Abstract: Systems and methods for the optimized allocation of content within a universe of inventory are described. For example, a method may include receiving content comprising at least one characteristic and at least one goal. A universe of inventory may be accessed that comprises a plurality of targets which may be assigned into a plurality of segments based on at least one demographic vector. An allocation optimization model may be generated based on the at least one content characteristic, the at least one goal and the plurality of segments. The content may be presented to the targets based on the allocation optimization model. Viewing data may be received that comprises data associated with target consumption of the content and the allocation optimization module may be re-optimized based on the viewing data. Additional factors, such as resource constraints and/or filtering rules, may be used when re-optimizing the allocation optimization module.

Abstract: Methods, systems, and apparatuses for audience metric determination are described herein. An audience segment may be targeted for delivery of content. A clustering algorithm may be used to categorize a quantity of users or devices into subsets based on a propensity to consume, present or output a particular type of content, and a quantity of time to output the particular type of content. A weight may be assigned to each subset based on its relevance to other subsets, such as based on data variance, e.g., on a distance to a midpoint of a specific subset of the subsets. An index parameter may be determined for the datasets, e.g., based on each weight for each subset, and data may be generated that reflects a ranking of content delivery spots for delivery of content to the audience segment.

Abstract: Systems, methods and computer-readable media for a decentralized application system that enables participating parties to automate the buying and selling of TV media units and/or aggregated TV and premium video audiences is described. The value-based TV/premium video media exchange application system allows the participants to interact with the system directly and/or automate transactions and execution between systems, while ensuring proper governance over each participants own rules and economics associated with the transactions, as well as individual campaign constraints and requirements. The decentralized application system significantly lowers current transaction and execution barriers, timing and costs, while providing a highly accountable and trusted system across all of the exchange participants.

Abstract: Systems, methods and computer-readable media for a decentralized application system that enables participating parties to automate the buying and selling of TV media units and/or aggregated TV and premium video audiences is described. The value-based TV/premium video media exchange application system allows the participants to interact with the system directly and/or automate transactions and execution between systems, while ensuring proper governance over each participants own rules and economics associated with the transactions, as well as individual campaign constraints and requirements. The decentralized application system significantly lowers current transaction and execution barriers, timing and costs, while providing a highly accountable and trusted system across all of the exchange participants.

Abstract: Methods, systems, and apparatuses for audience metric determination are described herein. An audience segment may be targeted for delivery of content. A clustering algorithm may be used to categorize a quantity of users or devices into subsets based on a propensity to consume, present or output a particular type of content, and a quantity of time to output the particular type of content. A weight may be assigned to each subset based on its relevance to other subsets, such as based on data variance, e.g., on a distance to a midpoint of a specific subset of the subsets. An index parameter may be determined for the datasets, e.g., based on each weight for each subset, and data may be generated that reflects a ranking of content delivery spots for delivery of content to the audience segment.

Abstract: Methods, systems, and apparatuses for content viewership statistic adjustment are described herein. Content viewership data is analyzed. A start time and an end time of a delivery of a content item in a content viewing session is determined based on the analysis. A false positive viewing event is determined based on a comparison between a viewing characteristic of the content viewing session and a threshold. The determined false positive viewing event is removed from a viewership statistic.

Abstract: Systems and methods for the optimized allocation of content on a content distribution system according to a content distribution plan are described. In some embodiments, a management system may be configured to generate an optimized schedule for content distribution, such as an advertising campaign. For a television distribution schedule, an impressions forecast may be generated based on the available inventory and historical audience measurement information, such as television ratings for a television advertising campaign. An optimized schedule may be generated based on the impressions forecast and content may be distributed according to the optimized schedule. Measurement information relating to the distribution according to the optimized schedule may be analyzed and used to generate a re-optimized schedule, for example, that may be used to schedule the advertising campaign on a subsequent day.

Abstract: A content provider may receive an indication for supplemental content to be output to a target audience, determine a first content item to be viewed by the target audience based on one or more characteristics of the target audience, and may send an indication for the supplemental content to be output at a time associated with the output of the first content item. The content provider may determine a quantity of devices which output the supplemental content for a first time and may determine that this quantity of devices is below a target quantity of devices to output the supplemental content for the first time during a particular time period. The content provider may determine a second content item to be viewed by the target audience and may send an indication for the supplemental content to be output at a time associated with output of the second content item.

Abstract: Systems and methods for the optimized allocation of content within a universe of inventory are described. For example, a method may include receiving content comprising at least one characteristic and at least one goal. A universe of inventory may be accessed that comprises a plurality of targets which may be assigned into a plurality of segments based on at least one demographic vector. An allocation optimization model may be generated based on the at least one content characteristic, the at least one goal and the plurality of segments. The content may be presented to the targets based on the allocation optimization model. Viewing data may be received that comprises data associated with target consumption of the content and the allocation optimization module may be re-optimized based on the viewing data. Additional factors, such as resource constraints and/or filtering rules, may be used when re-optimizing the allocation optimization module.

Abstract: Systems and methods for the optimized allocation of content within a universe of inventory are described. For example, a method may include receiving content comprising at least one characteristic and at least one goal. A universe of inventory may be accessed that comprises a plurality of targets which may be assigned into a plurality of segments based on at least one demographic vector. An allocation optimization model may be generated based on the at least one content characteristic, the at least one goal and the plurality of segments. The content may be presented to the targets based on the allocation optimization model. Viewing data may be received that comprises data associated with target consumption of the content and the allocation optimization module may be re-optimized based on the viewing data. Additional factors, such as resource constraints and/or filtering rules, may be used when re-optimizing the allocation optimization module.

