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A Deep Dive Into Disney's Data Cleanroom, Measurement Feature

Disney’s Clean Room -- announced in October 2021 and powered by Disney Select -- has begun the next phase of its project focused on measurement. Horizon Media became the first to test this expansion.  

"Essentially what happens is a client will have data in their own Clean Room environment through a provider like Snowflake," said Danielle Brown, senior vice president of data enablement and category strategy at Disney Advertising. “We use our own proprietary audience graph in our environment where we can connect audiences and see where there's overlap and leverage the Clean Room for audience discoverability.

Marketers now have the ability to test measurement capabilities and audience activation through Disney Advertising’s Clean Room with support from data providers Habu, InfoSum, and Snowflake. 

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The introduction of the cleanroom last year with launch partner Omnicom Group provides insight into audience segments. 

“Since the launch of our clean room work with Disney, we’ve been able to streamline audience activation and establish a privacy safe framework for audience insights for our mutual clients,” said Kelly Metz, managing director of Advanced TV and Linear Activation at Omnicom Media Group “We really expect to see this level of secure data partnership deliver not only reliable activation insights at scale, but also set new standards for our industry on incrementality insights so we can understand the true impact of Disney media on our client’s business objectives.”      

How does it work? A client’s data sits in what Brown called a “storage unit” -- a way for advertisers to leverage their audience insights and discover where more of their target audience lies within a secure environment

Disney has developed a proprietary solution, using Snowflake’s media data cloud and Habu’s UI software-as-a-serviceto enable advertisers’ audience data to be matched, leveraging Disney’s powerful and expansive proprietary audience graph. It leverages Snowflake’s media data cloud to enable this type of data connectivity piece.

Advertisers can connect first-party data to an increased number of data sources to gain more actionable consumer insights, while being able to address and adapt to a changing data and privacy landscape.

Brown and her team works with the Disney Data Science team to design specific features for categories.

There are nearly 2,000 audience segments in Disney Select, built from proprietary first-part data. The segments are designed to meet the needs of every brand, with specific segments available for each category, such a  telco and tech, CPG, auto and more. 

The clean room enables advertisers to see what content their key consumers are interested in. This way, brands can know if they’re over indexing with audiences in one place, or under indexing in others, informing how to build their media mix with Disney. 

Disney’s proprietary audience graph is built off of hundreds of millions of identifiers and hundreds of thousands of attributes across the company's portfolio of products and sites. Brown said the company began to build the audiences from scratch six or seven years ago. It also expanded access to other audience insights as Disney acquired companies. 

Brown said Disney has established multiple audience segments surrounding fandom of sports and specific teams based on ESPN's expansive reach.

In addition to the behavioral and psychographic information gleaned across its products, Disney supplements the dataset by leveraging survey data to seed information for modeling.

Some of those questions might include whether someone is a fan of a certain product, or a tech enthusiast, or is planning to buy a car in six to 12 months? The insights from the surveys provide the means to create look-a-like model audiences.

There are dozens of brands using Disney’s clean room to inform pre-planning decisions through audience exploration. Still, Disney is expanding to offer measurement capabilities within the clean room environment. 

“We have a team that oversees auto, tech, and telco, among others, so we’re connecting industry behaviors and trends to these categories,” Brown said. “We bring the information to the data science team to build additional audience segments.”

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