Keeping customer data useful and private across clean rooms, media networks, and the cloud
By Kimberly Bloomston, SVP of product at LiveRamp, the leading data collaboration platform
Marketers are increasingly interested in leveraging the latest available technology. However, when using sophisticated tools that manage data in ever-expanding collaboration use cases, it’s crucial to prioritize privacy. Marketers should think about data and privacy in two ways: the privacy that drives consumer trust and the privacy that must be governed to mitigate business risk. By gaining a deeper understanding of how to approach privacy and the controls and partnerships that protect it, marketers can ensure there are proper safeguards in place to build enduring brand and business value that extends far beyond marketing.
Maintain Privacy Controls Wherever Data Lives
In today’s ecosystem, data collaboration is necessary for companies to personalize the customer experience, forge more strategic partnerships, and build brand and business value. Juxtaposed with this is the reality that most systems and privacy controls do not stay with the data when it moves in collaboration settings. It’s critical to have good data hygiene, which includes data minimization practices. This includes limiting the collection, storage, use or movement of data to only what is strictly necessary to achieve a specific purpose. These efforts are becoming increasingly important as more companies engage in media networks, clean rooms, or using data in the cloud.
Controls such as pseudonymization, which removes personally identifiable information (PII) to prohibit the re-identification of data, should be leveraged anytime consumer data is present. Based on the level of risk associated with each use case, data owners can then set different controls over how data is leveraged. These configurable controls are important to ensure third-parties, such as a retailer’s suppliers, or a media company’s numerous advertisers, only have access to the specific data sets that fulfill their purpose without exposure to other information.
An example of a configurable control is implementing an expiration on data sharing. This practice helps ensure that data is not used beyond the intended purpose. Complying with an expiration date, after which vendors must delete or return data to one party or another, means that data is not retained for longer than necessary, protecting the privacy and security of the data.
These best practices are also applicable for internal collaboration where parties don’t need visibility into entire data sets. For example, a brand’s data science team can identify customer profiles using one data point, while its marketing team can send an email marketing newsletter using another.
Setting configurable controls ensures that data shared is on a “need to know” basis and can be adjusted in whichever way best serves the use case at hand. This key unlocks the ability to safely collaborate with data wherever data lives.
Understand Privacy Isn’t One-Size-Fits-All
Clean rooms have arguably become the de facto privacy-focused approach to data collaboration and for good reason. These safe and neutral spaces allow partnerships to exist and analytics and measurement to occur without either party having access to the other’s PII. Yet, not all clean rooms are created equal. Some have more comprehensive approaches to privacy than others, and do not necessarily solve every collaboration need. In some instances, the level of security and controls in a clean room can actually be excessive for the needs of a company, say between internal IT and marketing teams, resulting in overly-restrictive controls that can hinder an average marketer use case.
While marketers certainly benefit from the variety of technical and procedural safeguards clean rooms use to ensure data is not misused, they’re not always the proper solution. To ensure adequate and appropriate protection, the level of control applied should be tailored to the level of risk associated with the type of data, access between collaborators, or application in which data is being used.
So while privacy protection in data collaboration is undoubtedly a priority, it must find a balance with utility in order to maximize the enterprise-wide value of data. Privacy is not a one-size-fits-all technology.
Strengthen Internal and External Partnerships to Drive Better Outcomes
With the introduction of new AI technologies and significant legislative changes dictating how, what, and where data can be used, it is crucial that stakeholders across companies are aligned and know how to respond. To maximize data utility without added privacy or security risk, marketing teams need to work with their tech counterparts for better overall collaboration. When CMOs and CIOs develop a shared understanding of the other’s data use cases they can maintain continuity in data protections.
There’s an opportunity for CMOs to become more educated on the cloud to accelerate data outcomes, in addition to becoming organizational thought leaders on privacy, security and data minimization overall. In return, CIOs should be encouraged to become more familiar with the marketing use cases possible in their data stack that support digital transformation so teams can become truly strategic partners. Only when the CMO and CIO work on data management together can a company truly de-risk its business.
The same rings true for partnerships outside of the business. Marketers should ask their technology partners how they are, or aren’t, thinking about these same things to determine if they are engaged in the most valuable relationships for their business. Getting smart with internal and external partners is a way to win.
As data collaboration becomes increasingly pivotal for business success, companies must stay aware of the nuances necessary to keep private data useful and useful data private. Evaluating on a use casebasis, understanding there is no one blanket privacy “solution,” and forging strategic partnerships within and outside the organization will help ensure marketers are equipped to navigate privacy implications and the controls necessary to protect businesses and their valued customers. By maximizing the value of data through responsible data collaboration, businesses will protect their brand, cultivate consumer trust, and deliver enterprise-wide value through innovation and growth.
