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In today's digital marketing landscape, data continues to become more valuable. But marketers are on edge: 76% of CMOs say the ability to comply with privacy regulations is a challenge, according to PwC’s latest Pulse Survey. In an inevitable, post-third-party, cookieless world where addressable inventory could shrink to just 10% of US web ad inventory from 56% today, businesses can no longer rely on third-party cookies for data-driven marketing.
In tandem, government regulations and consumer expectations on privacy have increased the need for consumer trust and governance controls. Plus, with the proliferation of MarTech and AdTech, data is now stored across many clouds and data gravity requires working with data where it resides.
Amid these challenges, marketers have a unique opportunity to deliver impactful consumer experiences by leveraging data as a competitive differentiator, while keeping privacy in mind.
You might be wondering, “Aren’t data clean rooms the solution?" Though these secure environments often help companies share and analyze data while remaining privacy-compliant, they’re only part of the solution. The real benefits come from rethinking data collaboration as a whole. You can bring together your siloed data and leverage data partnerships to gain a deeper understanding of the customer and reimagine their experience.
Why are organizations investing in data clean rooms?
As a key enabler for developing a data collaboration program, clean rooms can serve many purposes. And, as clean room solutions have matured to help meet market needs, they should be seen as a long-term, effective reality, not a passing trend. Here are some reasons organizations are investing in data clean rooms:
How do I choose which clean room to use?
Data clean rooms are not a one-size-fits-all solution. Different clean rooms suit different data collaboration needs and should be considered based on the use cases you are looking to drive. Currently, there are three main kinds of clean rooms available that can work together to support your data collaboration program:
- Advertiser walled garden. Clean rooms play an essential role in media measurement and activation. Large advertising networks, such as Google (ADH), Amazon (AMC), Meta (Meta Advanced Analytics), have developed their own clean room solutions powered by their proprietary data for more advanced insights and targeting. However, these use cases would be limited to each respective walled garden.
- X-media network clean room. Like the walled gardens, media networks or large publishers provide their advertisers with measurement and targeting offerings. Unlike walled gardens, these players have opted to leverage existing clean room technology vendors to enable their offerings. Traditionally, the key value proposition was the ability of media networks to provide closed-loop attribution, but as media networks have expanded outside of retailers, the value has proliferated into other use cases such as reach, frequency, suppression management, audience development and targeting.
- Interoperable standalone clean room. Unlike the other two clean room types, this clean room approach involves advertisers directly licensing a clean room themselves. The clean room is indirectly used as a paid service. When directly licensing a clean room, advertisers can select an interoperable, easy-to-use and flexible clean room vendor that enables the advertiser to better target, measure and enhance media across activation channels.
So, what’s next?
To do data collaboration well, you need to make sure it pays off. Many organizations stumble on the way to data collaboration because they often don't plan well. As you start your journey, consider the following preparation checklist:
- Define your data collaboration program. Whether you are looking to start your own media network as a ‘Data Owner’ or looking to use partner data, by first identifying your data collaboration use cases, you can determine whether you need your own clean room or if you can use a partner’s.
- Size the opportunity. Moving forward with a clean room can be pivotal; however, it can demand considerable investment in cross-functional resource time. Forecast the size of the prize to understand whether it's a worthwhile investment and whether it will be a sustainable business function.
- Determine your value proposition to the market. If you are unable to stand out from existing market offerings, it's likely your program will be unsustainable at driving demand. Make sure that you understand the uniqueness of your data attributes, attainable share of market, traffic and reliability of your customer data.
- Gain CISO buy-in. Creating a data collaboration is not an easy feat. Your organization will often need to make challenging decisions on data sharing and movement. Each choice will likely require partnership with your information security counterparts. Making sure they are involved from the start can help prevent any showstoppers.
Executive perspectives on data collaboration
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