Scheduling Advertising on Cable Television

Sebastián Souyris (), Sridhar Seshadri () and Sriram Subramanian ()
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Sebastián Souyris: Lally School of Management, Rensselaer Polytechnic Institute, Troy, New York 12180
Sridhar Seshadri: Gies College of Business, University of Illinois, Urbana-Champaign, Illinois 61820
Sriram Subramanian: Pinterest, New York, New York 10018

Operations Research, 2023, vol. 71, issue 6, 2217-2231

Abstract: Advertisement scheduling is a daily essential operational process in the television business. Efficient distribution of viewers among advertisers allows the television network to satisfy contracts and increase ad sale revenues. Ad scheduling is a challenging multiperiod, mixed-integer programming problem in which the network must create schedules to meet advertisers’ campaign goals and maximize ad revenues. Each campaign must meet a specific target group of viewers and a unique set of constraints. Moreover, the number of viewers is uncertain. To solve this problem, we develop and implement a practical approach that combines mathematical programming and machine learning to create daily schedules. These schedules are of high quality according to standard business metrics and the small integer programming gap. Leading networks in the United States and India using our methods experience a 3%–5% revenue increase.

Keywords: OR Practice; scheduling; revenue management; analytics; machine learning; advertising; television–business (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:71:y:2023:i:6:p:2217-2231

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