What is a data clean room: Definition, benefits, use cases
A data clean room is a software environment where multiple parties can securely share data. Learn the benefits, challenges, and get examples.
Today’s consumers crave personalized experiences. Regardless of the brand, shoppers expect to be known and understood, and they demand heightened, digitally enhanced experiences at every touchpoint.
This is a tall order for marketers facing cookie deprecation, walled gardens, and stricter privacy regulations. The pressure is coming from governments across the world and some states within the US, but it’s also stemming from wary consumers whose distrust in sharing data seems to grow daily.
As a result, consumers have created a catch-22 for their beloved brands. Consumers demand personalization, but aren’t willing to share their personal data to inform and enable these individualized, omnichannel experiences.
Anonymous first-party data offers marketing teams the opportunity to gather essential data generated by anonymous signals from their company’s website traffic while adhering to consumers’ privacy demands.
However, many brands are overlooking these anonymous data sets that have no personal identifiers — when in reality, they should value them as much as their first-party data.
Marketing in the age of data privacy
Marketers are unsure what data they can get while adhering to consumer demand for privacy. For example, onsite tags and martech stacks vary with the data that can be seen and tracked.
Marketers also are unsure what data they can use without running afoul of privacy legislation. Current regulations don’t fully explore the differences between known and unknown, particularly the unknown data from users that haven’t self-identified, or data from known users that haven’t signed in again.
As a result, companies struggle to adjust data management process and marketing strategies for evolving legislations.
What’s more, companies are threatened by ‘’unsubscribe/opt-out” requests and how that applies to unknown data. After all, how do you unsubscribe someone if you don’t know them?
Enterprises are unsure and unwilling to handle anonymous data such that it remains in compliance with laws.
Fear no more: Anonymous first-party data
As if that’s not complicated enough, anonymous data requires a separate data structure with strong controls, and the payoff for anonymous personalization is arguably less than lower funnel efforts using first-, second-, or third-party data from known users.
Changes and testing done further down the funnel where there’s more data to use and conversions to track is much easier. Marketers are missing the value of tracking unknown to known and then using unknown portion of the journey with similar unknown cohorts.
Most marketers want to ensure they distinguish users as granularly as possible without “fingerprinting” them. And while it’s widely known that anonymous signals shouldn’t used to identify personally identifiable information (PII), marketers are uncertain how and what to track without doing so.
That said, using these signals to differentiate traffic and create similar cohorts to personalize experiences is acceptable. For example, marketing teams may learn language and geographic information that allows for site customization and sharing relevant products like mittens in colder climates by utilizing anonymous signals.
And even more importantly, marketers can — and should — combine signal data with onsite behaviors for further insights.
How to use anonymous first-party data
So how can marketing leaders establish tactics that will help their teams make better use of anonymous web traffic data?
First, having a transparent privacy policy is key. You have to say what you do, do what you say. Privacy policies must be clear and explicit in describing their use of these tags and cookies.
The more details shared, and the resulting benefit from what you’re doing increases the chances of consumer opt-ins.
Another essential, basic step in improving anonymous first-party data management and utilization is deploying an intelligent, domain-specific, true first-party tagging solution that can both read a user’s signals and provide cookies for future sessions. There are several companies that offer these tagging capabilities and can help track unknown users within the appropriate legal parameters.
As we move away from third-party cookies and data sharing among partners, companies must look within to track, gather, and analyze anonymous first-party data to help inform decisions.
The time is NOW
We’re already witnessing a new era of heightened privacy policies and consumer distrust. Data is becoming increasingly scarce and more difficult to manage.
Marketing leaders have overlooked anonymous first-party data for too long. If they continue to underutilize it, their companies will soon pay the price.
