Data collaboration is entering an exciting new era. Data clean rooms are quickly going mainstream, and marketers are beginning to understand the power and limitations of their first-party data.
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First-party data has a market value to others and can be improved by sharing it, a feat that can now be done without exposing personally identifiable data (PII) or even the data itself.
The end of cookies only elevates the need for data collaboration in compliant and secure ways. Marketers still need customer 360s, and the combination of data clean rooms and CDPs can deliver them. The good news is the outcomes will be even better than the old way of collecting data.
Data clean rooms are not new, but they are becoming more mainstream. A data clean room is a secure, governed framework within which third parties, who may or may not be known to each other or the provider, have agreed to work together using the first-party data of one, some, or all of the participants.
A data clean room allows companies to run queries against other's data, to share their own, and to analyze sensitive or regulated data without exposing that underlying data.
They eliminate concerns over privacy laws such as GDPR because personally identifiable information (PII) is anonymized, processed, and stored in a compliant way.
Recently, we've seen the growing popularity of distributed data clean rooms, based in the cloud, which allow parties to exchange and analyze each other's data without that data ever having to move from its original location.
Data is shared but de-identified, greatly streamlining both compliance and security burdens, because every time data moves it creates a potential exposure in these areas.
Not having to move the data also increases operational efficiency as it eliminates the need for time-consuming ETL processes, not to mention the dependency on a data science team, involved in moving data.
Why does this matter? Because the marketer's remit hasn't changed. Marketers must strive continuously for omnichannel, personalized, and differentiated customer experiences and cannot rely on first-party data alone to consistently deliver that.
The distributed data clean room combined with a CDP makes possible a critical shift in the marketer mindset: from being a data consumer to becoming a data producer.
By sharing anonymized data in a clean room environment that may include others in your industry, you can see how others work with that data in ways that can transform how you think about your customers.
And, while it won't be the focus of this blog post, the ability to share data in a secure and governed way also opens the door to potentially monetizing your data, which feeds back into the marketing balance sheet to improve the ROI on your spend. Through a data clean room, marketers can control what data comes in, how data in the clean room may be joined to other data in the clean room, what types of analytics can be performed on their data, and what data, if any, can leave the room.
A data clean room's architecture. Source: SnowflakeYou can see the possibilities here; not only can you securely access data you could not otherwise, but you can see your own data acted upon in ways that glean new insights for you, too.
Data clean rooms keep you in control, allowing you to give access only to those parties with your permission. Some global brands have seen value in using distributed data clean rooms (and CDPs) across subsidiaries, divisions, and business units within their own companies.
This means marketing can elevate its status, once again, as a producer of data and insight, not just a consumer.
Beyond these data-specific benefits, data clean rooms, cloud data platforms, and a CDP work together (and integrate with key marketing tools) to enhance the customer experience and empower marketers to innovate and experiment with marketing campaigns and strategies, such as:
A brand can connect its CDP to a data clean room to not only anonymize its first-party data but also analyze it alongside third-party sources. It can receive data from the clean room in the form of new customer segments or targeted audiences, all augmented from other anonymized data in the clean room, and feed it back into the marketing platform for activation.
Data clean rooms can also help marketers with measuring campaign effectiveness. While your martech stack can measure the effectiveness of a campaign against itself (first phase vs. second phase, or the latest campaign stats compared with the same one run last quarter), anonymous data sharing can help you see how your campaigns performed against companies targeting similar customers.
Distributed data clean rooms allow you to leverage your CDP using live, anonymized data to achieve customer segmentation, explore what-if scenarios such as new segments, and innovate new customer experiences.
A CDP can only be as innovative as the quality of data put into it. With live data shared anonymously from third parties, your CDP is supercharged with fresh insights to enable advanced audience segmentation and improved predictive modeling.
When combined with a cloud-based data warehouse like Snowflake, which can facilitate a distributed data clean room without moving data, we may well find that marketing has leapfrogged past the need for cookies with a secure and governed way to understand customer behaviors and journeys.
As the heart of your first-party data strategy, your CDP becomes an integral part of your data clean room strategy by extension.
In that ever-relentless pursuit of the 360-degree view of the customer, the CDP is the foundation from which you build customized, personal customer experiences at scale.
Data clean rooms bring further dimension to that first-party data, providing a critical edge to your marketing efforts as we navigate the current changes to the digital marketing landscape.
In the digital marketing world, the once-hyped standalone data clean room (DCR) is taking a backseat to a new category ' comprehensive data collaboration platforms (DCPs). These innovative platforms offer a more holistic and scalable approach to data sharing, analysis, and activation, empowering marketers to unlock the full potential of their data.
The Evolution of Data Clean Rooms
Remember the days when clean rooms were touted as the ultimate solution for data privacy, audience insights, and collaborative marketing? While they promised to solve issues like data silos, diminishing identifiable signals, and stringent privacy regulations, their limitations became increasingly apparent. Engineer-intensive data transformation requirements, lack of scaled universal identifiers, time-consuming import/export processes, and high costs prevented clean rooms from being the be-all and end-all of collaborative data matching.
