Abstract: A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

Abstract: A method including the steps of generating, using one or more processors, a first statistical model fitted to first data related to in-store purchases resulting from economic browses made by known visitors to an online website, generating, using one or more processors, a bias correction to the first statistical model based on comparison between observed behavior of all unknown visitors to the online website and observed behavior of all known visitors to the online website, applying, using one or more processors, the generated bias correction to the first statistical model so as to obtain a second statistical model fitted to second data related to in-store purchases resulting from economic browses made by unknown visitors to the online website, and calculating, using one or more processors, a total monetary amount resulting from the in-store purchases made by the known and unknown visitors based on the first and second data.

Abstract: Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

Abstract: Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

Abstract: Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

Abstract: A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

Abstract: A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

Abstract: A method for maximizing page yield in advertisement display to Web users includes tracking click activity associated with advertisements displayed to users through a hierarchal set of search results pages associated with a keyword; tracking bidding activity by advertisers related to the keyword and corresponding advertisements of the advertisements; applying at least one component model to the click or bidding activity as correlated with a particular search results page of the hierarchal set of search results pages via which the advertisements receiving the click activity are displayed, wherein the at least one component model generates a set of output values representative of the tracked click activity; and providing the output values to the at least one component model to iteratively optimize a number of advertisements displayed on the particular search results page via which at least some of the advertisements are displayed in response to a query for the keyword.

Abstract: A method for valuating an advertiser considered for acquisition includes capturing click-related data by users with reference to a plurality of advertisements owned by a plurality of advertisers in a keyword market; calculating a marginal value of each of the plurality of advertisers as a function of a plurality of averaged market factors, wherein the marginal value of an additional advertiser is also calculated to result in at least an estimated displaced revenue if at least one advertisement of the additional advertiser for at least one keyword were competitively included in the keyword market; and deciding whether to pursue the additional advertiser based on the marginal value of the additional advertiser as associated with the at least one keyword.

Abstract: Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

Abstract: Embodiments of the present invention provide systems, methods and computer program products for assessing advertiser response based upon change in click traffic and value. One embodiment of a method for assessing advertiser response includes determining one or more keyword markets impacted by a traffic quality action, setting a baseline cost per acquisition for the one or more keyword markets impacted by the traffic quality action, determining one or more advertising metrics for the one or more keyword markets impacted by the traffic quality action having a certain network market value, fitting the one or more advertising metrics into a probabilistic model and determining the probability of reaction of the one or more keyword markets to changes in the one or more advertising metrics. The present invention provides systematic model to assess advertiser response that addresses all of the limitations of today's advertiser response assessment.

Abstract: A method for valuating an advertiser considered for acquisition includes capturing click-related data by users with reference to a plurality of advertisements owned by a plurality of advertisers in a keyword market; calculating a marginal value of each of the plurality of advertisers as a function of a plurality of averaged market factors, wherein the marginal value of an additional advertiser is also calculated to result in at least an estimated displaced revenue if at least one advertisement of the additional advertiser for at least one keyword were competitively included in the keyword market; and deciding whether to pursue the additional advertiser based on the marginal value of the additional advertiser as associated with the at least one keyword.

Abstract: A method for maximizing page yield in advertisement display to Web users includes tracking click activity associated with advertisements displayed to users through a hierarchal set of search results pages associated with a keyword; tracking bidding activity by advertisers related to the keyword and corresponding advertisements of the advertisements; applying at least one component model to the click or bidding activity as correlated with a particular search results page of the hierarchal set of search results pages via which the advertisements receiving the click activity are displayed, wherein the at least one component model generates a set of output values representative of the tracked click activity; and providing the output values to the at least one component model to iteratively optimize a number of advertisements displayed on the particular search results page via which at least some of the advertisements are displayed in response to a query for the keyword.

Abstract: A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

Abstract: The present invention relates to systems and methods for generating an adjustment factor for a cost associated with a user selection of an advertisement displayed at a website. The method of the present invention comprises retrieving analytics data and traffic quality metric data associated with the website, and calculating a traffic quality score for the website. An adjustment factor for the website is calculated based upon the traffic quality score associated with the website and a benchmark traffic quality score.