Traditional Or Digital, TV Networks Crave Just One Thing – Forbes
There were two big stories in the TV industry last week and they both revolved around data.
Disney announced that it would be launching standalone OTT apps for ESPN and for the Disney Channel, and Facebook announced the rollout of its long-awaited Watch feature, which will (initially) feature professionally produced short-form videos from well-known brands such as NASA, the NBA and National Geographic.
Both companies launched their products with one key goal in mind: to gather the sort of data that gives them a better understanding of their viewers and their viewing habits, which will in turn allow them to produce better programming, run more highly targeted advertising and more effectively promote their own original programming.
Disney Magic Begins With Data
Disney in particular had very little data about their viewers beyond Nielsen ratings, which offer very limited information (age and gender) around who is watching. And while Nielsen can go deeper with certain households, what they provide is still a representation of Disneyâs viewership. Disney wants something much deeperâthey want census level data.
With a standalone subscription app, Disney gets access to six important pieces of data about their viewers: their names, their credit card numbers, their email addresses, their IP addresses, their street addresses and their phone numbers.
They can then combine that data with data from third party providers like Experian to begin targeting their audiences. So that if, say, they notice that someone is tuning in to the ESPN app to watch Dodgers games, they can email them an offer for a Dodgers cap from the ESPN store. Similarly, they can run that same Dodgers cap offer as an ad that shows up on any mobile devices or PCs using the same IP address.
They can run addressable advertising, too, showing different ads to different people watching the same show based on demographics and location. And they can monitor their shows to see which segments and storylines result in the biggest viewership peaks and valleys, and adjust their programming decisions accordingly. (Itâs always dangerous to base programming decisions on data, but if say, a new segment of a late night talk show proves very popular, making it a more regular feature is an easy win.)