Fortunately, the tides have turned, and clean rooms are no longer standalone products but rather features integrated into diverse and growing data collaboration platforms, like Lotame's Spherical platform. This shift begs the question:
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Do clean rooms have a future on their own, or is their fate to become fully absorbed into these comprehensive solutions?
The Limitations of Standalone Clean Rooms
Let's begin by exploring the value proposition of data clean rooms. When two or more collaboration partners can understand the overlap between their audiences, opportunities arise for co-marketing, contextual targeting, refining campaign messaging, measurement, and attribution. However, standalone data clean rooms often struggle with scalability.
Imagine a brand and a publisher, each with sizable audiences. After narrowing down to authenticated users, they might be left with only 10,000 hashed emails or mobile IDs. If an overlap analysis reveals a 10 percent shared user base, that's merely 1,000 people to target. For most marketers, 1,000 individuals may not be enough to power scaled programmatic and marketing strategies effectively.
The 'Do Something' Dilemma
This scenario might evoke memories of the Customer Data Platform (CDP) craze, where the industry buzzed with the possibilities of collecting and activating first-party data, only for marketers to realize they lacked sufficient data to execute scaled strategies.
Like some CDPs, standalone clean rooms fall short in the 'do something' aspect. After the work of preparing, sharing, and permitting data, what insights can a marketer gain? How can they make those insights actionable? How do they derive value from their actions?
While those 1,000 customers might not be viable for scaled prospecting on their own, integrating them into a machine learning algorithm, performing identity resolution, or analyzing their intersections with second and third-party data could extrapolate them to a wider audience of net-new consumers and IDs. This is where the power of data collaboration platforms truly shines, unlocking new opportunities for audience targeting and personalization.
The Power of Integration
The integration of clean rooms into larger data collaboration platforms makes perfect sense. Clean rooms become one option among many methods for partners to achieve their marketing and monetization goals, with all the necessary pipelines for downstream data activation already built-in. Data clean rooms are far more effective as part of the data puzzle rather than being treated as the whole solution.
It's important to note that standalone clean rooms still have a place in the market for truly giant brands and media owners with millions of customer records, robust in-house data platforms, and integration with universal identifiers. For these industry juggernauts like Disney and Amazon, a point solution might suffice.
Data Collaboration Today
The strongest evidence of clean rooms being absorbed into larger data collaboration platforms lies in the market movements over the past year. Companies providing identity solutions and data marketplaces are either building their own clean room functionality or acquiring clean room providers, as seen in LiveRamp's $200 million acquisition of Habu.
This strategic move aligns with marketers' desire to interact with data enrichment, identity resolution, scaling, and downstream activation capabilities without moving their data. By integrating clean room functionality into the entire platform, a one-stop-shop for data collaboration is created, streamlining the process and minimizing the need for multiple-point solutions. Lotame's end-to-end data collaboration platform Spherical, is one example of a comprehensive data solution for collecting and connecting, enriching, modeling, collaborating and activating data.
The Walled Garden Approach
One area where movement has been limited is within the walled gardens operated by companies like Disney and Meta. Their clean rooms are not standalone but are designed exclusively to commercialize their own first-party assets. While brands can bring their data to find matches with these walled gardens' customer data, doing so beyond their boundaries has proven futile.
Amazon, perhaps due to its sheer scale, has been an exception, straddling the line between a walled garden and a collaborative platform ' a 'hedged garden,' if you will. While activation and personalization are ultimately confined to Amazon's programmatic ecosystem (with promises of direct pipes with third-parties in the future), its push for interoperability with identity solutions and the launch of modeling capabilities indicate a more open attitude that may be built upon further.
The Future of Data Collaboration
Have data collaboration platforms figured everything out? Given the complexities of data sharing and activation, it would be naive to say yes. However, what they have is a North Star goal for broad connectivity and interoperability across platforms and solutions, and there is widespread movement towards achieving it.
As Lana Warner, Senior Director of Partnerships & Strategic Solutions at Lotame, aptly puts it, 'While clean rooms might be appropriate for the Disneys and Amazons of the world, the vast, vast majority of marketing happens beyond such juggernauts, and the solutions that cater to this majority are building toward data collaboration with a far broader scope.'
The rise of data collaboration platforms is revolutionizing marketing strategies, offering a comprehensive and scalable approach to data sharing, analysis, and activation. By embracing these innovative solutions, marketers can unlock the full potential of their data, foster collaborative partnerships, and drive more effective and personalized campaigns. With the ability to integrate diverse data sources, leverage advanced analytics, and activate insights across multiple channels, data collaboration platforms empower marketers to stay ahead of the curve in an increasingly data-driven landscape.
As the industry continues to evolve, the lines between traditional marketing tools and data collaboration platforms will likely blur, giving rise to more integrated and unified solutions. Marketers who embrace this shift and leverage the power of data collaboration platforms will be well-positioned to deliver exceptional customer experiences, drive business growth, and thrive in the ever-changing world of advertising technology.
This article was originally published by Performance Marketing World.
Learn more about Lotame's end-to-end data collaboration Spherical, and how it can help you onboard, connect, enrich, and activate data ' whether you have it or need it ' to better understand and engage consumers. Contact us today!
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