Predictive Programmatic Audience Analysis for Non-Addressable Delivery
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Solution Overview
Problem
Existing communications networks face limitations in delivering targeted advertisements due to non-addressable environments, equipment constraints, bandwidth limitations, and reliance on incomplete ratings information, leading to inefficient ad targeting and limited audience analytics.
Innovation Solution
Utilize resources from addressable asset delivery systems to enhance audience analytics and targeting in non-addressable contexts by leveraging audience classification, voting, reporting, and conversion data to optimize asset delivery opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If addressable advertising is implemented, then targeting precision is improved, but device complexity and network infrastructure requirements increase
Solution Approach 1:
The patent segments the advertising system into addressable and non-addressable components. By classifying advertising opportunities into segments based on addressability capabilities, the system enables precise targeting where infrastructure exists while maintaining simplicity in areas where it does not, thus resolving the contradiction between targeting precision and device complexity
Solution Approach 2:
The system creates a universal advertising platform that can operate in both addressable and non-addressable modes. The same core infrastructure supports multiple functionality levels, allowing networks to implement targeted advertising without requiring all devices to be complex addressable units, thereby improving targeting precision while limiting the increase in device complexity
2Loss of information
If addressable advertising is implemented, then audience analytics quality is improved, but bandwidth consumption and network load increase
Solution Approach 1:
The patent extracts and separates the analytics collection function from the advertising delivery function. By using independent analytics mechanisms that operate parallel to the advertising system, the platform can gather high-quality audience information without proportionally increasing bandwidth consumption for ad delivery itself
Solution Approach 2:
The system implements analytics collection at appropriate levels without excessive overhead. By collecting only the necessary audience metrics needed for effective targeting and analytics rather than comprehensive data, the system improves audience analytics quality while controlling bandwidth consumption to reasonable levels
3Productivity
If fine-grained audience classification is implemented, then ad targeting effectiveness is improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent segments audience classification into hierarchical levels, implementing fine-grained classification only where needed and sufficient coarser classification elsewhere. This segmentation enables effective ad targeting by providing detailed audience segments for addressable advertising while using simpler classification for non-addressable contexts, thus improving productivity without proportionally increasing system complexity
Solution Approach 2:
The system applies different levels of classification quality to different contexts and locations in the advertising ecosystem. Fine-grained classification is applied locally where addressable infrastructure exists and where it provides maximum value, while simpler classification is used in other areas, optimizing ad targeting effectiveness while managing system complexity
4Measurement precision
If comprehensive audience tracking is implemented, then conversion measurement accuracy is improved, but privacy concerns and user resistance increase
Solution Approach 1:
The patent implements partial tracking that collects sufficient data for conversion measurement without excessive monitoring. By gathering only the specific metrics needed for accurate conversion measurement rather than comprehensive behavioral tracking, the system improves measurement precision while minimizing privacy concerns and user resistance
Solution Approach 2:
The system incorporates feedback mechanisms that allow users to control their tracking participation. By providing users with feedback about what is being tracked and options to opt-in or opt-out, the platform achieves improved conversion measurement accuracy through voluntary participation while reducing privacy concerns and resistance
Data Source
AI summary
A predictive programmatic system (100) uses an addressable asset delivery system to provide audience information for non-addressable asset delivery opportunities. The illustrated system (100) is implemented in connection with an addressable asset delivery system (102) deployed, for example, in a cable or satellite television network. The addressable asset delivery system (102) is used to address assets to user devices 104 of a communications network. An asset provider may request dissemination of an asset over the communications network via a contracting platform (106). A targeting module (108) is operative for accessing audience information (110) and providing targeting information to the contracting platform (106). The audience information (110) may be developed by obtaining information regarding the audiences for addressable asset delivery opportunities and associated level of interest and conversion information, and the targeting module (108) may use information to characterize overall audiences for non-addressable asset delivery opportunities. This information can be provided to the contracting platform (106) to assist asset providers in identifying non-addressable asset delivery opportunities for specific assets of the asset providers.