In September, I took to the stage at DMEXCO to discuss why companies and individuals who have only been focused on cookies have completely missed the point. The transition our industry has been going through over the last few years was never about cookies; it was about data privacy. The correlation between cookies and data privacy was that those surrogates for identity that enable companies to track individuals across sites and devices were terrible for privacy.
As I prepared this presentation, I reflected on how our industry has changed in the 16+ years I have been part of it. During that time, our industry went through multiple transformations. Today, it feels like we’re at the last stages of our industry's most recent transformation as we move from an industry built on third-party cookies to one built on data collaboration and collective responsibility.
Privacy-safe data collaboration maximizes the relevance and accuracy of advertising campaigns, leading to more meaningful consumer experiences. Data clean rooms have become foundational for companies that invest in privacy-enhancing technologies. Data clean rooms ensure that campaigns meet privacy standards and deliver impressive business results.
With the rising popularity of data clean rooms, we have seen many businesses jump on the bandwagon. As with any industry trend, success brings imitation—and not all imitations are created equal. Here are three warning labels you should always look for when adopting data collaboration technology:
Data Clean Room Warning 1: Beware of Privacy Washing
Privacy washing is becoming a prevalent issue in the industry, much like greenwashing in the environmental sector. Terms like "privacy-first," "privacy-safe," and "privacy-centric" are being thrown around far too easily, often with little substance behind them or requirements to back up these claims. Many companies promoting these privacy-centric solutions are built on outdated technology and practices that are far from privacy-first. They still rely on centralizing and commingling vast amounts of customer data—the antithesis of true privacy.
Rather than fundamentally addressing these shortcomings, some companies simply slap on a new label or acquire a piece of technology that supposedly makes them "privacy-first." However, privacy cannot be tacked onto an existing solution; it must be ingrained from the ground up.
Take InfoSum as an example. Our technology was built in Europe during the introduction of the GDPR, making privacy a core component of our platform from day one. Whether in Europe or the United States, the same privacy standards apply across the board, regardless of jurisdiction. The principle is simple: privacy is not an add-on. It must be built into the technology itself.
Privacy-enhancing technologies (PETs) should form the backbone of any collaboration platform. Best-in-class solutions will not employ a single PET but layer multiple into their solution. At InfoSum, we utilize basic hashing and encryption, differential privacy techniques and privacy-set intersection alongside our patented Bunkers, secure multi-party computation and synthetic ID generation.
A simple guiding principle. At the most basic level, data collaboration should ensure that data is never shared between parties. Data should never be shared, centralized and/or commingled. It’s an outdated practice with no place in a privacy-first future.
Data Clean Room Warning 2: Beware of the Lack of Neutrality
The second critical warning label in data collaboration is the lack of neutrality. With the rise of data clean rooms, we’ve seen a proliferation of "clean room-like" solutions. However, many of these options have a significant flaw: they are neither neutral nor independent, often tying your data and operations to a specific provider’s ecosystem.
For instance, when a data clean room is offered by an identity vendor, the solution is typically bound to that vendor’s proprietary identifier. This creates a limitation—you are restricted to collaborating only within that ecosystem, reducing flexibility and control. Similarly, cloud providers may offer clean rooms, but they require that your data reside within their storage environment. This can add unnecessary complexity and dependency on a single provider's infrastructure. Then, there are the walled garden clean rooms offered by media giants. These solutions restrict collaboration to their owned media channels, severely limiting the scope of what’s possible.
In all of these cases, your collaboration ability is constrained by the provider's technology and business interests. Worse, you are also tied to their privacy practices, which may not meet your standards or the evolving regulatory landscape. This lack of neutrality compromises the flexibility and independence essential for effective, privacy-first collaboration.
More importantly, these solutions often have ulterior motives that can conflict with their focus on preserving privacy. Consider this: Who would you rather trust to protect your data? A company that profits from how often it can resell that data or one whose business model relies on keeping your data secure? To ensure true privacy-safe collaboration, the solution must not only be neutral and independent but also free from any commercial interests that would jeopardize the integrity of your data.
Data Clean Room Warning 3: Beware of Complexity
Complexity is a major barrier to effective data collaboration. Many platforms are built with only data scientists in mind, requiring advanced coding skills and deep technical knowledge to operate. This leaves non-technical teams, like marketers and product managers, unable to fully participate in data-driven decisions, creating silos and slowing down collaboration.
To truly unlock the power of data collaboration, technology must be designed for all users—not just the experts. An ideal platform offers a user-friendly interface that allows business users to access insights and execute campaigns without needing extensive technical expertise. At the same time, it must also provide advanced tools for technical users, such as data scientists, who require deeper functionality.
When collaboration tools are unnecessarily complex, businesses face delays and inefficiencies. In today’s fast-paced digital world, agility is essential. Teams need quick access to insights to stay competitive, and when complexity slows this down, opportunities are lost. What’s more, if a solution profits from making processes more complicated—whether through prolonged execution times or reliance on managed services—it’s not the right solution for your business.
At InfoSum, we have focused on enabling collaboration as fast and efficient as possible. As recently as a few weeks ago, we broke our speed record. A client was signed, onboarded, trained and using the platform to execute multiple collaborations within 24 hours. No missed opportunities!
Moreover, our platform allows individuals to focus on what they do best to maximize value and reduce costs. We don't want a costly data scientist building queries and awaiting approval repeatedly. Instead, our solution empowers business users with the ability to execute both complex and simple data collaborations with little to no technical experience. This allows data scientists to focus on more strategic tasks while day-to-day operations are handled by those closer to the business and the client.
The future of data collaboration lies in making these tools accessible, allowing everyone in the business to unlock the potential of data and drive growth.
Key Takeaways
To summarize, these are the three critical takeaways when considering data collaboration technology:
- Privacy by default: The technology must incorporate multiple layers of privacy protection and security. Privacy isn’t something that can be added later—it has to be at the core of the technology from the start.
- Neutrality is essential: Your collaboration technology should be independent and free from reliance on third-party identifiers, storage, or media. It should offer a level playing field for all parties.
- Simplicity is key: Data collaboration should be easy to use for everyone within your organization. Look for solutions that balance a user-friendly interface with the advanced capabilities your technical teams need.
By adhering to these principles, businesses can unlock the full potential of privacy-first data collaboration, breaking down the barriers that have historically limited success. In doing so, they can focus on delivering high-performing advertising solutions that are not only effective but also respect consumer privacy in the new privacy-first era.
For a more in-depth exploration of these critical issues and practical advice on navigating the evolving landscape of data collaboration, watch my full presentation from DMEXCO. In it, I delve deeper into these warning labels and share actionable strategies to help your business succeed. Watch the full presentation here, and let’s continue building a future where privacy and innovation go hand in hand.
