Abstract: A method may include obtaining a data set associated with viewing of digital content. The method may also include matching at least a portion of the data set to at least one consumer in a consumer graph to obtain person matched data. The method may further include extrapolating the person matched data to a total audience. The method may also include obtaining a total estimate of viewership data associated with the viewing of the digital content based on the extrapolated person matched data. The method may further include obtaining a viewership estimate of the digital content based on the total estimate of viewership data and the data set.

Abstract: A method may include obtaining an advertising campaign, determining one or more devices associated with a consumer, and associating the one or more devices with a consumer identifier. The method also includes obtaining data associated with the one or more devices associated and corresponding the data with the consumer identifier. The method also includes deduplicating the data related to the consumer identifier across one or more viewing methods. The method also includes displaying the deduplicated data. The method also includes adjusting the advertising campaign based on user input.

Abstract: The technology relates to sequential or tailored delivery of advertising content across a plurality of media conduits. The invention achieves sequential story telling for advertising campaigns in place of single-series advertising, by delivering over a period of several sessions on a variety of devices. An advertiser can air a campaign on a consumer individual's cell phone device, continue the second portion of the campaign via a desktop browser session, and conclude with the third portion of the campaign on the individual's OTT device. The technology provides advanced controls over targeting and scheduling with high precision.

Abstract: A method includes receiving first viewership data associated with a first consumer view of an advertisement of an advertising campaign, generating a first consumer characterization based on the first viewership data, and calculating a predictive model of consumer behavior in view of the first consumer characterization and a plurality of constraints. The method also includes running a first plurality of simulations using the predictive model in a plurality of advertisement campaigns. The method also includes receiving second viewership data associated with a second consumer view of the advertisement of the advertising campaign. The method also includes generating a second consumer characterization based on the second viewership data. The method also includes updating the predictive model in view of the second consumer characterization. The method also includes providing at least one of the first consumer characterization, the second consumer characterization, or the predictive model to a user interface.

Abstract: The technology relates to sequential or tailored delivery of advertising content across a plurality of media conduits. The invention achieves sequential story telling for advertising campaigns in place of single-series advertising, by delivering over a period of several sessions on a variety of devices. An advertiser can air a campaign on a consumer individual's cell phone device, continue the second portion of the campaign via a desktop browser session, and conclude with the third portion of the campaign on the individual's OTT device. The technology provides advanced controls over targeting and scheduling with high precision.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.

Abstract: The present invention is directed to statistical methods for measuring cross-screen efficacy as it relates to advertising. The improved statistical methods provide the ability for advertisers and advertising agencies to predict the behaviors of consumers based on their aggregated cross-screen behavior. The system creates a new output that includes optimized user segments and classifications. A second part of the output is improved measurement and prediction of future consumer behaviors based on the processed multisided data on cross-screen behavior.

Abstract: The present invention is directed to statistical methods for measuring cross-screen efficacy as it relates to advertising. The improved statistical methods provide the ability for advertisers and advertising agencies to predict the behaviors of consumers based on their aggregated cross-screen behavior. The system creates a new output that includes optimized user segments and classifications. A second part of the output is improved measurement and prediction of future consumer behaviors based on the processed multisided data on cross-screen behavior.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content to consumers' TV's using a programmatic TV bidding model. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The present invention is directed to statistical methods for measuring cross-screen efficacy as it relates to advertising. The improved statistical methods provide the ability for advertisers and advertising agencies to predict the behaviors of consumers based on their aggregated cross-screen behavior. The system creates a new output that includes optimized user segments and classifications. A second part of the output is improved measurement and prediction of future consumer behaviors based on the processed multisided data on cross-screen behavior.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The present invention is directed to statistical methods for measuring cross-screen efficacy as it relates to advertising. The improved statistical methods provide the ability for advertisers and advertising agencies to predict the behaviors of consumers based on their aggregated cross-screen behavior. The system creates a new output that includes optimized user segments and classifications. A second part of the output is improved measurement and prediction of future consumer behaviors based on the processed multi-sided data on cross-screen behavior.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content to consumers' TV's using a programmatic TV bidding model. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The technology relates to sequential or tailored delivery of advertising content across a plurality of media conduits. The invention achieves sequential story telling for advertising campaigns in place of single-series advertising, by delivering over a period of several sessions on a variety of devices. An advertiser can air a campaign on a consumer individual's cell phone device, continue the second portion of the campaign via a desktop browser session, and conclude with the third portion of the campaign on the individual's OTT device. The technology provides advanced controls over targeting and scheduling with high precision.