The last two years in digital media have seen more turbulence than the previous eight combined.
We’ve had successive announcements from platforms like Apple and Google, ever-growing regulatory headwinds, and a rising tide of consumer backlash against centralized data & intelligence fuelled in part by the rise of blockchain and Web3.0. Given the scale and pace of today’s emergent challenges, you’d be forgiven for burying your head in the sand.
But as the old adage goes “with change comes opportunity”, and large media companies like Disney and NBC Universal are doing just the opposite, launching new, privacy-first, and decentralized audience and data solutions powered by data clean room technology. In fact, data clean rooms are quickly becoming our industry’s newest buzzword(s).
What Is a Data Clean Room?
A data clean room is a secure, protected environment that enables two or more parties to bring data together for joint analysis with privacy, security, and governance rules in place.
Data clean rooms are the future of data collaboration, but they’re not a new idea. Historically, clean rooms were used in a variety of use cases, but almost always involved data owners shipping their data to the clean room.
Today, it is secure, privacy and governance-protecting software which enables companies to do three things:
- Join distributed datasets securely, without moving or exposing the underlying data
- Provision appropriate data access and privacy/governance measures
- Leverage the power of joint datasets to power end-to-end marketing applications including Measurement, Segmentation, Activation, Incrementality Experimentation, Overlap Analysis, Reach and Frequency Analytics & Management, Consumer Journey Analysis, Propensity Scoring, Machine Learning, & more
Why Do Data Clean Rooms Exist?
According to Gartner, 73% of marketers fear that privacy concerns will negatively affect their analytics and the organizations that promote data sharing are the ones that will outperform their peers on most business value metrics by 2023. With less data available to marketers and agencies “off the shelf”, data clean rooms offer a way for data owners (such as publishers and retailers) to provide privacy-first data offerings that strike the right balance of access, aggregation and advantage to their partners.
When evaluating why data clean rooms have emerged and are being readily adopted, three main themes emerge: privacy and control, unifying disparate data, and the constant desire for higher quality data.
1. Privacy and control
With third-party cookies on the way out and the industry embracing a privacy-first mindset, data will remain distributed under lock and key. This shift in the consumer data landscape has created uncertainty for marketers as tactics such as targeting and measurement are becoming increasingly more complex and difficult. While these changes create many challenges, they also open the door to new opportunities and ways for companies to reimagine their data strategy in preparation for the future.
Data clean rooms are the vehicle for media companies to securely share data with key advertising partners while maintaining full control over how, for how long, and where that data can be used. As privacy regulations continue to evolve, clean rooms are built to adapt to work within the framework of new privacy laws. Privacy-preserving techniques ensure that no source data is ever exposed in its raw form and no personally identifiable data is ever shared with anyone.
2. Unifying disparate data
No single view of the customer is possible without understanding media exposure, yet data lives in multiple silos, both within a single organization and across potential partners who have similar interests. Modern marketing is interconnected. But it’s not realistic to believe that consumer data can ever be fully unified in one platform. Moving data is a huge security risk. It needs to be protected where it lives, when in transit, and wherever it lands. Co-mingling data in a single platform is an antiquated approach to collaboration and smart companies are not moving their data. Data clean rooms enable safe, secure analysis of data wherever it lives.
3. Accessing higher quality data
As restrictions become tighter and tighter, brands are starving for more high quality data to make better business decisions and make their marketing more effective. Media companies have that data but may have been hesitant to share it in the past due to privacy concerns and lack of control. A clean room enables both parties to have transparency and control over what and how data is accessed and used, while ensuring that consumer privacy and consent is protected in line with all external regulations and internal policies. This opens up a whole new world of possibilities and mutually beneficial business growth for media companies and their advertising partners alike.
What Are the Types of Data Clean Rooms?
There are three main types of data clean rooms: walled gardens, pure players, and multi-platform. Some larger companies have also taken on the challenge of developing their own in-house data clean rooms.
