• DocumentCode
    3164434
  • 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
  • fYear
    2013
  • fDate
    7-10 Dec. 2013
  • Firstpage
    370
  • Lastpage
    378
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining (ICDM), 2013 IEEE 13th International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1550-4786
  • Type

    conf

  • DOI
    10.1109/ICDM.2013.169
  • Filename
    6729521