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Optimal Keyword Bids in Search-Based Advertising with Stochastic Advertisement Positions

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Abstract

US expenditures on search-based advertising exceeded $12 billion in 2010. Advertisers bid for keywords, where bid price determines ad placement, affecting click-through and conversion rates. Advertisers must select keywords, allocating each a proportion of their fixed daily budget. In this paper, we construct a stochastic model for the selection and allocation process. We provide analytical results for the single-keyword problem and examine the multiple-keyword problem numerically. We investigate trade-offs between keywords given varying levels of risk and return. We show the implications of enforcing a probabilistic budget constraint. Our paper provides a critical analysis of the advertiser’s problem that may guide future research.

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Authors and Affiliations

  1. San Francisco State University, San Francisco, CA, 94132, USA

    Susan Cholette & Özgür Özlük

  2. DeGroote School of Business, McMaster University, Hamilton, Ontario, L8S 4M4, Canada

    Mahmut Parlar

Authors
  1. Susan Cholette
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  2. Özgür Özlük
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  3. Mahmut Parlar
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Corresponding author

Correspondence to Özgür Özlük.

Additional information

The authors thank the Editor-in-Chief for his constructive comments that have improved the exposition of the paper.

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Cholette, S., Özlük, Ö. & Parlar, M. Optimal Keyword Bids in Search-Based Advertising with Stochastic Advertisement Positions. J Optim Theory Appl 152, 225–244 (2012). https://doi.org/10.1007/s10957-011-9886-3

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  • DOI: https://doi.org/10.1007/s10957-011-9886-3

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