Abstract: The present disclosure relates to methods, systems, and apparatuses for providing promotion recommendations using a promotion and marketing service. Some aspects may provide a method for providing a promotion recommendation framework. The method includes receiving, via a network interface, a promotion recommendation inquiry from a component of a promotion and marketing service, the promotion recommendation inquiry including electronic identification data identifying at least one of a consumer or a consumer characteristic. The method also includes identifying, via processing circuitry, promotion transaction information associated with the electronic identification data. The promotion transaction information includes electronic data identifying at least one transaction performed using the promotion and marketing service.

Abstract: A method, apparatus, and computer program product are disclosed to score elements of a structure database. The method includes accessing a structure database comprising one or more promotion options, one or more promotion option structures, and one or more promotion structures, wherein each promotion structure comprises one or more of the promotion option structures, each promotion option structure corresponds to one or more of the promotion options, and each promotion option is associated with at least one service. The method further includes generating a promotion option score for each promotion option in the structure database, generating, by a processor, a promotion option structure score for each promotion option structure in the structure database, and generating a promotion structure score for each promotion structure in the structure database. A corresponding apparatus and computer program product are also provided.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for recommending contextually relevant promotions to consumers in order to facilitate their discovery of promotions that they are likely to purchase from a promotion and marketing service.

Abstract: A method, apparatus, and computer program product are disclosed for improved machine learning using a statistical model. In the context of an apparatus, some example embodiments include a processor configured to cause retrieval of information regarding a plurality of consumers, and modeling circuitry configured to train a statistical model of the plurality of consumers based on the retrieved information, and predict, using the statistical model, an incremental booking value associated with the promotion for each consumer of the plurality of consumers. The processor is further configured to select a subset of the plurality of consumers for receiving impressions of the promotion. Some example embodiments may further include communications circuitry configured to transmit an impression of the promotion to each consumer in the subset of the plurality of consumers.

Abstract: A method, apparatus, and computer program product are disclosed to score elements of a structure database. The method includes accessing a structure database comprising one or more promotion options, one or more promotion option structures, and one or more promotion structures, wherein each promotion structure comprises one or more of the promotion option structures, each promotion option structure corresponds to one or more of the promotion options, and each promotion option is associated with at least one service. The method further includes generating a promotion option score for each promotion option in the structure database, generating, by a processor, a promotion option structure score for each promotion option structure in the structure database, and generating a promotion structure score for each promotion structure in the structure database. A corresponding apparatus and computer program product are also provided.

Abstract: A method, apparatus, and computer program product are disclosed for improved machine learning using a statistical model. In the context of an apparatus, some example embodiments include a processor configured to cause retrieval of information regarding a plurality of consumers, and modeling circuitry configured to train a statistical model of the plurality of consumers based on the retrieved information, and predict, using the statistical model, an incremental booking value associated with the promotion for each consumer of the plurality of consumers. The processor is further configured to select a subset of the plurality of consumers for receiving impressions of the promotion. Some example embodiments may further include communications circuitry configured to transmit an impression of the promotion to each consumer in the subset of the plurality of consumers.

Abstract: The present disclosure relates to methods, systems, and apparatuses for providing promotion recommendations using a promotion and marketing service. Some aspects may provide a method for providing a promotion recommendation framework. The method includes receiving, via a network interface, a promotion recommendation inquiry from a component of a promotion and marketing service, the promotion recommendation inquiry including electronic identification data identifying at least one of a consumer or a consumer characteristic. The method also includes identifying, via processing circuitry, promotion transaction information associated with the electronic identification data. The promotion transaction information includes electronic data identifying at least one transaction performed using the promotion and marketing service.

Abstract: Certain embodiments provide a computer-executed method for generating a future sales estimate for an item. The method includes programmatically accessing, from a dataset via a network device, an inventory residence time period of an item. The method also includes programmatically accessing, from the dataset via the network device, prior performance data associated with the item. The method also includes programmatically executing an inventory valuation engine to generate a future sales estimate for the item based on the inventory residence time period and the prior performance data. The method further includes executing a notification generation engine to adjust a notification policy defining a frequency or other characteristic of electronic marketing communications indicating the item transmitted to consumer devices based on the future sales estimate.

Abstract: The present disclosure relates to methods, systems, and apparatuses for providing promotion recommendations using a promotion and marketing service. Some aspects may provide a method for providing a promotion recommendation framework. The method includes receiving, via a network interface, a promotion recommendation inquiry from a component of a promotion and marketing service, the promotion recommendation inquiry including electronic identification data identifying at least one of a consumer or a consumer characteristic. The method also includes identifying, via processing circuitry, promotion transaction information associated with the electronic identification data. The promotion transaction information includes electronic data identifying at least one transaction performed using the promotion and marketing service.

Abstract: Certain embodiments provide a computer-executed method for generating a future sales estimate for an item. The method includes programmatically accessing, from a dataset via a network device, an inventory residence time period of an item. The method also includes programmatically accessing, from the dataset via the network device, prior performance data associated with the item. The method also includes programmatically executing an inventory valuation engine to generate a future sales estimate for the item based on the inventory residence time period and the prior performance data. The method further includes executing a notification generation engine to adjust a notification policy defining a frequency or other characteristic of electronic marketing communications indicating the item transmitted to consumer devices based on the future sales estimate.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: A variety of techniques are described by which keyword sets and target audience profiles may be generalized in a systematic and effective way with reference to relationships between keywords, profiles, and the data of an underlying user population.

Abstract: A variety of techniques are described by which keyword sets and target audience profiles may be generalized in a systematic and effective way with reference to relationships between keywords, profiles, and the data of an underlying user population.

Abstract: Methods and apparatus are described for presenting sponsored search results. A user is enabled to initiate a search from a context. The sponsored search results and organic search results are presented in a search results page in response to the search, an order of the sponsored search results and placement of subsets of the sponsored search results relative to the organic search results in the search results page having been determined with reference to contextual information relating to the context.

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.