Abstract: The present application relates to systems and computer-implemented methods for conducting a second price auction associated with an opportunity to realize an online advertisement. In some implementations, advertisers may be informed with the opportunity to realize the online advertisement, and may be provided with information associated with a user that may view the opportunity to realize the online advertisement; an individual reserve price may then be determined for each advertiser, based on the advertiser's individual bidding preference and the information associated with the user; and then the auction may be conducted to determine a winning bidder among candidate advertisers whose bidding price is higher than the individual reserve price associated therewith, using second price method.

Abstract: The present application relates to systems and computer-implemented methods for calculating a suggested reserve price associated with an opportunity to realize an online advertisement. In some implementations, a database of historical online advertisement auctions is established; historical online advertisement auctions from the database of historical online advertisement auctions that are associated with a feature are clustered to form a cluster; a reserve price associated with the cluster of historical online advertisement auctions is calculated to generate a desired revenue; and the reserve price is stored as a suggested reserve price for the opportunity to realize the online advertisement that is associated with the feature.

Abstract: The present application relates to systems and computer-implemented methods for calculating a suggested reserve price associated with an opportunity to realize an online advertisement. In some implementations, data associated with historical online advertisement auctions are clustered based on a reference opportunity for realizing an online advertisement, wherein each historical online advertisement auction of the cluster is associated with a first bid price of higher value and a second bid price of lower value; a dominance relationship between a distribution of the first bid prices of the cluster and a distribution of the second bid prices of the cluster is determined; a reserve price associated with the cluster based on the dominance relationship is calculated; and the reserve price is stored as a suggested reserve price to realize an online advertisement, wherein the suggested reserve price is associated with the reference opportunity that is associated with the cluster.

Abstract: The present application relates to systems and computer-implemented methods for determining a future bidding strategy regarding auctions associated with realization of an online advertisement. In some implementations, a server may be used to determine an optimized bid pacing parameter for an online advertisement based on a current bid pacing parameter associated with the online advertisement and an online advertisement supply information for a time period so that based on the optimized bid pacing, realization of the online advertisement over the time period substantially confirms to a spending strategy associated with the online advertisement during the time period. As such, the systems and computer-implemented methods may allow advertisers to control their spending strategy accurately during an advertising campaign.

Abstract: The present application relates to systems and computer-implemented methods for calculating a suggested market variable associated with an auction of an online advertisement realization opportunity. In some implementations, an optimization procedure may be operated, wherein the optimization procedure may comprise sending an initial market variable associated with one or more auctions to bidding agents; receiving from each of the bidding agents a response market variable associated with the initial market variable; determining according to an auction bidding rule a winning market variable from the response market variables; and substituting the initial market variable with the wining market variable. The optimization procedure may be operated repeatedly until the winning market variable stabilizes. Then the stabilized market variable may be sent to an advertiser as the suggested market variable.

Abstract: A method, system, and computer program product for using advertising campaign allocation optimization results to calculate bids. The method commences by receiving a candidate impression opportunity corresponding to an advertising campaign that has both branding objectives and performance-based objectives. Contracts that can be satisfied by serving the candidate impression opportunity use advertising campaign allocation optimization results to determine a set of matching contracts. Given the matching contracts, the method continues to calculate bids for those matching contracts, then selects a target contract from among the matching contracts. The method then bids on the candidate impression opportunity using the calculated bid of the selected target contract. The method optimizes for overall campaign performance even when the campaign includes both branding campaign objectives and performance-based campaign objectives.

Abstract: Techniques are provided which improve performance of bid agents on online advertising exchanges. Methods and systems elicit an advertiser's goals for an online advertising campaign. One or more bid agents are selected to be included in a bid program based at least in part on the goals. Each of the bid agents is matched to one or more goals, and each of the bid agents is configured to calculate a bid for an ad call based at least in part on predetermined rules. One or more parameters of the selected bid agents are set based at least in part on marketplace conditions in an online advertising exchange.