With The Right Standards In Place, Data Clean Rooms Could Be The Best New Thing For Marketers

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by David Smith, senior director of business development and partnerships at Neustar.

Shortly before the General Data Protection Regulation went into effect in May, Google announced plans to sunset a service that shared with marketers certain user-level information about ad performance on DoubleClick and YouTube. As an alternative, the company steered advertisers toward its Ads Data Hub data-sharing product instead.

It was a watershed moment. Ads Data Hub is just one example of a growing class of controlled data pathways known as clean rooms, which help brands and providers of unique data, such as media platforms and transaction processors, balance data-sharing needs with data-oversight responsibilities.

As data governance takes center stage, these clean rooms are proliferating, along with growing buzz about their advantages.

The problem is that the industry has yet to align standards around data clean rooms. Without clear, quick and impartial industrywide guidelines in place, all their very real promise could spin into an array of unintended – and potentially undesirable – consequences.

Defining data clean rooms

Named for the hermetically sealed areas where microchips and other sensitive materials get made, data clean rooms allow inventory partners to share customer information with brands, while still maintaining strict controls in place.

I define data clean rooms as a shared environment, secured from external access, between two or more companies where each company determines the degree of visibility to their data.

The opportunity provided by data clean rooms is tremendous: They create a safe passage through which data providers – and especially the otherwise elusive walled gardens – can more easily share the marketing performance data that brands crave.

The devil is in the details

Alongside the opportunity, data clean rooms also create new uncertainty. That’s because, as uncharted territory, many crucial issues still need to be worked out.

1. Squaring sample sizes

Brands track customer journeys at the individual customer level, through such identifiers as browser cookies, mobile IDs and email addresses. Clean rooms may aggregate these identifiers into larger groups of 50, or even 1,000. But how will brands compare their granular data with the aggregate numbers – and compare aggregate numbers with each other?

2. Aligning on customer identity

Brands and data providers might identify customers in subtly different but important ways, such as looking at different segments of the customer journey or using different approaches to resolve the many identifiers back to the same person. As a result, there’s no guarantee that everyone is looking at the same view of the customer – or even at the same customer at all.

3. Who owns clean room data?

There are various ways to structure the management of a data clean room, including independent oversight and full ownership by the data provider. In each situation, data ownership questions inevitably arise.

Who owns the data within the clean room and what rights do other parties have, if any, to that data?

How can the data be shared across parties and with whom?

What kinds of data – and at what level of granularity – can the brands remove from the clean room, and what needs to stay?

What rights do data providers have, if any, over brands’ models developed within clean rooms?

What kinds of data will providers allow brands to include? For instance, will data owners prevent their data flowing into an environment owned by a competitor?

Managed correctly, clean rooms could become the pre-eminent tool for brands to better understand the place of walled-garden marketing within the broader marketing ecosystem. But without the right standards and methods to work across them, clean rooms stand to become yet another hurdle to data interoperability and control. And in today’s high-stakes, post-GDPR “new world order” of data governance, the costs of unintended data-sharing consequences are only rising.

These are issues we should address now, as clean rooms are just beginning to gain traction. The advertising industry needs to collaborate with a trusted, neutral third-party authority, such as the IAB, to work with media companies, brands, data partners and clean room users for better-defined clean room standards that ensure the effective and transparent management of data across all clean rooms, while also keeping consumer data, and the business of data, secure.

Follow Neustar (@Neustar) and AdExchanger (@adexchanger) on Twitter.

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1 Comment

  1. Agreed, David. As consumer and government demand for data privacy gains traction, the risks around data privacy breaches grow in lockstep. Meanwhile the major user graphs (Google, Facebook, etc) are going to want to protect said user graphs for financial reasons as well.

    Advertisers may currently feel a bit peeved at Google for redacting user-level data, but as those advertisers activate more of their own customer data, they’re likewise going to want to keep both their customers’ privacy and their hard-won financial assets (i.e., their customer data) well protected, so this will end up being a two-way street. Everyone’s going to come to expect and appreciate some kind of user data “escrow” environment that allows business to proceed without any party taking on excess risk or giving up excess value.

    Ads Data Hub-esque solutions may create some challenges in the short term as everyone readjusts targeting and measurement to function without row-level access to user data, but over the long term, these “clean rooms” are going to solve way more problems than they create.