Optimal keyword bidding in search-based advertising with target exposure levels
Search-based advertising has become very popular since it provides advertisers the ability to attract potential customers with measurable returns. In this type of advertising, advertisers bid on keywords to have an impact on their ad’s placement, which in turn affects the response from potential customers. An advertiser must choose the right keywords and then bid correctly for each keyword in order to maximize the expected revenue or attain a certain level of exposure while keeping the daily costs in mind. In response to increasing need for analytical models that provide a guidance to advertisers, we construct and examine deterministic optimization models that minimize total expected advertising costs while satisfying a desired level of exposure. We investigate the relationship between our problem and the well-known continuous non-linear knapsack problem, and then solve the problem optimally by utilizing Karush–Kuhn–Tucker conditions. We present practical managerial insights based on the analysis of both a real-life data from a retailer and a hypothetical data.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 226 (2013)
Issue (Month): 1 ()
|Contact details of provider:|| Web page: http://www.elsevier.com/locate/eor|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Zhao, Lan & Nagurney, Anna, 2008. "A network equilibrium framework for Internet advertising: Models, qualitative analysis, and algorithms," European Journal of Operational Research, Elsevier, vol. 187(2), pages 456-472, June.
- Kumar, Subodha & Sethi, Suresh P., 2009. "Dynamic pricing and advertising for web content providers," European Journal of Operational Research, Elsevier, vol. 197(3), pages 924-944, September.
- Kumar, Subodha & Jacob, Varghese S. & Sriskandarajah, Chelliah, 2006. "Scheduling advertisements on a web page to maximize revenue," European Journal of Operational Research, Elsevier, vol. 173(3), pages 1067-1089, September.
- Oliver J. Rutz & Michael Trusov & Randolph E. Bucklin, 2011. "Modeling Indirect Effects of Paid Search Advertising: Which Keywords Lead to More Future Visits?," Marketing Science, INFORMS, vol. 30(4), pages 646-665, July.
- Bretthauer, Kurt M. & Shetty, Bala, 2002. "The nonlinear knapsack problem - algorithms and applications," European Journal of Operational Research, Elsevier, vol. 138(3), pages 459-472, May.
- Kinshuk Jerath & Liye Ma & Young-Hoon Park & Kannan Srinivasan, 2011. "A "Position Paradox" in Sponsored Search Auctions," Marketing Science, INFORMS, vol. 30(4), pages 612-627, July.
- Zsolt Katona & Miklos Sarvary, 2010. "The Race for Sponsored Links: Bidding Patterns for Search Advertising," Marketing Science, INFORMS, vol. 29(2), pages 199-215, 03-04.
- Sha Yang & Anindya Ghose, 2010. "Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence?," Marketing Science, INFORMS, vol. 29(4), pages 602-623, 07-08.
- John F. Stewart, 1979. "The Beta Distribution as a Model of Behavior in Consumer Goods Markets," Management Science, INFORMS, vol. 25(9), pages 813-821, September.
When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:226:y:2013:i:1:p:163-172. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.