AI Media Planning System for Cross-Screen Ad Campaigns
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Solution Overview
Problem
Existing systems struggle to develop effective advertising strategies across multiple media platforms, particularly due to the inability to track video content consumed through over-the-air broadcasts, which limits the accuracy and efficiency of ad placement.
Innovation Solution
A method and AI system that utilize datasets representing media consumption properties to develop enhanced plans for messaging across cross-screen media platforms, including both trackable and untrackable platforms, by generating audience propensity datasets, pricing datasets, and viewing datasets to create optimized media plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If advertising strategies are developed across multiple media platforms including untrackable platforms, then the coverage and reach of advertising campaigns is improved, but the measurement precision and accuracy of ad placement is worsened
Solution Approach 1:
The patent introduces an AI system as an intermediary that mediates between untrackable media platforms and measurable advertising outcomes. The system uses probabilistic models and audience propensity datasets to bridge the measurement gap, allowing advertisers to allocate budgets across untrackable platforms (like over-the-air TV) while still achieving measurable optimization through its predictive algorithms
Solution Approach 2:
The system changes the parameter of measurement from direct tracking to probabilistic prediction. By transforming the measurement approach from deterministic (direct tracking) to probabilistic (audience propensity scoring), the system enables inclusion of untrackable platforms while maintaining optimization capability through statistical modeling of advertising effectiveness
2Measurement precision
If data collection focuses on trackable devices only, then the measurement accuracy is improved, but the quantity of audience coverage is worsened due to exclusion of untrackable platforms
Solution Approach 1:
The patent segments the audience population into trackable and untrackable segments, then applies different measurement and modeling approaches to each. The AI system creates separate datasets for tracked devices and untracked devices, processes them through different methodologies, and integrates the results to achieve both accuracy for tracked segments and comprehensive coverage across all segments
Solution Approach 2:
The AI system serves multiple functions simultaneously: it acts as a measurement tool for trackable platforms and as a predictive modeling tool for untrackable platforms. This multi-functionality allows the system to maintain measurement precision where possible while extending coverage to untrackable platforms through probabilistic audience propensity modeling
3Device complexity
If traditional advertising planning methods are used without AI optimization, then the device complexity is reduced, but the productivity and effectiveness of advertising campaigns is worsened
Solution Approach 1:
The AI system performs self-service by automatically optimizing advertising budgets across media platforms without requiring complex human intervention. The system autonomously processes datasets, generates audience propensity models, and recommends budget allocations, thereby improving productivity while keeping the user interface simple and the overall system complexity manageable
Data Source
AI summary
A set of criteria for deploying an advertisement campaign to a set of audience members associated with a region are received. An audience propensity dataset associated with media platforms are received. The media platforms can include a first and second set of media platforms. Content output by the first set of media platforms can be monitorable by an organization, and content output by the second set of media platforms is not monitorable by the organization. A pricing dataset indicating pricing information associated with the first set of media platforms at the region is received. A viewing dataset indicating viewing information for the set of audience members using the first set of media platforms is received. A media plan generated based on a predicted viewership dataset, a tier dataset, and a cost dataset.