Distilling the Data Clean Room with MightyHive

In today’s landscape where personalization and relevance are critical, marketers are increasingly asked to understand both the creative and technical sides of the equation when it comes to delivering digital experiences to customers. S4Capital, a new-era model offering end-to-end advertising services to brands and organizations around the world, bridges that gap: “Data is at the center of what we do,” Sir Martin Sorrell, Founder and Executive Chairman of S4Capital, told IBC365 in a recent interview. “People that claim data destroys creativity or hinders it are talking nonsense. Good data and good insights inform creativity and makes it more effective.”

Achieving this requires close collaboration between MediaMonks, whose forte lies in creativity and enabling efficient production at scale, and MightyHive, who provides consulting and services in the areas of media operations and training, data strategy, and analytics. Emily Del Greco, President of the Americas at MightyHive, puts it succinctly: “MediaMonks is about taking the risk, and MightyHive comes quickly with feedback [backed by data.]”

We sat down with Myles Younger, Senior Director of Marketing at MightyHive, to discuss one of the biggest challenges that brands face when it comes to measuring performance and developing insights-driven content: privacy. From GDPR to the new California Consumer Privacy Act, privacy is going to become more challenging through 2020. For brands that struggle to look beyond the walled gardens of partner and platform data to gain a fuller view of their customers, Younger offers some advice: consider investing in a data clean room, which enables partners to develop new insights without compromising their audiences’ privacy. Younger walks us through what data clean rooms are, what you might consider before setting one up and more.

How would you explain data clean rooms?

Myles Younger: My analogy for how I would explain it is: imagine you have two data owners, ColorCo and FoodCo. ColorCo has data on its audience, including everyone’s favorite color. FoodCo has a similar audience to ColorCo, and knows their favorite food. ColorCo would like to know what the overlap is between their audiences, maybe identifying what the most popular combinations are in favorite color versus food—but neither wants to reveal to the other any personally identifiable information that could compromise the value of their data or the privacy of their audience.

A data clean room allows them to bring their data together in a neutral environment to figure out where the overlap is, meaning they might find that 300 people in their audience favor yellow and hotdogs—but neither ColorCo nor FoodCo know who those 300 people are, they just get the overlaps. That’s the special thing: you build new insights while protecting individual privacy.

Speaking of privacy, that’s a major concern for brands and their audiences. How do data clean rooms ensure brands still get a high quality of insights?

MY: Traditional methods of understanding the user are beginning to erode and brands are embracing first-party data that gives them a truer sense of who their audience is and what they need. What’s important to remember about data clean rooms is that they offer you access to insights gained from the first-party data of others.

As cookie-driven campaign measurement continues to become less reliable, brands are going to have to start looking elsewhere for insights on creative performance, reach and frequency, and attribution. Because data clean rooms generate insights from first-party data, they should be towards the top of every marketer’s list to at least become familiar with, if not start tinkering with.

At MediaMonks, we often discuss with clients the importance of delivering a total brand experience, applying insights and user data across a customer decision journey that extends beyond a single platform. Could data clean rooms aid in this process?

MY: Absolutely! Data clean rooms could aid in delivering the total brand experience in more meaningful ways than we’ve ever seen before. I know that sounds hyperbolic, but it’s justified.

Up until now, digital ad targeting, personalization, measurement and optimization have been based on what you might call the “total cookie experience.” Cookies and ad tech tracking IDs form a big universe, but it’s an isolated place. Even before things like GDPR and Safari ITP, it was very difficult to connect millions of ephemeral (and often fraudulent) browser cookies and third-party tracking IDs back to genuine business data (customers, products, transactions, loyalty and preference data, stores, apps, strategic partner data, etc). Given that clean rooms run on first-party databases and not cookies, brands gain the opportunity to tap into the totality of CX data sets when making analyses or optimizations. For marketers who have been used to making fuzzy inferences from nebulous, siloed cookie pools, I think working from actual business data is going to seem like a revelation.

What else would excite brands about data clean rooms?

MY: Data clean rooms are a big win for measuring performance and ROI. Let’s say you’re a CPG brand, meaning you’re likely selling your product through distributors and retailers. Traditionally, you might have to wait months for reportage on transaction data. But we have a CPG client who uses data clean rooms to interrogate or query a retailer’s POS data in almost real time.

Given the rapid access to insights that data clean rooms offer, what are some other ways that working with one would change my day-to-day as a marketer or strategist?

MY: There really is a promise for far more rapid access to data. Previously, many marketers’ approaches were cookie-driven, which adds latency and degrades fidelity of the data. Data clean rooms let you act on a more instantaneous basis.

And while data clean rooms inhibit ownership or direct access to others’ data, it really can bring you closer to it. That might sound counter-intuitive, but data clean rooms prompt you to shift your perspective a bit. We always ask our clients: what do you want, the data or the insights? You probably want the latter, and while data clean rooms might keep you an arm’s length from the data itself, they bring you closer to the insights.

How easy is it to partner with another brand or company to join data in a clean room? Do you think data clean rooms will usher in greater collaboration as brands discover overlaps between their audiences?

MY: This is clearly an area for early adopters right now, but MightyHive is seeing early success and we’re onboarding advertisers into clean rooms left and right. The momentum is clearly there.

A smart place to start with respect to inter-brand collaboration is with existing strategic brand partnerships. For example: whenever consumers travel, they’re inundated with sophisticated partner marketing programs across airlines, booking sites, hotels, loyalty programs and credit cards. These brand and audience partnerships already exist, and clean rooms are probably going to come into play more and more as a means to share audiences, CX touchpoints, measurement data and insights.

Get your hands dirty with data clean rooms.