Title :
A High-Dimensional Set Top Box Ad Targeting Algorithm Including Experimental Comparisons to Traditional TV Algorithms
Author :
Kitts, Brendan ; Dyng Au ; Burdick, Bill
Author_Institution :
PrecisionDemand, Seattle, WA, USA
Abstract :
We present a method for targeting ads on television that works on today´s TV systems. The method works by mining vast amounts of Set Top Box data, as well as advertiser customer data. From both sources the system builds demographic profiles, and then looks for media that have the highest match per dollar to the customer profile. The method was tested in four live television campaigns, comprising over 22,000 airings, and we present experimental results.
Keywords :
advertising; data mining; digital television; set-top boxes; TV algorithms; advertiser customer data mining; customer profile; demographic profiles; high-dimensional set-top box ad targeting algorithm; live television campaigns; set-top box data mining; Advertising; Educational institutions; Media; Sociology; Statistics; TV; Vectors; advertising; set top box; targeting; television;
Conference_Titel :
Data Mining (ICDM), 2013 IEEE 13th International Conference on
Conference_Location :
Dallas, TX
DOI :
10.1109/ICDM.2013.169
