There's a point in the development of successful technology when it reaches maturity, gets widely embraced—and becomes invisible to end users.
We don't need to understand radio waves to use our phones, or the technology behind LCD or OLED to watch a favorite show on TV. Today, most companies use cloud computing without being experts in the technology thanks to AWS, Azure and others. Tech becomes our next nature, to use futurist Koert Van Mensvoort's terminology.
Are we there yet with data clean rooms?
There's no question that data clean rooms, and data collaboration in general, are quickly becoming a must-have for marketers faced with signal loss and what Jules Polonetsky, CEO of the Future of Privacy Forum, recently called a firehose of privacy regulations around the world. In its 2023 State of Data survey, the IAB reports that 64% of decision-makers engaged with privacy-preserving tech across brands, media owners and agencies are currently using data clean rooms, and another 21% are considering adding one soon to their martech quiver. That doesn't leave too many on the fence.
But for most vendors, setting up a data clean room remains a “lengthy and complex process,” the IAB points out. "Data clean rooms are not turnkey technology, and they require significant investments in talent, cost, and setup, including data infrastructure, connectivity as well as onboarding." At InfoSum, we built our data clean room technology to be nimble and easy to stand up, but most other solutions in the market today require a heavy lift, and nearly 40% of data clean room users end up running into serious data interoperability and internal resource issues.
There’s hope though.
Some of today’s most progressive media companies in CTV, retail media and gaming have recognized the need to shelter their clients from all the complexity and embed the full functionality of a data clean room inside their own first-party data solutions. In integrating a highly-flexible and interoperable data clean room like InfoSum’s with their existing tech—and ‘productizing’ its features to meet their clients’ specific requirements—these media companies are lowering the barrier of entry for their advertising partners and allowing them to shift their focus from the mechanics involved in operating a clean room to actually creating value from their business.
Let’s review a couple of early examples.
Channel 4 and ITV lead the charge
Back in 2020, Channel 4 launched BRANDM4TCH, a media planning and buying system where the company’s advertising clients could “bring their own data,” find the overlap with Channel 4’s 27 million registered on-demand viewers in the UK and “speak directly to their customers on the Channel 4 platform in a way that is personal and GDPR compliant.” An InfoSum data clean room and Mediarithmics CDP worked behind the scenes to safeguard all customer data and streamline the activation process.
The solution was quick to impress when it was first released, with brands across verticals showing substantial lifts in key metrics like spontaneous awareness (+42%) and first-choice consideration (+121%) compared to demographic targeting. The benefits extend further down the funnel too, with a recent campaign by Deliveroo improving app sign-ups by 20%. Channel 4 has now expanded its data clean room-based product suite to provide easy-to-use audience building, attribution and retail media solutions in partnership with Sainsbury’s Nectar360 loyalty programme.
Speaking of retail media collaborations, ITV has recently launched two data clean room-based product, Matchmaker, to match its 37 million registered viewers to shopper data from Boots’ Advantage Card and Tesco’s Clubcard, with 17 million and 20 million members respectively.
The objective for ITV isn’t to come up with a massive overlapped audience that could be targeted as a whole, but rather to create dozens of smaller and richer audience segments for CPG advertisers that don’t have access to large pools of first-party data of their own. Matchmaker gives those advertisers the ability not only to target responsive audiences on ITV but also measure conversions at the point of sale. The prospect of closed-loop measurement is clearly striking a chord with the brands involved in early trials (Heineken, Magnum, Walkers, Sure and John Frieda among them), and in the words of Jayesh Rajdev, Controller of Advanced Advertising for ITV, the company is already “full steam ahead on customer roll-out and development roadmap.”
The idea of productizing a data clean room to emphasize specific use cases and make its features more accessible to a wider market is not just coming to life in the UK. Market leaders like Samsung Ads, Disney, Experian, and Fandom are all engaged in developing advanced data clean room-based solutions in the US, as is News Corp in Australia and Axel Springer All Media in Germany.
Most of those developments revolve around four fundamental use cases.
Four highly-successful data clean room use cases for data-driven advertising solutions
At the 2023 ANA Financial Management Conference recently, ANA CEO Bob Liodice stated, "Data Clean Rooms are an essential collaboration tool for audience insights, measurement and data activation in a privacy-centric ecosystem". At InfoSum, we couldn’t agree more, now let’s explore those use cases in more detail.
The first and most obvious use case has to do with matching a brand’s first-party customer data to a media company’s first-party viewer or user data, and making it possible for the brand to ‘target the overlap’ with personalized ads and promotions. This is a crucial application for data-driven performance marketers, but one that was rife with privacy complications when the match was done with cookies and data shared without any safeguards. An advanced data clean room can sequester each party’s data in a dedicated bunker, with tight access permissions and, most importantly, perform the match without moving any of the data around.
New customer conquesting
Another important use case is the acquisition of new customers, and a data clean room-based solution can help accomplish this by identifying consumers in the media company’s dataset who aren’t yet in the advertiser’s dataset. This is sometimes referred to as ‘audience suppression.’ The fact that those consumers aren’t yet customers of the brand doesn’t automatically make them good candidates, of course, and brands ought to further refine their target audiences before launching a new customer acquisition campaign, but by narrowing down the initial pool to non-customers, they aren’t wasting money on—and sending awkward nice-to-meet-you messages to—existing customers.
A key technique to boost chances that a new customer will be receptive to the brand’s appeal is lookalike modeling, or any other type of classification or machine learning process that can take characteristics from existing customers (demographics, interests, media usage, purchase history) and predict like-behavior among new prospects. This is a crucial application for FMCG companies and smaller brands that need to be able to use a small set of first-party data as a seed and work with a media owner or other party like Mediarithmics or Experian to maximize addressable scale and accuracy. A platform based on data clean room technology gives them a way to accomplish those steps without having to worry about data security and privacy compliance.
Using a robust data clean room-based platform, a media company can query a brand’s or a data partner’s first-party data to segment its own users based on common interests and behavior profiles. Those cohorts can then be measured for their responsiveness to various types of products and campaigns and monetized as syndicated audiences. This closed-loop capability sits at the heart of Channel 4’s partnership with Sainsbury’s and ITV’s partnerships with Boots and Tesco in the UK, and it’s the main reason why CTV and retail media networks have become such natural partners recently.
It’s time to democratize the data clean room
Every day, more brands, agencies, media owners and data providers are engaging with data clean rooms and growing more confident in their capabilities. They’re not invisible yet, but it’s really encouraging to see them get embedded into a new wave of advanced media planning and buying tools.
At InfoSum, we want data clean rooms to become second nature for marketers, not just for analysts with a degree in data science. The marketing industry needs to evolve towards a more privacy-centric ecosystem, and democratizing clean rooms is a crucial step in that direction. That's why we work hard to make our own data clean room as flexible and easy to productize as possible. Please get in touch with us, and we’ll show you how fast you can stand up your own breakthrough data-driven solution on top of our industry-leading technology.