Efficient use of customer data is vital for businesses to reach their [potential] customers effectively. Customer data platforms (CDPs) and data clean rooms (DCRs) are two distinct tools to reach this goal, each with its unique strengths and capabilities.
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Many know that CDPs offer a comprehensive view of customer touchpoints and seamless campaign orchestration, while DCRs enable organizations to open up beyond their own walls and collaborate externally.
Recently, some CDP providers have claimed to be extending into the DCR space by offering an environment for their customers to collaborate on first-party data. This has led some brands to believe that CDPs are now a one-stop shop for all their first-party data needs. However, this isn&#;t the case, as CDPs often have weaker privacy guarantees and fewer capabilities regarding first-party data collaboration.
In this article, we delve into the strengths and weaknesses of CDPs and DCRs, arguing that both are essential components of a robust, future-proof data strategy.
CDPs and data clean rooms have complementary strengthsMany brands are actively investing in setting up CDPs to navigate the challenges posed by. That&#;s because one of the primary advantages of CDPs is their ability to construct a 360° view across all customer touchpoints. This view makes CDPs very helpful in organizing customer data into one central repository that serves as a single source of truth. By enabling businesses to collect valuable insights into customer behavior, preferences, and interactions, CDPs provide a much-needed boost to the brand&#;s first-party data.
And while many CDPs also offer options for first-party data activation with external partners, the fact is they don&#;t do this in a sufficiently secure manner.
For example, a common method CDPs employ to deliver on these promises is sending personal data such as hashed emails to the other party. Brands relying on CDPs who use this method risk losing control and privacy with their collaboration partner. Still, working together on data is becoming increasingly necessary with the decline of third-party cookies. So how can brands do this in a compliant way?
This is where DCRs come in: Privacy-preserving data clean rooms are the only solution enabling brands to collaborate with external parties in a fully secure and private way. By using these types of DCRs, brands can mitigate the risks associated with direct data sharing and ensure compliance with privacy regulations. This enables use cases beyond mere activation, extending towards innovative collaborations combining first- and second-party data for audience insights, creation, and data enrichment.
By embracing capabilities offered by DCRs alongside their CDPs, brands can bridge the gap between targeting existing customers and reaching untapped audiences, thereby maximizing the effectiveness of their marketing efforts.
It's important to note that brands can seamlessly integrate DCRs into their data strategies without having a pre-existing CDP. All that is required are identifiers, such as addresses from a CRM or customer list, for matching purposes. The strength of DCRs lies in their flexibility &#; allowing brands to derive value even without an extensive dataset.
However, for brands seeking to unlock the full potential of DCRs, the recommendation is to incorporate the richer information made possible by a CDP. The better quality the dataset within the clean room is, the better results brands can expect from their collaborative efforts.
CDPs excel in seamlessly orchestrating campaigns across direct and media channels. This ability to streamline marketing efforts ensures a cohesive and targeted approach. However, the implementation period for CDPs can be lengthy, stretching across several months.
With DCRs, implementation can be achieved within a day, making it an ideal solution for setting up campaigns quickly.
CDPs and DCRs should not be framed as an &#;either-or&#; scenario. Embracing a hybrid approach that leverages the strengths of both CDPs and DCRs is the key to unlocking the full potential of customer data in the new first-party future. It's not about choosing one over the other; it's about harnessing their complementary aspects to propel your data strategy forward.
The deprecation of third-party cookies, increased data privacy regulations and compliance requirements have challenged marketers to shift their marketing and advertising programs towards a first-party data strategy. Now, marketers are exploring new ways to optimize ad spend, create better loyalty programs, and provide the best digital experiences by building direct relationships with customers.
Enter the rebirth of data clean rooms. It&#;s not exactly a new tool for data management, but it helps resolve some of the biggest data-oriented challenges marketers face today. According to Gartner, 80 percent of advertisers with media budgets of $1 billion or more will be using data clean rooms by .
A data clean room is a secure and anonymous private data exchange. It&#;s a database where a company matches its first-party data with aggregated data from a second-or-third-party data source, like a publisher or a trusted partner. Once the data sources are matched up, one or both parties can analyze the combined data to be leveraged for various applications.
Here&#;s how it works:
In most cases, all data is brought into a central location, but there are some examples where distributed data clean rooms (such as from Snowflake) keep the data in its original location, and its owner allows controlled analytics to the other party.
