Abstract: Systems and methods for cross-platform exposure limits of content are described herein. For example, an indication of an exposure limit associated with an advertisement may be determined. The advertisement may be output via each of a plurality of different platform types. The quantity of outputs of the advertisement across the plurality of different platform types may be limited based on the exposure limit.

Abstract: Systems and methods for tracking impressions across a plurality of platforms are described. For example, a method may include receiving information indicating a plurality of outputs of content via a plurality of platforms. The plurality of platforms may comprise different platform types. Impression information for the content may be stored across the plurality of platforms. Based on the impression information, one or more additional outputs of the content, via the plurality of platforms, may be caused.

Abstract: Systems and methods for the optimized allocation of content according to a schedule are described. In some embodiments, a system may be configured to modify a schedule file to replace broadcast content. The system may receive the schedule file indicating an identifier associated with content to be output during a slot associated with a time window in a broadcast event. The system may modify the schedule file to replace the identifier with a replacement identifier associated with replacement content. The system may transmit the broadcast event as a linear feed comprising the replacement content.

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 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: 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: 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: 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 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: 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 and systems for dynamic modification of an audience are disclosed. A portion of an audience to which a supplemental content item was output during output of a first content item may be determined. A modified audience may be determined based on at least one characteristic associated with the portion of the audience to which the supplemental content item was output during output of the first content item. Output of the supplemental content item may be caused during output of a second content item. The second content item may be determined based on at least one characteristic associated with the modified audience.

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 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.