Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving one or more user-defined objectives associated with a group of data elements, wherein at least one of the user-defined objectives includes an objective related to a selected target group; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; developing a first prediction of a performance of the group of data elements during a time period based on the one or more user-defined objectives and the one or more constraints; and apportioning at least a portion of the resources to each data element in the group of data elements based on the first prediction once the time period has started.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a designation of one or more data elements for distribution; receiving a designation of a plurality of electronic event types detectable over a network, the plurality of electronic event types being associated with receipt or electronic display of at least one data element of the one or more data elements, to be tracked; forecasting a return on investment, associated with distribution of the one or more data elements, based on a forecast of occurrences of the plurality of electronic event types; and optimizing distribution of resources to the one or more data elements based on the forecasted return on investment.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a selection of a first objective and a second objective, the first objective and second objective comprising goals associated with distribution of a plurality of data elements; receiving an indication that the first objective has a higher priority than the second objective; receiving a first goal metric associated with the first objective and a second goal metric associated with the second objective; determining a first forecasted metric based on the first goal metric associated with the first objective; determining a second forecasted metric based on the second goal metric associated with the second objective; and allocating resources for the distribution of a plurality of data elements based on the first goal metric, the second goal metric, the first forecasted metric, the second forecasted metric, and the indication that the first objective has a higher priority than the second objective.

Abstract: Systems and methods are disclosed for optimizing data element usage according to user-defined objectives, comprising receiving a plurality of user-defined objectives associated with a group of data elements; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; apportioning at least a portion of the resources to each data element in the group of data elements in a manner that meets the one or more constraints; receiving metrics associated with the performance of the group of data elements in meeting the plurality of user-defined objectives; determining an effectiveness of each data element in the group of data elements for meeting the plurality of user-defined objectives; and automatically revising the at least a portion of resources associated with each data element in the group of data elements.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving one or more user-defined objectives associated with a group of data elements, wherein at least one of the user-defined objectives includes an objective related to a selected target group; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; developing a first prediction of a performance of the group of data elements during a time period based on the one or more user-defined objectives and the one or more constraints; and apportioning at least a portion of the resources to each data element in the group of data elements based on the first prediction once the time period has started.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a designation of one or more data elements for distribution; receiving a designation of a plurality of electronic event types detectable over a network, the plurality of electronic event types being associated with receipt or electronic display of at least one data element of the one or more data elements, to be tracked; forecasting a return on investment, associated with distribution of the one or more data elements, based on a forecast of occurrences of the plurality of electronic event types; and optimizing distribution of resources to the one or more data elements based on the forecasted return on investment.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a selection of a first objective and a second objective, the first objective and second objective comprising goals associated with distribution of a plurality of data elements; receiving an indication that the first objective has a higher priority than the second objective; receiving a first goal metric associated with the first objective and a second goal metric associated with the second objective; determining a first forecasted metric based on the first goal metric associated with the first objective; determining a second forecasted metric based on the second goal metric associated with the second objective; and allocating resources for the distribution of a plurality of data elements based on the first goal metric, the second goal metric, the first forecasted metric, the second forecasted metric, and the indication that the first objective has a higher priority than the second objective.

Abstract: Systems and methods are disclosed for optimizing data element usage according to user-defined objectives, comprising receiving a plurality of user-defined objectives associated with a group of data elements; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; apportioning at least a portion of the resources to each data element in the group of data elements in a manner that meets the one or more constraints; receiving metrics associated with the performance of the group of data elements in meeting the plurality of user-defined objectives; determining an effectiveness of each data element in the group of data elements for meeting the plurality of user-defined objectives; and automatically revising the at least a portion of resources associated with each data element in the group of data elements.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a designation of one or more data elements for distribution; receiving a designation of a plurality of electronic event types detectable over a network, the plurality of electronic event types being associated with receipt or electronic display of at least one data element of the one or more data elements, to be tracked; forecasting a return on investment, associated with distribution of the one or more data elements, based on a forecast of occurrences of the plurality of electronic event types; and optimizing distribution of resources to the one or more data elements based on the forecasted return on investment.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving one or more user-defined objectives associated with a group of data elements, wherein at least one of the user-defined objectives includes an objective related to a selected target group; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; developing a first prediction of a performance of the group of data elements during a time period based on the one or more user-defined objectives and the one or more constraints; and apportioning at least a portion of the resources to each data element in the group of data elements based on the first prediction once the time period has started.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a designation of one or more data elements for distribution; receiving a designation of a plurality of electronic event types detectable over a network, the plurality of electronic event types being associated with receipt or electronic display of at least one data element of the one or more data elements, to be tracked; forecasting a return on investment, associated with distribution of the one or more data elements, based on a forecast of occurrences of the plurality of electronic event types; and optimizing distribution of resources to the one or more data elements based on the forecasted return on investment.

