To Bid or Not to Bid? - Keyword Selection in Paid Search Advertising
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The selection of keywords for bidding is a critical component of paid search advertising. When thenumber of possible keywords is enormous, it becomes difficult to choose the best keywords foradvertising and then subsequently to assess their effect. To this end, we propose an ultrahighdimensional keyword selection approach that not only reduces the dimension for selections, but alsogenerates the top listed keywords for profits. An empirical analysis using a unique panel dataset froma large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) ispresented to illustrate the usefulness of our approach.
Abstract
The selection of keywords for bidding is a critical component of paid search advertising. When thenumber of possible keywords is enormous, it becomes difficult to choose the best keywords foradvertising and then subsequently to assess their effect. To this end, we propose an ultrahighdimensional keyword selection approach that not only reduces the dimension for selections, but alsogenerates the top listed keywords for profits. An empirical analysis using a unique panel dataset froma large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) ispresented to illustrate the usefulness of our approach.
참고문헌 (9)
- Chen, J., "Extended Bayesian information criterion for model selection with large model spaces", Biometrika, 95(3) (2008)
- George, E. I., "The variable selection problem", Journal of the American Statistical Association, 95(452) (2000)
- Mehta, A., "Adwords and Generalized Online Matching", Journal of the ACM, 54(5) (2007)
- Fan, J., "Sure independence screening for ultra-high dimensional feature space (with discussion)", Journal of the Royal Statistical Society, Series B, 70(5) (2008)
- Ghose, A., "An empirical analysis of search engine advertising: sponsored search in electronic markets", Management Science, 55(10) (2009)
- Tibshirani, R., "Regression shrinkage and selection via the lasso", Journal of the Royal Statistical Society, Series B, 58(1) (1996)
- West, M., "paradigm:Bayesian Statistics, Proc. Seventh Valencia Internat. Meeting", pp.723~732 (2003), Oxford University Press
- Wang, H., "Forward regression for ultrahigh dimensional variable screening", Journal of the American Statistical Association, 104(488) (2009)
- Zou, H., "Regularization and variable selection via the elastic net", Journal of the Royal Statistical Society, Series B, 67(2) (2005)