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Editorial

Tips to Inform Your Customer Data Clean Room Strategy

7 minute read
Jonathan Moran avatar
Are data clean rooms the answer to accessing high-quality customer data for marketing?

By now, most marketers are aware of the convergence of global factors that will undoubtedly make targeting and measurement more difficult to perform in the future. 

  1. The deprecation of the third-party cookie by Google, which is forcing brands to rethink their entire customer data strategy, all the way from zero-party data through first- and second- to third-party data.
  2. A byproduct of data deprecation is the intensified creation of “walled gardens” or data repositories that are created and owned by big tech players for data control and monetization.
  3. New channels such as in-game, in-stream and in-app combined with new environments like the Metaverse are causing marketers and advertisers to reconsider how they collect and interact with customer data.
  4. Demand by consumers for privacy and control over their data has never been higher.

It seems that almost daily new policies, processes and practices are being put in place concerning what and how customer data can be collected, leveraged and shared.

Are Data Clean Rooms the Answer?

Can data clean rooms help us access high-quality customer data for marketing and advertising targeting and measurement? The concept of data clean rooms has been around since Google launched Ads Data Hub in 2017. For those not familiar, a data clean room is a secure data environment that enables brands to access anonymized marketing and advertising data (usually second-party in nature and shared by bigger tech brands) to augment marketing and advertising interactions with end customers in a privacy-friendly way.

Recent talk of data deprecation has created a resurgence in data clean room talk, as well as discussion surrounding private walled garden creation. 

Related Article: 5 Targeting Recommendations for a Post-Cookie World

Walled Garden vs. Data Clean Rooms

Initially, walled gardens and data clean rooms were thought to be synonymous, but this is not the case.

Walled gardens are data repositories owned by big tech brands that can collect marketing and advertising data and then monetize that data — both internally and externally.

Data clean rooms, which can be either private (brand use only) or public (shared with partners), provide additional security and privacy protocols that walled gardens don’t always have. Additionally, you can purchase data clean room software — whereas you can’t purchase walled garden software. However, as data clean rooms gain popularity, their viability remains uncertain — mainly due to the lack of customer validation and general usage. Many questions remain around data clean rooms, including:

  • How will a data clean room fit into my marketing and advertising ecosystem?
  • What level of data detail they will provide?
  • How useful that data will be for targeting, personalization and measurement purposes?
  • What use cases will I accomplish with my data clean room software that I can’t accomplish today?
  • Do I need a data clean room or are the capabilities present in other solutions within my ecosystem, such as my customer data platform?

One thing is clear — marketing and advertising technologists should consider several key factors when deciding if and when a data clean room makes sense for your brand.

Data Security and Privacy Are Paramount

The entire premise of a data clean room is to provide access to collaborative data without jeopardizing consumer privacy or a brand’s data security protocols. To that end, security and privacy techniques for customer data must be embedded in the data clean room solution. Data clean rooms must have techniques like identity management, graphing, obfuscation and resolution present. 

In some instances, identity management and resolution solutions can be appended to the solution, but that adds a layer of complexity to data movement and usage processes. Data clean rooms must be able to ingest, join, store and protect customer profiles in an automated fashion.

Ideally, customer data is encrypted during both storage and transit — so that even marketers that interact with the data clean room solution are not exposed to the data. For more advanced users that choose to extract audiences from a data clean room solution, capabilities like obfuscated cohort creation and differential privacy should be available.

Related Article: Is Bad Data Ruining Your Customer Experience?

Learning Opportunities

Data Governance Follows Closely Behind

Out-of-the-box security and privacy controls are important but are only as good as the processes that they lead to. Talend defines data governance as a collection of processes, roles, policies, standards and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.

As you define your data clean room use cases, it’s important to also define how and where data will move — as well as exactly how data from your clean room will be used. This means knowing and documenting what data manipulations and governance processes are needed — this may include knowing how data is normalized, how it is joined or appended and what data attributes are zero- and first-party data as well as what may be second-party data coming from your data clean room. Data governance documentation will serve your organization well from a risk and compliance perspective as well, ensuring data is being used correctly from a legal and ethical perspective.

Additionally, if data is manipulated to make it more effective for certain use cases, for example revealing encrypted identifiers or attributes, processes must be in place to “de-identify” the data when it is exported from the clean room solution. If data is not de-identified properly and violations do occur, clean room solutions must offer manners in which to remediate those violations.

In short, B2C marketers should demand transparency surrounding data governance. The responsibility for this is lies equally between the data clean room vendor and the purchasing organization.

Data Integration for Analysis and Activation

Now that the data privacy and governance aspects are covered, it’s time to consider how to analyze and activate data coming from your clean room. At the minimum, data clean room solutions should offer capabilities for:

  • Customer Understanding. Augmenting customer profiles with additional data insights is perhaps the top use case for clean rooms. Data from big tech providers that will reside in clean rooms will benefit the analysis that needs to be done to inform audience creation, look-a-like modeling, media planning (attribution and optimization), cross-publisher and cross-platform campaign success, and ultimately downstream engagement.
  • Customer Engagement. With browser and identity deprecation on the way, brands will need access to customer data that they will not be able to easily obtain via their current data collection methods. This data will be appended to a brand’s existing customer profile information in solutions like customer data platforms and help to serve as the foundation for customer prospecting and marketing purposes.
  • Data Monetization. For some brands, placing their data into a clean room solution and then offering access to partners to that clean room becomes a way to monetize data assets. A great example of this is the rapid rise of retail media networks, whereby retailers make their audience data available to partner brands to match their first-party data against. This allows the retailer to monetize their data and the partner brand to perform marketing and advertising on retailer domains or subsites to better inform their marketing, engagement, product development and other future strategies.

Recognize Costs, Martech Vendor Capabilities

As you work to develop your data clean room strategy, consider your data privacy and security, governance and analysis and activation needs. You will need to understand your marketing and advertising spend and map out use cases where a data clean room would be involved to determine what will work best in your platform ecosystem.

It certainly wouldn’t hurt to ask existing vendors within your martech stack if they offer clean room capabilities. I imagine some traditional enterprise marketing technology vendors will be adding clean room capabilities to their product listings shortly.

Last but not least, understand the costs and resources involved with deploying a clean room at this stage in the game — knowing that things are continually shifting in the marketing and advertising world!

About the author

Jonathan Moran

Jonathan Moran covers global product marketing activities at SAS, with a focus on customer experience and marketing technologies. Prior to SAS, Jon gained over 20 years of marketing and analytics industry experience at both Earnix and the Teradata Corporation in pre-sales, consulting and marketing roles.

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