Blog Go inside data clean rooms in 2022: An o...

Data is a more poignant topic than ever in 2022, especially for mobile marketers. So, it’s no surprise that the humble data clean room — which first came on the scene back in 2017 when Google launched its Ads Data Hub  — is suddenly the new buzzword again. Thanks to new privacy measures, data clean rooms are particularly relevant to any entity attempting to leverage first-party data. Let’s dive into the definition, uses, and inner workings of data clean rooms as they pertain to mobile marketers.

What is a data clean room?

A data clean room is a neutral, encrypted, and secure space where first-party data from multiples sources is anonymized, paired with aggregated data, and shared. Essentially, a data clean room is ad tech that allows different parties to leverage their user data collaboratively while maintaining control over how, when, and by whom their data is used.

Data clean rooms came about in advance of privacy legislation—such as GDPR in 2018—as a way to continue sharing data in a privacy-friendly way. However, as an entire new wave of privacy-centric measures sweep the mobile marketing landscape, such as App Tracking Transparency (ATT) and cookie deprecation, data clean rooms are re-entering the conversation with a renewed sense of importance.

In practice, data clean rooms have allowed advertisers to break down the walls and get access to aggregated data in a privacy-friendly way.

Different types of data clean rooms

There are several different types of data clean rooms. We’ve listed them below and provided an overview of the advantages and disadvantages of each.

  • Walled gardens: These data clean rooms are provided by big tech platforms like Facebook, Google, or Amazon. These tech giants create a closed ecosystem, whereby they have the control to safely commercialize first-party data. The downside to walled gardens is that they lack a single source of truth, and so advertisers can’t get cross-platform activation data like multi-touch attribution.
  • Diversified providers: With structural flexibility, this group allows organizations to collaborate to get data signals while being privacy compliant. They are typically smaller, established companies in related industries like cloud data storage and marketing applications. On the downside, they offer limited access to walled garden data.
  • Pure players: These are young clean room vendors that develop data clean room software solutions for media companies and brands. They are architecturally flexible and typically offer a more unified view of the data insights. However, they are limited in first-party data granularity and can be difficult to integrate.
  • Mobile measurement partners (MMPs): An MMP is a neutral platform that provides available user-level data within its clients’ business logic to be aggregated and grouped for actionable insights. The real-time user-level and cross-channel data granularity provided by MMPs make it a popular choice for marketers. Check out Adjust, an MMP trusted by app marketers worldwide for app growth.

How do data clean rooms work?

Within the confines of a data clean room, marketers can upload their first-party data — whether that comes from their own site, a Salesforce account, or even their app. The data is then hashed and encrypted, removing all Personally Identifiable Information (PII), including the company identity of the marketer. This is important because it means competitors will not be able to identify an individual company’s data.

For example, in a data clean room, Facebook can share its first-party data with advertisers in a way that complies with regulations and does not violate consumer privacy. In turn, those advertisers can upload their own first-party data and pair it with Facebook’s more extensive set of aggregated data to create more useful insights.

Typically, the insights derived from data clean rooms are at the aggregate level. Keep in mind that while users agree on the parameters, the actual data governance is enforced by the trusted data clean room provider.

What do data clean rooms mean for the privacy-first Internet?

The tide is shifting in favor of user privacy and reshaping the mobile marketing landscape forever. In 2021, ATT went into full effect, but that’s just one of the changes impacting the way we track users on the mobile web and internet. Soon after, Google announced it would stop sharing GAID for users who opt-out.

Even Facebook is moving toward a more privacy-centric model. In October 2021, Facebook announced it would no longer send user-level campaign data to advertisers. Then, in January of this year, Google revealed it is replacing cookies with Topics. Soon thereafter, in February, Google began expanding its Chrome-focused Privacy Sandbox to Android to develop “effective and privacy-enhancing advertising solutions, where users know their information is protected, and developers and businesses have the tools to succeed on mobile”.

It’s clear that the future of the internet is privacy-first, and so, savvy marketers are looking for ways to get results without compromising user trust. Meanwhile, marketers are also challenged by consumers who expect personalized experiences and custom messaging. So, for many, data clean rooms now require a balancing act of the demands of privacy versus personalization.

The role of data clean rooms by vertical

Whether marketers are looking for ways to continue targeting specific users or a path to improving contextual ad targeting, data clean rooms have a role to play in every vertical.

  • Crypto: Many apps faced with the challenges of the privacy era have the advantage of years of data and learnings to draw on. But as one of the newest entrants to the mobile game, cryptocurrency exchanges do not have huge repositories of historical data to draw on, making data clean rooms a great place to find new, helpful insights.
  • E-commerce: No matter how loyal your e-commerce customers are, they inevitably shop at more than one place. In our increasingly privacy-centric world, the only way to know what your shoppers are up to might be to share data in a clean room and simultaneously take advantage of others’ data.
  • Fintech: Fintech shares a lot in common with crypto exchanges, but privacy and security are major concerns for users sharing their financial information. With even more regulation in place for many fintech apps, data clean rooms provide a secure environment to share data.
  • Food delivery: One of the most challenging tasks for food delivery apps is re-engagement. Users typically only use food delivery apps when actively looking for food. Data is integral to effective engagement and retention efforts, and clean rooms can help food delivery apps gain the insights they need to bring users back.
  • Health and wellness: When it comes to health and wellness apps, engagement is everything. Users need to form a habit to see results, demanding that the apps be on top of their engagement game. Understanding when, where, and how to reach users with motivational messaging can mean the difference between success and failure—both for an app and its users. With newer privacy measures, knowing where your users are when they are not in-app and what messaging they respond to is becoming more difficult. Still, with the help of aggregated data from a clean room, you can gain the valuable insights you need.
  • Gaming: Mobile gaming is hot, and competition is fierce. From the initial install to battling it out for in-app time with the other games on your users’ phones, data is what fuels optimization. Mobile game publishers with a portfolio of games have treasure troves of data they can draw on about in-game behavior, but understanding what your users do when they aren’t playing is becoming increasingly difficult. Clean rooms can provide you with more insight into what users are doing when they aren’t playing and, ultimately, will help you know how to better monetize these users.

First-party data is more valuable than ever before, but so is protecting user privacy. By utilizing a clean data room, mobile app marketers can supercharge the power of their data while respecting current privacy regulations.

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