Walled Garden Clean Rooms
The most common media clean rooms today are those within the Walled Gardens, which are closed platforms that enable privacy-safe analysis within that single environment. Amazon Marketing Cloud (AMC), Facebook Advanced Analytics (FAA), and Google Ads Data Hub (ADH) are the three big players, but more walled gardens are mooted to have clean room offerings in the pipeline.
They support first-party data set enrichment with their own event-level data, but they can be inflexible and often difficult for the everyday business person to use; requiring a data scientist to extract the insights available. They are also isolated in their design, and not interoperable with one another.
Neutral Clean Room Vendors
Pure players are companies that are developing data clean room software solutions for media companies and brands to use. Some of the players in this space include Habu, InfoSum and LiveRamp. They offer more flexibility, allow for collaboration, offer a more unified view, and can be easier to use without a data scientist present. Some require third-party infrastructure for data ingestion and are limited in first-party data granularity. Some also have narrow downstream integration options.
Clean Rooms Within Other Platforms / Ecosystems
Some businesses that operate in adjacent industries like cloud data storage or have specific marketing applications have announced their own data clean room solutions. This group includes providers such as Snowflake, BlueConic, Epsilon, and Merkle.
The warehouse-level offerings from the likes of Snowflake offer architectural flexibility and governance controls but are technical solutions. Those embedded within marketing applications may offer ease of access, but typically have limited access to partner data outside of their ecosystem, as well as no connections into walled garden data clean rooms that matter to brands.
What Are the Common Use Cases for Data Clean Rooms?
Media companies and brands use data clean rooms to compete with walled gardens; the media company is not only a place to run ads, but it also can offer a deeper level of insight with rich data assets along with media.
Data clean rooms enable companies to privately and securely share disparate data, either among their own brands (consider a company like Hearst that has more than 360 brands with their own portfolio) or with partner companies, like CPG, automotive, entertainment, and retail.
Here are some examples of common use cases:
- Accelerate ROI across the Campaign Lifecycle: A media empire with a large portfolio of brands is offering a unique and differentiated offering to their advertising partners. Through privacy-safe clean rooms, they are empowering advertisers to connect their own first-party data to impression logs, audience segments and user attributes to deliver richer, more actionable consumer insights while being able to address and adapt to a changing data and privacy landscape.
- Reimagine the Customer Journey: A luxury automotive company is closing gaps in the customer journey by leveraging a data clean room to safely tap into signals from a large auto classifieds site to reflect the most recent behaviors, intent signals, and additional attributes that make up a complete consumer profile. By synthesizing comprehensive and accurate data about their consumer’s interests and behaviors, while not revealing personally identifiable information, the publisher enables its advertising partners to deliver better experiences for consumers and more effective campaign performance.
- Improve Media Measurement: A global beauty brand is driving increased efficiency and effectiveness across their entire portfolio of brands by leveraging the user- and impression-level campaign data that is uniquely available in the Amazon Marketing Cloud clean room and expanding the scope of campaign insights.
How Do You Get Started with Data Clean Rooms?
First movers will definitely have an advantage and media companies have a head start with using data clean rooms for collaboration because they already have some of the key advertising relationships in place. Other types of businesses, including CPGs, retailers, and agencies, might need to do a little legwork to identify and establish partnerships, but now is the time for companies to set the foundation for their future.
3 Ways for Companies to Get Started Today:
- Identify the types of insights from shared data that would most benefit their business
- Determine their potential data collaboration partners, either internally or externally
- Explore and select the data clean room solution(s) that best fits their needs
Data clean rooms offer companies of all types to unlock collaboration opportunities not imaginable before. Media companies and retailers can offer unique and differentiated solutions to their advertising partners. CPG, automotive, and other companies can now access new and rich data signals from strategic partners to enrich consumer profiles and improve targeting and measurement.
With the rise of clean rooms and data collaboration, agencies will be relied on heavily for strategy and execution. As measurement and other tried and true marketing tactics become increasingly difficult and data continues to remain distributed, innovative brands are seizing the moment to revamp their strategy and explore and test new solutions that will not only evolve but thrive amidst these changes.