• DocumentCode
    265174
  • Title

    Paid Search: Modeling Rank Dependent Behavior

  • Author

    Anderson, Chris K. ; Ming Cheng

  • Author_Institution
    Sch. of Hotel Adm., Cornell Univ., Ithaca, NY, USA
  • fYear
    2014
  • fDate
    6-9 Jan. 2014
  • Firstpage
    3093
  • Lastpage
    3099
  • Abstract
    Using disaggregated data from a Chinese search engine we jointly model ad rank and performance for hospitality related keyword searches. As a result of our modeling framework we can better determine the optimal keyword bidding strategy for an advertiser given the search engine´s control over ad rank. Our approach removes rank bias in estimating keyword bidding performance. We then illustrate the impact of branded versus generic keyword searches, outlining profit maximizing keyword bidding.
  • Keywords
    advertising; query processing; search engines; tendering; Chinese search engine; ad rank modelling; branded keyword search; disaggregated data; generic keyword search; hospitality-related keyword search; keyword bidding performance estimation; optimal keyword bidding strategy; paid search process; performance modelling; rank bias removal; rank dependent behavior modeling; Advertising; Companies; Data models; Internet; Joints; Mathematical model; Search engines; Logistic Regression; Search Engine Marketing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences (HICSS), 2014 47th Hawaii International Conference on
  • Conference_Location
    Waikoloa, HI
  • Type

    conf

  • DOI
    10.1109/HICSS.2014.385
  • Filename
    6758986