Method and artificial intelligence system for developing enhanced plans related to messaging across cross-screen media platforms

An apparatus, comprising:

• a memory;
• and
• a processor operatively coupled to the memory, the processor configured to:
• generate, based on an audience dataset indicating a set of attributes associated with a set of audience members and a set of weights, a predicted viewership dataset indicating predicted media viewership information of an advertisement campaign for the set of audience members:
• generate a tier dataset based on at least one of (1) an audience propensity dataset, (2) the predicted viewership dataset, (3) a trackable viewing dataset, or (4) a first digital campaign dataset previously collected from a first plurality of devices associated with at least one first media platform from a plurality of media platforms, and
• for each media platform from the plurality of media platforms, the tier dataset indicating a tier of media consumption for that media platform for each audience member from the set of audience members:
• generate, based on a second digital campaign dataset previously collected from a second plurality of devices associated with at least one second media platform from the plurality of media platforms, a cost dataset indicating a set of costs associated with deploying the advertisement campaign in accordance with at least one criterion from a set of criteria:
• generate a media plan for deploying the advertisement campaign to the set of audience members based on the predicted viewership dataset, the tier dataset, and the cost dataset.

A non-transitory processor-readable medium storing code representing instructions to be executed by one or more processors, the instructions comprising code to cause the one or more processors to:

• generate, based on an audience propensity dataset, an audience dataset indicating a set of attributes associated with a set of audience members:
• generate a set of weights (1) based on the audience propensity dataset and a viewing dataset and (2) to counter sample bias associated with the viewing dataset:
• generate, based on at least one of the audience dataset or the set of weights, a predicted viewership dataset indicating predicted media viewership information of an advertisement campaign for the set of audience members:
• generate a tier dataset based on at least one of (1) the audience propensity dataset, (2) the predicted viewership dataset, (3) the viewing dataset, or (4) a first digital campaign dataset previously collected from a first plurality of devices associated with at least one first media platform from a plurality of media platforms, and
• for each media platform from the plurality of media platforms, the tier dataset indicating a tier of media consumption for that media platform for at least one audience member from the set of audience members:
• generate, based on a second digital campaign dataset collected from a second plurality of devices associated with at least one second media platform from the plurality of media platforms, a cost dataset indicating a set of costs associated with deploying the advertisement campaign in accordance with at least one criterion:
• and
• generate a media plan for deploying the advertisement campaign to the set of audience members based on at least one of the predicted viewership dataset, the tier dataset, or the cost dataset, the media plan including a set of budget recommendations for the plurality of media platforms.