Title :
Computational Television Advertising
Author :
Balakrishnan, S. ; Chopra, Sonik ; Applegate, Douglas ; Urbanek, S.
Author_Institution :
AT&T Labs. Res., Florham Park, NJ, USA
Abstract :
Ever wonder why that Kia Ad ran during Iron Chef? Traditional advertising methodology on television is a fascinating mix of marketing, branding, measurement, and predictive modeling. While still a robust business, it is at risk with the recent growth of online and time-shifted (recorded) television. A particular issue is that traditional methods for television advertising are far less efficient than their counterparts in the online world which employ highly sophisticated computational techniques. This paper formalizes an approach to eliminate some of these inefficiencies by recasting the process of television advertising media campaign generation in a computational framework. We describe efficient mathematical approaches to solve for the task of finding optimal campaigns for specific target audiences. In two case studies, our campaigns report gains in key operational metrics of up to 56% compared to campaigns generated by traditional methods.
Keywords :
advertising; mathematical analysis; television; Iron Chef; Kia ad; branding; computational techniques; computational television advertising; marketing; mathematical approaches; measurement; online television; operational metrics; predictive modeling; television advertising media campaign generation; time-shifted television; Advertising; Computational modeling; Measurement; Media; Optimization; Predictive models; TV; Computational Advertising; Media Campaign Generation; Optimization; Television Advertising;
Conference_Titel :
Data Mining (ICDM), 2012 IEEE 12th International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4673-4649-8
DOI :
10.1109/ICDM.2012.129