Journal of Optimization Theory and Applications

, Volume 152, Issue 1, pp 225-244

First online:

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

  • Susan CholetteAffiliated withSan Francisco State University
  • , Özgür ÖzlükAffiliated withSan Francisco State University Email author 
  • , Mahmut ParlarAffiliated withDeGroote School of Business, McMaster University

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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.


Search-based advertising Budget optimization Probabilistic models