact of a marketing initiative on an app's key performance indicators (KPIs), such as installs or in-app purchases (IAPs), by comparing to a baseline of what would have occurred without that marketing effort. A marketing impact may be positive, negative, or neutral. This approach helps mobile app marketers identify activities genuinely contributing to growth and revenue goals. Deep dive: Incrementality measurement.
“We’ve based our measurement approach on what we call the triangulation,” explains Katie. “Attribution is our short-term measurement. The conversion has happened, the install or event has been paid for. You can get frequent, granular data in real-time with attribution.
“Taking it a step further, incrementality is a mid-term measurement. You’re testing out new campaigns, channels, networks, regions. You want to know as quickly as possible if your dollars are well spent. This is where incrementality helps you understand how to test these campaigns. We then see the third, long-term form of measurement being MMM. This is the approach that really allows you to get strategic with your budget allocation, to get the most bang for your buck. All three of these different measurement approaches are the key to next generation measurement that allow you to make directional decisions without relying solely on device-level data.”
Adjust leads the way in privacy-centric measurement
Offering all of the above solutions in our measurement portfolio (contact your Adjust representative for more information), Adjust has been at the forefront of industry measurement changes. Our primary goal, as ever, is to provide mobile marketers with solutions that empower data-driven decision-making and campaign optimization.
In the words of Katie Madding, “The SKAN and Privacy Sandbox frameworks do not complete measurement. There are so many gaps in the data that you can now not do the job you’re meant to do as a growth marketer. That’s where Adust comes in–we’re looking to solve those gaps. Measurement is nothing without optimization and optimization is nothing without measurement. You need both.”
The key to this new, privacy-centric, post-ID era is to combine attribution methodologies with aggregated methodologies in one, cohesive strategy for the most robust, reliable insights possible. Adjust adheres to the following principles of aggregated iOS measurement:
Convert: Adjust assists in maximizing user consent with research-driven opt-in best practices.
Collect: Adjust offers the collection of aggregated SKAN data through an extensive partner network.
Compute: Leveraging both deterministic and aggregated data, Adjust's conversion model computes data points to project performance for non-consented data and KPIs.
Together, these data analysis methods provide marketers with reliable insights in the short-term all the way through to the long-term.
The mobile marketing landscape is undergoing a significant transformation in response to evolving privacy frameworks and user expectations. As we move away from the solitary use of traditional attribution methods, the need for privacy-centric measurement approaches becomes paramount.
Adjust has positioned itself at the forefront of this change, providing innovative tools and strategies to help marketers navigate the new era of mobile marketing successfully. To learn more about how Adjust can help you implement a new generation of measurement, contact your Adjust rep today or request a demo.
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