Abstract: In various embodiments, methods and systems for optimizing viewability rates by utilizing pre-bid client-side detection in autonomous bid-decisioning for advertising campaigns is provided. When provided with a unitary demand-side platform and sell-side platform system, advertisers may employ aspects of the present disclosure to pose a significant advantage in optimizing viewability rates for exchange sites purchased on the open digital advertising market. An advertiser, by way of the unitary demand-side and sell-side platform, can determine that runtime pre-bid viewability data corresponding to an exchange site is available. Based on the runtime pre-bid viewability data and historical performance data corresponding to the exchange site, an optimized calculation can be made to infer a substantially high likelihood of viewability if the exchange site is ultimately purchased by the advertiser.

Abstract: Systems and methods are disclosed for optimizing data element usage according to user-defined objectives, comprising receiving a plurality of user-defined objectives associated with a group of data elements; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; apportioning at least a portion of the resources to each data element in the group of data elements in a manner that meets the one or more constraints; receiving metrics associated with the performance of the group of data elements in meeting the plurality of user-defined objectives; determining an effectiveness of each data element in the group of data elements for meeting the plurality of user-defined objectives; and automatically revising the at least a portion of resources associated with each data element in the group of data elements.

Abstract: Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a selection of a first objective and a second objective, the first objective and second objective comprising goals associated with distribution of a plurality of data elements; receiving an indication that the first objective has a higher priority than the second objective; receiving a first goal metric associated with the first objective and a second goal metric associated with the second objective; determining a first forecasted metric based on the first goal metric associated with the first objective; determining a second forecasted metric based on the second goal metric associated with the second objective; and allocating resources for the distribution of a plurality of data elements based on the first goal metric, the second goal metric, the first forecasted metric, the second forecasted metric, and the indication that the first objective has a higher priority than the second objective.

Abstract: Methods, systems and computer program products are provided for targeting users for content provision. In one method, the method receives at a server, one or more content objects and one or more ZIP+4 codes as targeting parameters for the one or more content objects. The method retrieves personal information of a plurality of users. The method then identifies one or more of the plurality of users located in geographic areas corresponding to the one or more ZIP+4 codes based, at least in part, on the personal information. Subsequently, the method targets a content object of the one or more content objects to the one or more of the plurality of users based on the identified geographic areas of the users and the ZIP+4 codes associated with corresponding ones of the one or more content objects.

Abstract: Methods, systems and computer program products are provided for targeting users for content provision. In one method, the method receives at a server, one or more content objects and one or more ZIP+4 codes as targeting parameters for the one or more content objects. The method retrieves personal information of a plurality of users. The method then identifies one or more of the plurality of users located in geographic areas corresponding to the one or more ZIP+4 codes based, at least in part, on the personal information. Subsequently, the method targets a content object of the one or more content objects to the one or more of the plurality of users based on the identified geographic areas of the users and the ZIP+4 codes associated with corresponding ones of the one or more content objects.

Abstract: Anonymous measurement of online advertising using offline sales is disclosed. The measurement uses anonymized online ad exposure data and anonymized offline sales, or conversion data, to measure effectiveness of online advertisement. The anonymized exposure and conversion data are matched using tokens from each data set; each token corresponds to a user and is generated from personally identifiable information of the user that is anonymized to preserve the user's privacy. The anonymized exposure and conversion data is aggregated using the tokens to map records in the data sets for a given user. Users' ad exposure and sales history is used, anonymously, to gauge ad effectiveness of a corresponding ad campaign. The effectiveness measure, or measures, can further be used to configure another ad campaign.

Abstract: Determining the impact or influence of targeting data on the success of an advertisement may be useful for improving targeting and evaluating third party targeting data. Advertising may be more effective when it is properly targeted based on the audience viewing the advertisement. Identifying the audience and determining information about that audience are part of the targeting process. Audience information or targeting data may be provided by third party data providers that can be used by publishers and/or advertisers to improve targeting. Utilizing a model for assessing the value provided by targeting data may be effective when multiple variables are considered to properly attribute advertisement success to the targeting data.

Abstract: Anonymous measurement of online advertising using offline sales is disclosed. The measurement uses anonymized online ad exposure data and anonymized offline sales, or conversion data, to measure effectiveness of online advertisement. The anonymized exposure and conversion data are matched using tokens from each data set; each token corresponds to a user and is generated from personally identifiable information of the user that is anonymized to preserve the user's privacy. The anonymized exposure and conversion data is aggregated using the tokens to map records in the data sets for a given user. Users' ad exposure and sales history is used, anonymously, to gauge ad effectiveness of a corresponding ad campaign. The effectiveness measure, or measures, can further be used to configure another ad campaign.

Abstract: Methods, systems and computer program products are provided for targeting users for content provision. In one method, the method receives at a server, one or more content objects and one or more ZIP+4 codes as targeting parameters for the one or more content objects. The method retrieves personal information of a plurality of users. The method then identifies one or more of the plurality of users located in geographic areas corresponding to the one or more ZIP+4 codes based, at least in part, on the personal information. Subsequently, the method targets a content object of the one or more content objects to the one or more of the plurality of users based on the identified geographic areas of the users and the ZIP+4 codes associated with corresponding ones of the one or more content objects.