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
Link To Document