Document Type
Article
Publication Date
8-25-2016
Abstract
Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of "impressions" in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue.
Recommended Citation
M.J. Panaggio; P.W. Fok; G.S. Bhatt; S. Burhoe; M. Capps; C.J. Edholm; F. El Moustaid; T. Emerson; S.L. Estock; N. Gold; R. Halabi; M. Houser; P.R. Kramer; H.W. Lee; Q. Li; W. Li; D. Lu; Y. Qian; L.F. Rossi; D. Shutt; V.C. Yang; Y. Zhou "Prediction and Optimal Scheduling of Advertisements in Linear Television", 2016, 1608.07305