Abstract: A method is described that includes accessing bids for ranked goods and minimum rank indicators that each specifies a lowest rank for a good that is acceptable to a bidder, assigning a ranked good to a first bidder based on a first bid and a first minimum rank indicator each associated with the first bidder, and outputting a signal indicative of a cost of the assigned rank good based on a second bid associated with a next highest bidder having a second minimum rank indicator that specifies a rank that is inclusive of a rank of the ranked good assigned to the first bidder.

Abstract: In an online advertising system, preferred cost bidding allows advertisers to specify a preferred “average” cost target (e.g., cost-per-click (CPC), cost per thousand impressions (CPM)), rather than a “maximum” cost target (e.g., maximum CPC, CPM). The system attempts to bring the advertiser's overall advertising cost as close as possible to the advertiser's specified average cost, using an iterative process (e.g., a feedback loop) that updates bids for keywords using historical performance data for the key words. In some implementations, a bid is automatically adjusted in an adaptive way to compensate for natural changes in fluctuations of the market using historical performance data to compute a bid that is likely to result in an average cost (per click) that is close to the advertiser's preferred average target cost (per click).