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 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 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: Within an advertising buying platform, advertising buyers are able to direct advertising content to TV/OTT/VOD inventory that matches targeted market segments. The advertising buyers select from a list of available market segments, and the system pairs the market segments to an anonymous dataset of media consumers (using a database of hashed online IDs). The dataset of hashed online IDs is then mapped to external OEM IDs (such as from a Smart TV) via the functions of a hashed identity mapping method. This permits the advertiser to target advertising content to a population of TV viewers. Also described herein are methods of bidding on programmatic TV content.

Abstract: A method includes obtaining, at a first data provider, a first query generation request. The method also includes determining whether a first query, that is to be generated based on the first query generation request, is approved. In response to a determination that the first query, that is to be generated, is approved, the method also includes generating the first query. The method further includes sharing the generated first query with a second data provider.

Abstract: Within an advertising buying platform, advertising buyers are able to direct advertising content to TV/OTT/VOD inventory that matches targeted market segments. The advertising buyers select from a list of available market segments, and the system pairs the market segments to an anonymous dataset of media consumers (using a database of hashed online IDs). The dataset of hashed online IDs is then mapped to external OEM IDs (such as from a Smart TV) via the functions of a hashed identity mapping method. This permits the advertiser to target advertising content to a population of TV viewers. Also described herein are methods of bidding on programmatic TV content.

Abstract: A method includes obtaining, at a first data provider, a first query generation request. The method also includes determining whether a first query, that is to be generated based on the first query generation request, is approved. In response to a determination that the first query, that is to be generated, is approved, the method also includes generating the first query. The method further includes sharing the generated first query with a second data provider.

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: A method may include obtaining a first data corpus and a second data corpus. The method may include correlating the first data corpus with the second data corpus. The method may include identifying a first rule and a second rule associated with performing searches. The method may include obtaining a first search query from a first data accessor to search the first data corpus and the second data corpus. The method may include validating that the first data accessor has permission to perform a search. The method may include obtaining first search results based on the first search query. The method may include validating the first search results based on the first rule and the second rule. The method may include transforming the first search results based on the first rule and the second rule. The method may include providing the transformed first search results to the first data accessor.

Abstract: Embodiments of the present disclosure may provide a data clean room allowing secure data analysis across multiple accounts, without the use of third parties. Each account may be associated with a different company or party. The data clean room may provide security functions to safeguard sensitive information. For example, the data clean room may restrict access to data in other accounts. The data clean room may also restrict which data may be used in the analysis and may restrict the output. The overlap data may be anonymized to prevent sensitive information from being revealed.

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 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: Within an advertising buying platform, advertising buyers are able to direct advertising content to TV/OTT/VOD inventory that matches targeted market segments. The advertising buyers select from a list of available market segments, and the system pairs the market segments to an anonymous dataset of media consumers (using a database of hashed online IDs). The dataset of hashed online IDs is then mapped to external OEM IDs (such as from a Smart TV) via the functions of a hashed identity mapping method. This permits the advertiser to target advertising content to a population of TV viewers. Also described herein are methods of bidding on programmatic TV content.

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.