Behind the clean room is ‘Disney Select’, a collection of Disney’s first-party data and advanced modeling capabilities in one place. It is built on the Disney Ad Sales Audience Graph, which is designed to map IDs that are available and relevant to specific households across Disney platforms, and connect properties and engagements across all Disney endpoints. .
Disney said it took an embedded approach to data science to succeed in this space.
With Disney Select, marketers Gambia Email List can choose the audience they want from a library of more than 1,000 first-party behavioral and psychographic segments, McGraw said. “We use more than 100,000 attributes to provide this audience segment information. Because it leverages advanced machine learning, you can do a lot of modeling whether you’re stepping out of the information seed or not adding third-party data,” he said.
For example, even if Disney doesn’t have a lot of data on car purchases, McGraw explains, adding the car marketer’s data to the clean room’s Disney data can create a more tailored model. “We’re also thinking about the desired outcome in each category and then doing the modeling to create segments around the desired outcome,” he added.
Embedding data science is key
For a data scientist to thrive in an advertising sales organization, McGraw advises, you need to find talent and your team members must have a variety of backgrounds and CH Leads skills. He added that it is not enough to select and hire only those with high quantitative specifications. “For example, you want someone with a background in marketing to sit right next to someone with a background in technology,” he says. “That way you get to know each other and exchange ideas and workflows. This allows us to collaborate closely, exchanging ideas and skills, whether it be data science, advanced analytics, data solutions and enablers,” said McGraw.