Implementing a Data Clean Room in Your App Marketing Strategy -

Implementing a Data Clean Room in Your App Marketing Strategy

In today’s world, industries are becoming more reliant on the need for data between parties. Consequently, data clean rooms are quickly becoming increasingly popular, especially in the app marketing space. By utilizing a data clean room, app marketers can, both, ensure that their data is secure and easily shareable with advertisers or publishers for collaboration. In this blog post, we’ll discuss how to implement a data clean room in your app marketing strategy.

What is a Data Clean Room?

Unlike its traditional counterpart, a data clean room is an online framework service that does not require any physical space. Through a data clean room, a marketer can confidently share his or her data with multiple parties, whilst ensuring its privacy, and still providing recipients with the necessary information to draw their conclusions. It is an online cloud service provided by ‘data warehouse as-a-service’ companies like Snowflake or AWS.

How does a Data Clean Room Differ from Other Data Sharing Services?

Data clean rooms are different from other data-sharing programs because of the fact that they give data admin’s ability to set rules on the types of queries that data recipients can run on the data. This essentially removes the need for data encryption methods like customer ID, device ID and/or cookie ID; a data clean room can allow app advertisers to unveil first-party data to other stakeholders without revealing any sensitive information. All information within a data clean room is fully encrypted, however, it can be shared with intended audiences without encryption if the data owner wishes to share information.

How Does a Data Clean Room Work?

Data Collection

The ad campaign data is funneled into the data clean room via an attribution tool, the app itself, or a third party ad network’s CRM tool (to name a few) via a pull API function.

Data Collation

The data is passed through the admin’s ruleset in order to censor sensitive information. If the data is being input into the clean room from multiple sources it is matched at the user level to present enriched and collated data.

Data Analytics

Once all the data is presented in fully enriched and censored form, the third operation of the data clean room is the analysis stage. The data is studied for any intersections or overlaps and analyzed for attribution purposes and propensity scoring. There are multiple use cases for data from a clean room that can differ based on the needs of its users.

Data Applications

After the full analysis of the data, marketers are able to make use of the output in order to launch deeper campaign examinations, build more relevant audiences (often through means of a co-marketing partnership) via better targeting, optimize their campaigns and execute cross-platform marketing strategies.

What are the Benefits of Data Clean Rooms to App Marketers?

Adhering to Privacy Regulations

Nowadays, app marketers have to take a new approach to sharing data especially given the state of GDPR and strict regulations on sharing the personally identifiable information (PII) of their app users. In instances where an app marketer needs to share information with a publisher in order to optimize campaigns, the data often needs to be aggregated or simply not shared in order to not breach privacy regulations. Data clean rooms allow advertisers to overcome this issue and give end users the necessary peace of mind that their data is fully private and secure.

Enhancing Publisher’s Data Analysis

In addition to complying with privacy regulations, data clean rooms allow app advertisers to share their unadulterated data streams with their intended recipients (publishers like DSPs for example) for examination. In instances when publishers require a deep dive in order to optimize campaigns on sub-source levels, data clean rooms will allow them to do so without running into the issue of data encryption. Encrypted data (or the overall lack of it) tends to hamper room for analysis and can cause long term problems in the advertiser-publisher relationship. Data clean rooms have essentially solved this gaping issue in the martech industry by allowing advertisers to share data with their publishers to make their analyses, whilst censoring the sensitive PII of their end users.

Improving Campaign Optimization and Targeting

As app publishers will have access to first-party data via data clean rooms, they will have more information to work with directly from the source itself. App marketers will gain the benefit of being able to optimize their campaigns better and target particular audiences as they will grant their publishers the necessary information to do so.

Time-Efficient Sharing Method

As an app marketer, you will certainly be able to shave off the great deal of time that it takes to collate data into a CSV to be shared with your stakeholders due to the enormous amount of sensitive information it contains. Data clean rooms only require you to initially set up a certain set of rules as to what information you wish to display to censor and to which viewing party; the app campaign data will continue to be displayed in real-time via a pull API afterward so you do not need to keep adding your ruleset. Time saved is time earned.

Co-Marketing Partnership Opportunities

App marketers do not necessarily need to use data clean rooms just with their publishers; given that the sensitive data of the end users is secure, you can also share it with companies that share your target market and create a value-added partnership. As a result of this partnership, companies sharing a data clean room can create better-detailed profiles of their target market in order to service and market to them better all the while keeping their user’s PII private.

How Should an App Marketer Maintain a Data Clean Room?

After having created a data clean room, your next biggest challenge is maintaining it. A data clean room is only as valuable as the effort you put into it; it should be kept up to date and organized to ensure the accuracy of the data and the success of the app.

Here are some tips for maintaining a clean data room:

Organize your Data

It’s important to keep your data organized in a way that makes sense for your team. This includes sorting and labeling data, as well as ensuring that the data is up to date.

Use a Database

A measurement database like an attribution tool is a great way to store and organize your data and sort your marketing channels. It will help you keep track of all the data you have, and make it easier to access and analyze it when you need to.

Use Data Analysis Tools

Simply adding data to a clean room won’t make much sense alone; data analysis tools can help you study important figures and trends from the data you have, and determine which data is most useful based on your purpose.

Keep your Data Secure

Data security is key, so make sure you have the necessary measures in place via the rulesets to ensure that the sensitive information in your dataset is censored from other parties that have access to your clean room.


Data clean rooms are definitely a game changer in the mobile marketing industry. With industry-shaking updates like GDPR, Intelligent Tracking 2.0, and Apple’s ‘opt-in’ requirements there is a clear trend towards enhancing user PII privacy, and app marketers will soon be flocking towards data clean rooms in order to maintain their operations as martech depends on the sharing of information between advertisers and publishers. 


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