Are data clean rooms here to stay?
Myth vs. reality in martech’s newest buzzy acronym
Every year in adtech and martech, we need a new three-letter acronym to get excited about. Right now, that acronym appears to be DCR, short for data clean room (which actually rolls off the tongue easier for us than DCR).
Unlike some shiny new tools that fizzled out, there are many legitimate reasons to be excited about data clean rooms. Let’s start at the definition: Data clean rooms are secure collaborative environments in which multiple organizations can share and use their data in a privacy-safe way. Data clean rooms have the potential to solve several key problems and help companies operationalize their data assets in a way that has long been promised—but rarely achieved.
At this stage of adoption, however, clean rooms are more of a luxury good since their significant cost of entry puts them out of reach for everyone but the largest enterprises. As their use increases, however, their costs will decline, more standardized (read: cheaper) ways of deploying will emerge, more people will learn to successfully leverage them, and new innovations will democratize their use for smaller players.
We estimate that we are about 12 to 18 months away from mass adoption of data clean rooms. That’s impressive given that the technology is relatively new. The walled gardens began offering DCRs in 2017, when Google first introduced Ads Data Hub, followed by solutions from Amazon and Meta. Today, infrastructure providers such as Snowflake and Amazon Web Services also offer data clean rooms, in addition to stand-alone clean rooms from companies such as InfoSum, Habu, and Optable.
Driving the business case for data clean rooms are a mix of regulatory and technological restrictions and disruptions that will grow more acute in the coming years. If you’re not using a data clean room today, you may be at some point in the future.
Shiny new toy
Why the seemingly sudden focus on data clean rooms now? It’s driven by a mix of regulatory and technological developments.
Privacy regulation is a significant catalyst for privacy-preserving technologies like data clean rooms. The EU’s General Data Protection Regulation, which went into effect in 2018, ushered in a new era that required more secure environments to collaborate with potentially sensitive data sets, particularly first-party data sets. The law launched a new wave of privacy-by-design technologies. Early adopters, namely big marketing spenders, began the process of reconstituting their martech, data, and adtech stacks—from planning and activation to analysis—to be more privacy-centric.
At the same time, technological innovations in privacy-preserving solutions emerged in response to large platforms enacting privacy policies. Google, after several postponements, now plans to deprecate third-party cookies in Chrome in 2024. Apple launched App Tracking Transparency in 2021, which forces app developers to get consumer consent before they can use its ID for Advertising (IDFA) for marketing purposes.
The conventional wisdom is that the deprecation of third-party cookies would increase the value of any first-party data assets owned by a company. We’ve seen an explosion of technologies to help companies manage their first-party data, including cloud solutions and SaaS offerings that run on top of extremely large data sets. In response, marketing teams have become much more technologically savvy in recent years—another sign of progress in ensuring that marketing data can be used effectively for business benefit.
The brands, agencies, and publishers with the highest degrees of data maturity are the companies most likely to use data clean rooms today; they will also have significant prior technology investments and sizable teams. According to the IAB’s State of Data 2023 report, most data clean room users have spent at least $200,000 on the technology, and a quarter has spent at least $500,000. That doesn’t include other privacy-centric technologies that enable data clean rooms, which can push the annual price tag past the $2 million mark. Since cost and maturity are the most significant gating factors for data clean rooms, they are a premium, luxury solution for only the largest companies.
Unlocking critical capabilities
Data clean rooms provide several key innovations, including a privacy-preserving environment for handling and combining sensitive customer data sets and their ability to operationalize more effective measurement processes.
For marketers, clean rooms unlock three core areas that span planning, activation, and analysis:
1. Getting insights about your audience: Data clean rooms enable direct communications and collaboration between media owners and brands, allowing them to analyze data more granularly and gain business intelligence about customers and marketing performance.
2. Activating data in a privacy-compliant way: Marketers must reduce their reliance on deterministic identifiers such as third-party cookies and mobile ad IDs, which face increasing limitations and eventual deprecation.
3. Solving measurement challenges: Companies need to run analytics on massive data sets more easily and effectively, which is typically a very expensive data science-intensive endeavor. Data clean rooms can reduce the complexity of these data sets so that companies can more easily run advanced analyses.
With more adoption, new use cases will emerge, including attribution, ROI measurement, media mix modeling, and other forms of predictive analysis. If these all sound familiar, the core innovation here is in the proverbial plumbing: The business cases aren’t necessarily new but the intelligence layer sitting on top of the key data assets is.
DCRs and the marketing stack
Individual marketing stacks differ, so where a data clean room would reside depends entirely on the stack.
In general, there will be a data infrastructure layer at the bottom of the marketing stack. This is where the data lives in perhaps a data warehouse, data lake, or similar container. This layer will also include a company’s data governance, data strategy, and identity assets.
The data would flow to a decisioning engine or “trust” infrastructure layer, which is where the data clean room would be housed.
From the centralized “brain,” the data would flow to various activation layers on all sides, such as a customer data platform (CDP) and analytics. The activation layer would then feed back into the data infrastructure layer and flow through the entire stack again.
Some view this type of architecture, with its centralized decisioning engine, as ideal for the modern martech stack.
