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

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.