Leveraging Big Data for more efficient TV advertising

By February 15, 2013
planète made of TV screens with data patterns around it

Targeting and analytics service from Simulmedia gives advertisers and agencies more accuracy in reaching viewers, by leveraging Big Data and applying "web-like advertising techniques" to television.


TV viewers are watching more than ever - 34 hours per week, but the way they watch TV is changing. To better optimize advertising across multiple channels and lower ratings, Simulmedia’s ad targeting and analytics service leverages Big Data. Their targeting strategy applies Internet-style data analysis to traditional TV, recommending show campaigns to marketers and agencies. Combining data from set-top boxes, as well as data from Nielsen, MRI, the US Census and other sources, Simulmedia targets ads according to demographic relevance without storing personal information. The data is processed through algorithms to predict which viewers will watch what, and they monitor how effective these campaigns are by measuring the engagement of targeted viewers.

Changing viewership patterns makes targeting even more important for marketers

As audience fragmentation has occurred, it has become indispensable for advertisers to find where they can most effectively reach their target viewers, so metrics must be more exhaustive. Big Data can crunch together datasets to better reveal what the viewers that they want to reach are watching. The data comes from several viewing sources, including cable, satellite, telco and TiVo boxes, which is licensed anonymously through the TV system operators. Currently, Simulmedia captures data from over 100 million viewing events and sees 500,000 national TV ads per week. While they launched with TV promotional advertisers, they have since expanded to work with travel, financial services, telco and entertainment industry advertisers.

Big Data can provide marketers with high-value viewers in unexpected places

Simulmedia’s targeting can apply to different capabilities, such as demographics like age and gender, plus several other targeting types, such as MRI - shopping behavior and household income, Tune-in Behavior - past viewing of programs, networks or timeslots and Ad Viewing Behavior - “exposure to complementary or competitive ad schedules.” This targeting can result in less cost within ad campaigns and more thorough coverage of a certain audience. As a client remarked about identifying underserved audience pockets with Simulmedia, “It wasn’t about getting a specific demographic... It was about finding viewers predisposed to watching a police drama.”

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