Audience Management System for Data-Driven Media Placement
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Solution Overview
Problem
Current advertising placement methods rely on broad demographic metrics, failing to distinguish between specific target groups and efficiently reach desired audiences, leading to inefficiencies and wasted ad exposure.
Innovation Solution
An audience management system that optimizes media placement by generating a grid arrangement of cells representing advertising slots with audience data, using optimization algorithms to select and allocate budget across content sources, time periods, and programming types, allowing for precise targeting and budget allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If broad demographic metrics are used for advertising placement, then coverage of wide audience groups is improved, but precision in reaching specific target audiences deteriorates
Solution Approach 1:
The patent segments the broad demographic audience into multiple specific target audience groups based on viewing behavior patterns, device usage, and engagement metrics. This allows advertisers to target precise audience segments while still covering large portions of the population through aggregated segmentation.
Solution Approach 2:
The patent adds new dimensions to audience measurement by incorporating device-level viewing data, cross-program viewing behavior, and real-time engagement metrics alongside traditional demographic information. This multi-dimensional approach enables both broad reach and precise targeting simultaneously.
2Ease of operation
If traditional aggregate metrics are used for ad placement, then simplicity of measurement is improved, but efficiency in avoiding wasted ad exposure deteriorates
Solution Approach 1:
The patent implements real-time feedback loops that track actual viewing behavior against predicted audience composition, allowing the system to adjust and optimize ad placement decisions dynamically. This feedback mechanism maintains operational simplicity while dramatically improving advertising efficiency through continuous optimization.
Solution Approach 2:
The patent replaces manual ad placement processes with automated optimization algorithms that use machine learning to analyze viewing data and recommend or automatically select optimal ad slots. This substitution maintains ease of operation through automation while improving productivity through intelligent optimization.
3Ease of operation
If manual ad slot selection is used, then control over placement decisions is improved, but time and resources required for optimization deteriorates
Solution Approach 1:
The patent performs preliminary analysis and pre-calculates optimal ad placement strategies by analyzing historical viewing data and predicting future audience composition. This preliminary action allows the system to quickly make placement decisions without time-consuming manual optimization while maintaining advertiser control through configurable parameters.
Solution Approach 2:
The patent enables the ad placement system to automatically optimize its own decisions using built-in optimization algorithms that learn from historical data and improve over time. This self-service capability reduces the time and resources required for manual optimization while maintaining or enhancing placement control through advertiser-defined constraints.
Data Source
AI summary
System and methods are presented for providing an interface to select advertising slots in an advertising campaign. In some embodiments, a user equipment device generates for display a plurality of cells in a grid arrangement. Each cell is associated with an advertising slot corresponding to a content source and a time period, and each cell includes a representation of an audience of the associated advertising slot. The user equipment device receives a user selection of a first cell of the plurality of cells, a function is executed with respect to a first advertising slot associated with the first cell.