A New and Growing Topic: Security Tolerance

Clean rooms are designed to allow data sharing with maximum security. But different clean rooms are created with different levels of security — a financial services company needs a different clean room configuration than an auto organization. A host of factors should be considered in order for organizations to get the security that they need.

Every organization has what I call a “security tolerance,” the amount of data security they need to keep their data safe and fit with the culture and security protocols already in place.

Security tolerance can depend on factors including:

• Industry vertical: Finance and health care may have more sensitive data they don’t want tracked back to a customer’s PII, for example.
• Privacy culture: Executives, legal, security, each team has a level of privacy that adds up to the overall culture of the company. Some brands are worried only about outright data breaches; others want to control “creepy” targeting that could ensue if data leaked to the wrong hands.
• Data use and monetization: This includes loyalty data, subscriber lists, purchase data, and other information that is at varying levels of importance to the business itself. For instance, a publisher serving ads only to logged-in subscribers will want to protect their lists, which are a core asset. 
• Specificity and uniqueness: The more specific an insight is, the more valuable it is. For instance, lifetime value information about an expensive product needs to be much more secure compared to view metrics from a branding campaign.

These factors must be discussed with major stakeholders to gauge overall sentiment. It’s also important to talk in context, with specific use cases. It might be very important to use data insights that need to be kept very secure so that ad campaigns can be accurately targeted. Those requirements need to be surfaced and accounted for. 

Building The Dream Room

Security is one factor that goes into the ultimate design of a clean room. Organizations also need to consider cost and scale. Just like building a dream home, clean rooms can be big and complex, or relatively straightforward.

Some requirements are non-negotiable. PII data must be completely secure for legal reasons. But, beyond that level, there are many other nuances that can dramatically alter the construction of a clean room. For example, an organization might want to ensure that their partners don’t see their data, but they feel comfortable sending data to a clean room provider to encrypt it. Compare that to a different organization that doesn’t even want the clean room provider to see the data, and doesn’t want the data to ever leave their servers at all.

At this point, it’s time to start building a clean room blueprint. This is the best way for stakeholders to see different options, and how those options will affect cost, scale and speed. A blueprint can help brands start to prioritize what they need most — for example, the ability to keep working with key partners without losing scale or pull insights from highly secure data as securely as possible.

The move to first-party data promises to give organizations better control over their data, and a closer connection to their customers. To get the full value from their data, organizations will need to combine their insights with partner data and activate their data across a variety of channels. To do this well, companies can’t simply rely on clean room services from a few big providers, they need to have their own way of activating campaigns across their ecosystem and consolidating insights to enhance their user view, not segment it. Creating a clean room that best fits the brand's needs creates the surest path to success.