Tips & Guides — 23 Mar 2023
What is the future of mobile ads?
Mobile attribution has become an increasingly important aspect of mobile app advertising. It enables marketers to track and measure the performance of their campaigns and make informed decisions about their ad spend. However, with the launch of Google’s Privacy Sandbox, the landscape of mobile attribution is set to change, and marketers will need to adapt their strategies accordingly.
Despite the challenges posed by the Privacy Sandbox, the prospects for the mobile app advertising market in 2023 and 2024 are positive. A report by eMarketer says that mobile ad spending in the US is expected to reach $117.35 billion by 2024, up from $87.06 billion in 2021. Below, we can observe the projections for the mobile market in the upcoming years.
One of the key drivers of growth in the mobile app advertising market is the increasing use of in-app advertising. In-app advertising offers a range of benefits over traditional mobile web advertising, including higher engagement rates and more precise targeting. With the rise of mobile gaming and the growing popularity of social media apps, in-app advertising is becoming an essential part of the mobile advertising mix.
Let’s discuss the implications of Google’s Privacy Sandbox for mobile attribution and the prospects for the development of the mobile app advertising market in 2023 and beyond.
Mobile attribution is the process of tracking and measuring the performance of mobile app advertising campaigns. It allows marketers to identify which channels, campaigns, and creatives drive installs and other in-app actions such as purchases or registrations. Mobile attribution platforms use a unique tracking link to follow the user journey from the point of click to the point of conversion. By analyzing this data, marketers can optimize their campaigns, increase their return on investment (ROI), and drive more conversions.
Google’s Privacy Sandbox is a set of privacy-preserving technologies that aim to protect user privacy while still allowing advertisers to deliver relevant ads. One of the key components of the Privacy Sandbox is the removal of third-party cookies, which are used by many mobile attribution platforms to track user behavior across different websites and apps.
Without third-party cookies, mobile attribution platforms will need to rely on other tracking methods such as probabilistic modeling and device graph technology. Probabilistic modeling uses machine learning algorithms to predict which devices are likely to belong to the same user based on factors such as IP address, user agent, and device type. Device graph technology creates a persistent ID that can be used to track users across different devices without relying on third-party cookies.
While these technologies are promising, they are not without their limitations. Probabilistic modeling is less accurate than deterministic methods, which rely on a unique identifier such as an email address or phone number. Device graph technology is also subject to limitations such as device churn, where users switch devices, and user churn, where users uninstall apps or stop using them altogether.
Google’s Privacy Sandbox is an initiative that aims to protect user privacy while still enabling the delivery of targeted advertising. It involves a series of proposed changes to the way cookies and other tracking technologies are used in the advertising industry. The changes are expected to have a significant impact on the advertising market, both for advertisers and publishers.
One of the main changes proposed in the Privacy Sandbox is the replacement of third-party cookies with a new system called Federated Learning of Cohorts (FLoC). FLoC uses machine learning algorithms to group users with similar interests into cohorts, which can be targeted with relevant advertising. This system is designed to protect user privacy by keeping their browsing history and other personal information private while still allowing advertisers to reach relevant audiences.
Another proposed change is the introduction of a new API called Turtledove, which allows advertisers to serve ads based on user interests without revealing any personal information. Turtledove is a decentralized system, which means that user data is processed locally on the user’s device rather than being sent to a central server. This makes it much more difficult for third parties to track users’ online activities.
So, how will these changes affect the advertising market after the launch of the Privacy Sandbox? Firstly, advertisers will need to adapt to the new system of targeting users. With FLoC, for example, advertisers will no longer be able to target individual users based on their browsing history or personal information. Instead, they will need to target groups of users with similar interests. This could mean that advertisers will need to rethink their targeting strategies and develop new ways of reaching relevant audiences.
Secondly, publishers may see a drop in revenue as a result of the changes. With Turtledove, for example, advertisers will be able to serve ads based on user interests without revealing any personal information. This means that publishers may receive fewer targeted ads, which could result in a reduction in revenue. However, some industry experts believe that the shift towards more privacy-focused advertising could ultimately result in more loyal and engaged audiences, which could be more valuable to publishers in the long run.
One of the key components of Google Privacy Sandbox is Federated Learning of Cohorts (FLoC). FLoC is a new way of targeting ads that groups users based on their browsing behavior. Rather than tracking individual users, FLoC creates groups of users with similar interests and serves ads to those groups. This approach is designed to protect user privacy while still allowing advertisers to reach their target audiences.
Another component of Google Privacy Sandbox is Turtledove, which is a new way of serving ads that reduces the need for third-party cookies. Turtledove uses a two-stage auction process to serve ads, with the first stage happening on the user’s device and the second stage happening on the advertiser’s server. This approach ensures that user data is not shared with third parties, improving privacy while still allowing for effective ad targeting.
FLEDGE is another component of Google Privacy Sandbox that aims to improve privacy while still allowing for effective ad targeting. FLEDGE is a new way of serving ads that allows for more transparent and privacy-centric ad auctions. FLEDGE uses encrypted data to ensure that user data is not shared with third parties, and it also allows users to control how their data is used for advertising purposes.
Google Privacy Sandbox has several benefits for both users and advertisers. For users, the initiative will improve privacy and ensure that their data is not shared with third parties without their consent. For advertisers, Google Privacy Sandbox will still allow for effective ad targeting, albeit with a different approach. Additionally, Google Privacy Sandbox will help to standardize privacy practices across the online advertising industry, making it easier for advertisers to comply with regulations and protect user privacy.
Finally, the changes proposed in the Privacy Sandbox could have a significant impact on the broader advertising industry. With Google being such a dominant player in the market, any changes to its advertising policies are likely to have ripple effects across the industry. This could lead to a shift towards more privacy-focused advertising as other players in the market look to keep pace with Google’s changes.
Mobile attribution is an essential component of mobile app advertising, allowing marketers to track and measure the performance of their campaigns. With the launch of Google’s Privacy Sandbox, mobile attribution platforms will need to adapt to new tracking methods to continue to provide accurate measurement and optimization.
As the mobile app advertising market continues to grow, the market inspires good optimism and rapid adaptation to the new conditions of application promotion is possible.
In the next article, we’ll talk about the Federated Learning of Cohorts (FLAC) which is part of Google’s Privacy Sandbox project. It offers an innovative approach to online advertising that promises to provide better privacy for users while still allowing advertisers to deliver targeted ads. With concerns about data protection and privacy on the rise, FLAC offers a new era of mobile attribution that could help balance the needs of advertisers and users alike.
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