Abstract: Systems and methods for the optimized allocation of content on a content distribution system according to a content distribution plan are described. In some embodiments, a management system may be configured to generate an optimized schedule for content distribution, such as an advertising campaign. For a television distribution schedule, an impressions forecast may be generated based on the available inventory and historical audience measurement information, such as television ratings for a television advertising campaign. An optimized schedule may be generated based on the impressions forecast and content may be distributed according to the optimized schedule. Measurement information relating to the distribution according to the optimized schedule may be analyzed and used to generate a re-optimized schedule, for example, that may be used to schedule the advertising campaign on a subsequent day.

Abstract: Systems, methods and computer-readable media for a decentralized application system that enables participating parties to automate the buying and selling of TV media units and/or aggregated TV and premium video audiences is described. The value-based TV/premium video media exchange application system allows the participants to interact with the system directly and/or automate transactions and execution between systems, while ensuring proper governance over each participants own rules and economics associated with the transactions, as well as individual campaign constraints and requirements. The decentralized application system significantly lowers current transaction and execution barriers, timing and costs, while providing a highly accountable and trusted system across all of the exchange participants.

Abstract: Systems and methods for frequency capping of content are described herein. For example, frequency cap information may be configured to indicate a content exposure limit for a content presentation. The number of exposures to the content presentation at a particular household may be monitored. If the number of exposures is equal to or greater than the content exposure limit, the content may be prevented from being presented to the household. The frequency cap information may be used alone or in combination with other information, such as household demographic, timeframe, and day-part information.

Abstract: A content provider may receive an indication for supplemental content to be output to a target audience, determine a first content item to be viewed by the target audience based on one or more characteristics of the target audience, and may send an indication for the supplemental content to be output at a time associated with the output of the first content item. The content provider may determine a quantity of devices which output the supplemental content for a first time and may determine that this quantity of devices is below a target quantity of devices to output the supplemental content for the first time during a particular time period. The content provider may determine a second content item to be viewed by the target audience and may send an indication for the supplemental content to be output at a time associated with output of the second content item.

Abstract: A content provider may receive an indication for supplemental content to be output to a target audience, determine a first content item to be viewed by the target audience based on one or more characteristics of the target audience, and may send an indication for the supplemental content to be output at a time associated with the output of the first content item. The content provider may determine a quantity of devices which output the supplemental content for a first time and may determine that this quantity of devices is below a target quantity of devices to output the supplemental content for the first time during a particular time period. The content provider may determine a second content item to be viewed by the target audience and may send an indication for the supplemental content to be output at a time associated with output of the second content item.

Abstract: Systems, methods and computer-readable media for a decentralized application system that enables participating parties to automate the buying and selling of TV media units and/or aggregated TV and premium video audiences is described. The value-based TV/premium video media exchange application system allows the participants to interact with the system directly and/or automate transactions and execution between systems, while ensuring proper governance over each participants own rules and economics associated with the transactions, as well as individual campaign constraints and requirements. The decentralized application system significantly lowers current transaction and execution barriers, timing and costs, while providing a highly accountable and trusted system across all of the exchange participants.

Abstract: Systems and methods for the optimized allocation of content within a universe of inventory are described. For example, a method may include receiving content comprising at least one characteristic and at least one goal. A universe of inventory may be accessed that comprises a plurality of targets which may be assigned into a plurality of segments based on at least one demographic vector. An allocation optimization model may be generated based on the at least one content characteristic, the at least one goal and the plurality of segments. The content may be presented to the targets based on the allocation optimization model. Viewing data may be received that comprises data associated with target consumption of the content and the allocation optimization module may be re-optimized based on the viewing data. Additional factors, such as resource constraints and/or filtering rules, may be used when re-optimizing the allocation optimization module.

Abstract: Systems and methods for frequency capping of content are described herein. For example, frequency cap information may be configured to indicate a content exposure limit for a content presentation. The number of exposures to the content presentation at a particular household may be monitored. If the number of exposures is equal to or greater than the content exposure limit, the content may be prevented from being presented to the household. The frequency cap information may be used alone or in combination with other information, such as household demographic, timeframe, and day-part information.

Abstract: Systems and methods for the optimized allocation of content within a universe of inventory are described. For example, a method may include receiving content comprising at least one characteristic and at least one goal. A universe of inventory may be accessed that comprises a plurality of targets which may be assigned into a plurality of segments based on at least one demographic vector. An allocation optimization model may be generated based on the at least one content characteristic, the at least one goal and the plurality of segments. The content may be presented to the targets based on the allocation optimization model. Viewing data may be received that comprises data associated with target consumption of the content and the allocation optimization module may be re-optimized based on the viewing data. Additional factors, such as resource constraints and/or filtering rules, may be used when re-optimizing the allocation optimization module.

Abstract: Systems and methods for the optimized allocation of content within a universe of inventory are described. For example, a method may include receiving content comprising at least one characteristic and at least one goal. A universe of inventory may be accessed that comprises a plurality of targets which may be assigned into a plurality of segments based on at least one demographic vector. An allocation optimization model may be generated based on the at least one content characteristic, the at least one goal and the plurality of segments. The content may be presented to the targets based on the allocation optimization model. Viewing data may be received that comprises data associated with target consumption of the content and the allocation optimization module may be re-optimized based on the viewing data. Additional factors, such as resource constraints and/or filtering rules, may be used when re-optimizing the allocation optimization module.