AI Campaign Targeting System Optimizing ROI via Data Correlation
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Solution Overview
Problem
There is a need for improvements in the communications infrastructure to enable effective creation and execution of advertising campaigns across television, mobile, and gaming platforms, specifically for managing and targeting multimedia content.
Innovation Solution
An artificially intelligent network system with subsystems for receiving and storing permissions, targeting recipients, distributing content, and confirming viewing, which includes an advertiser interface, subscriber interface, and a unique targeting system that uses data sets for optimizing advertising campaigns based on user preferences, demographic data, and return on investment parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual advertising campaign management is used across multiple platforms, then system complexity is reduced, but productivity and efficiency of campaign creation and deployment deteriorate
Solution Approach 1:
The system divides campaign management into distinct functional modules: content creation subsystem, targeting subsystem, deployment subsystem, and monitoring subsystem. Each module handles specific tasks independently, improving overall productivity while managing complexity through functional separation.
Solution Approach 2:
The patent introduces an artificial intelligence intermediary that automatically correlates user permission data with demographic data and handles campaign optimization. This AI mediator manages the complex data processing and decision-making, freeing human operators from manual complexity while maintaining high productivity.
2Measurement precision
If basic targeting methods are used, then system complexity is reduced, but measurement precision of audience targeting deteriorates
Solution Approach 1:
The system merges multiple data sources including user permission data, demographic data, historical viewing data, and trending data into a unified targeting model. This integration improves measurement precision by considering multiple factors simultaneously, while the AI system manages the complexity of combining these diverse data types.
Solution Approach 2:
The targeting system dynamically adjusts targeting parameters based on correlated data from multiple sources. The AI system modifies targeting parameters in real-time to optimize campaign performance, improving precision while the automated parameter management handles the associated complexity.
3Productivity
If automated data correlation systems are implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system implements self-service automation where the AI automatically correlates user permission data with demographic data without requiring manual intervention. The system serves itself by autonomously managing data integration, correlation, and optimization, improving productivity while the automation handles the inherent complexity.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors campaign performance and uses this information to refine data correlation algorithms. This feedback loop improves productivity by automatically optimizing based on real-world results, while the automated feedback processing manages the complexity of continuous improvement.
Data Source
AI summary
An artificially intelligent network for ad campaign design and distribution having a first subsystem for receiving and storing permission to receive targeted content; a second subsystem for selecting recipients for the content; a third subsystem responsive to the second subsystem for distributing the content; and a fourth subsystem for confirming the viewing of the content. In the illustrative embodiment, the system further includes a subsystem for creating as well as receiving the content. The system provides an artificially intelligent campaign creation and deployment system with an advertiser interface; a subscriber interface; and a targeting system for creating, deploying and monitoring an advertising campaign using inputs received via the advertiser and subscriber interfaces and a unique targeting system. The targeting system comprises first arrangement for receiving a first data set with user permissions and preference data; second arrangement for receiving a second data set based on demographic data; and third arrangement for correlating the first data set with the second data set to provide a third data set optimized with respect to at least one parameter. In an illustrative embodiment, the second arrangement further includes arrangement for receiving and factoring in historical and trending data and the parameter is return on investment.