Data clean rooms help organizations process and analyze data from different partners in a secure and compliant way. The best data clean room for your organization will depend on your goals.
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The most prominent examples of data clean rooms today are walled garden data clean rooms that come from big ad media publishers, like Google Ads Data Hub and Amazon Marketing Cloud.
When you work with a data clean room from one of these walled gardens, you analyze the performance of your ads from the individual publisher&#;s platform &#; they do not provide a cross-platform perspective. One drawback of these data clean rooms is you cannot analyze performance across publishers. There may also be restrictions or limitations on how you can use the data.
AdTech vendors or agencies also provide data clean rooms. However, in certain cases, there may be no way to know if the data clean room&#;s attribution model methodology is valid or accurate. If you choose to work with someone else&#;s data clean room, you need to ensure it provides the security necessary to house your first-party data and that your data is appropriately pseudonymized to safeguard the privacy of customer information.
Today, many companies and independent vendors are building their own private data clean rooms. There, they can work with multiple partner datasets to create an omnichannel view of their customer data to analyze for various purposes, like optimizing advertising spend or executing personalized marketing campaigns.
Consumers are now more aware of how brands use their personal information. Privacy laws also continue to come into place to protect consumer privacy. Regulations like the European Union&#;s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are the two most well-known privacy laws, but they are just the start to a broader data regulation environment.
Publishers like Google and Apple have also restricted third-party cookies and have implemented tools that allow consumers to control how their personal data is shared.
Access to first-party data that comes from a consumer&#;s direct interaction with a brand helps marketers understand a lot about their customers, but it doesn&#;t always tell the entire story. Second-and-third party data from partners, publishers, and ad networks help fill in the missing pieces.
Data clean rooms provide access to third-party data that privacy laws and the end of cookies are taking away.
Data clean rooms give this access in a secure, compliant environment, allowing marketers to:
Depending on the type of data clean room, marketers may be also able to build custom audiences that can be sent directly to an ad platform, whether that&#;s a publisher, ad network, a demand-side platform (DSP), or a customer data platform.
There are many use cases for data clean rooms, but the most well-known is between a publisher and an advertiser.
We&#;ve already talked about the walled gardens of Google and Amazon, which publishers own their own data clean rooms. Advertisers bring in their first-party data and then analyze the combined data to understand ad performance. .
If an advertiser works with multiple publishers, they have to perform their analysis separately for each publisher and then manually bring that data together to give them a more holistic view of their ad spend. The same is true if an advertiser wanted to work with a data clean room from an AdTech vendor.
However, there are data clean rooms run by agencies that bring in third-party data from multiple ad networks, publishers, and demand-side platforms, giving advertisers a complete picture of ad spend (though this still would not include data from the walled garden publishers).
Another use case for data clean rooms is for CPG companies. Since CPG companies do not sell their products to consumers directly, they have limited transaction data. They do, however, have first-party data from direct-to-consumer interactions, marketing, advertising, and loyalty programs.
The retailers that sell CPG products have additional transaction data from their own marketplaces or platforms. So, if the two parties combined their data in a data clean room, CPG companies could better understand how their marketing campaigns were driving purchases from the retailer. They could also analyze the combined data to improve targeting and segmentation of their campaigns and offers to specific high-performing segments through a retailer&#;s media network.
While airlines, hotels, and car rental services do not provide the same services, these services are complementary and often are purchased together. If these parties were to combine their data, they could better understand what their target markets want. By analyzing the shared dataset, they may find opportunities to co-market or deliver loyalty programs that provide more value for both the customers and involved partners.
A customer data platform (CDP) is at the heart of your first-party data strategy. It&#;s where you bring together first, second and third-party customer data to build a single customer view that&#;s required to create personalized, relevant experiences at scale.
A data clean room is an extension of a first-party data strategy. A brand can connect its CDP to a data clean room to allow first-party data to be anonymized and analyzed alongside third-party sources. It can also receive data from the data clean room in the form of segments or targeted audiences it can then share with connected marketing platforms for activation.
A CDP does not provide the same environment as a data clean room. But it does give data providers and organizations centralized control of their data and its use. Together, a data clean room and a CDP allows organizations to manage, process and analyze data in way that&#;s safe, efficient and compliant.
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