Data clean rooms’ biggest challenge
The data clean room landscape is nascent and highly fragmented, which creates its greatest hurdle: interoperability. In response, the IAB Tech Lab recently released the first draft of a clean room interoperability standard as part of a larger portfolio of data clean room specifications. . This is the first standard of its kind to lay the groundwork for how different data clean rooms can easily talk to each other.
This is important for brands and publishers that may need to push their data into more than one clean room. Doing so wouldn’t need to be such a huge undertaking for every integration, because the standard would provide a common language for these clean rooms to talk to each other. We expect that with the adoption of this type of standard, we'll see an even faster and easier path to adoption.
Do you need a clean room *in the next 18 to 24 months*?
We recommend that you don’t invest in a clean room until you have each of the following components:
• A team of at least six to 10 specialists with privacy expertise: If you don’t have a dedicated team, it’s less likely that you can take full advantage of data clean rooms. About half of all data clean room users have between six and 10 employees who are tasked with privacy-related technologies. Not only will you have to find and hire this talent with experience in privacy, data, and security, but you will need to retain them. If you don't have the talent in-house, you can still access data clean rooms through partnerships, an agency, or an outsourced team offering data clean rooms as a service.
• A sizable annual advertising budget for addressable ads: By sizable, we’re talking at least $100,000. Perhaps if you spend less than this, you can still play with data clean rooms but in a different way. You probably won’t be able to pull off a full clean room implementation, but perhaps working with an agency may be more feasible, or depending on your company, you could potentially share your data with a larger partner who can share costs and expertise.
• A comprehensive data strategy: Many companies talk a good game about the importance of data, but in our experience, very few companies have a bona fide data strategy in place, even though some may think they do. Some may have a data strategy tied to actionability around data or a specific channel, but they miss the larger picture of how to turn their data into an asset. That includes how they treat and value different types of data, and the ways in which they operationalize it to generate revenue.
• Other advanced technology deployed in your stack, such as a CDP or identity tools: Data clean rooms need a universe of other technologies to be used to their full potential. If your organization already has in place tools such as consent management platforms, CDPs, and identity solutions, you are likely already evaluating clean rooms.
Companies that have checked off all of these boxes will likely need a clean room within the next two years. If there’s an unchecked box, it is likely the data strategy that’s missing. This is a critical piece that should be in place before you consider adding any additional technologies. In its simplest form, it covers the data being collected, how frequently it is updated, and the quality and value of various sources. On the commercialization side, the strategy will organize all of that data, in terms of what is needed for planning, forecasting, activation, and other areas of business.
The bottom line
It’s important to remember that data clean rooms are not standalone technologies; they are an integral part of a privacy-by-design technology stack. Companies can’t just invest in a clean room and expect their martech stacks to magically be transformed; there's a significant level of investment required to make them place nicely within existing set-ups.
As we’ve mentioned several times, the costs and effort to deploy and maintain data clean rooms are significant. However, with more adoption and advancement, the costs will decline—and they are already rapidly falling. We expect that clean room providers will make them easier to test and use. There is an opportunity for specialist providers to create vertical clean rooms to serve less digitally advanced industries.
Depending on how a company plans to use a clean room, they may not have to cover the full cost themselves if they can find opportunities to share their data and take advantage of clean rooms in a more cost-effective way. A data clean room-as-a-service offering could be compelling from an agency or other provider for those who don’t have the staffing to properly leverage a clean room. We expect this space to evolve quickly and further blur the lines between DCRs as a separate product and DCR functionality as a necessary evolution of data storage and activation, so choose your timing wisely.
One question
Where would a data clean room fit into your martech, data, and adtech stack? Which use cases would make the most sense for your business?
Dig Deeper
State of Data 2023: Data Clean Rooms & the Democratization of Data in the Privacy-Centric Ecosystem
IAB TechLab’s Data Clean Room assets
On next year’s to do list: Clean rooms and better data
Why we care about data clean rooms
Ana guesting on the Marketecture podcast & discussing clean rooms
Thanks for reading,
Ana, Maja, and the Sparrow team
Enjoyed this piece? Share it, like it, and send us comments (you can reply to this email).
Who we are: Sparrow Advisers
We’re a results oriented management consultancy bringing deep operational expertise to solve strategic and tactical objectives of companies in and around the ad tech and mar tech space.
Our unique perspective rooted deeply in AdTech, MarTech, SaaS, media, entertainment, commerce, software, technology, and services allows us to accelerate your business from strategy to day-to-day execution.
Founded in 2015 by Ana and Maja Milicevic, principals & industry veterans who combined their product, strategy, sales, marketing, and company scaling chops and built the type of consultancy they wish existed when they were in operational roles at industry-leading adtech, martech, and software companies. Now a global team, Sparrow Advisers help solve the most pressing commercial challenges and connect all the necessary dots across people, process, and technology to simplify paths to revenue from strategic vision down to execution. We believe that expertise with fast-changing, emerging technologies at the crossroads of media, technology, creativity, innovation, and commerce are a differentiator and that every company should have access to wise Sherpas who’ve solved complex cross-sectional problems before. Contact us here.