Monetization Platform for Behavioral Data Aggregation
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Solution Overview
Problem
Current Internet-based advertising techniques fail to optimally target and deliver content to mobile communication facilities due to their design for web-based search engines and lack of utilization of unique data assets from telecommunications and fixed mobile convergence networks.
Innovation Solution
A monetization platform that receives, analyzes, and delivers behavioral and other data associated with wireless subscribers to ad servers or publishers, enabling targeted advertising by linking with ad networks, publishers, and wireless operators, and facilitating conditional access and financial considerations for data use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If Internet-based advertising techniques are used for mobile communication facilities, then advertising delivery is possible, but targeting precision and advertising relevance deteriorate
Solution Approach 1:
The patent introduces a monetization platform as an intermediary system between advertisers and mobile communication facilities. This platform aggregates behavioral data from multiple sources, processes it through analysis algorithms, and delivers targeted advertising content. The intermediary resolves the contradiction by enabling precise targeting through data aggregation and processing while maintaining ease of advertising delivery through automated platform operations.
Solution Approach 2:
The patent transforms raw behavioral data into refined user profiles by applying various processing parameters including aggregation thresholds, segmentation criteria, and relevance weighting factors. These parameter changes convert undifferentiated data into precise targeting information, improving advertising relevance while maintaining delivery efficiency through automated processing.
2Measurement precision
If behavioral data from multiple sources is aggregated, then advertising targeting effectiveness improves, but system complexity increases
Solution Approach 1:
The patent combines multiple data sources including behavioral data, contextual information, and user profiles into a unified monetization platform. By merging these diverse data streams into a single integrated system, the patent achieves comprehensive targeting capabilities while managing complexity through centralized data processing and unified access protocols.
Solution Approach 2:
The monetization platform is designed as a universal system that handles multiple data types, processing methods, and advertising delivery formats through a single integrated architecture. This multi-functional design reduces overall system complexity by eliminating the need for separate processing systems for each data source or advertising format.
3Productivity
If conditional access and revenue sharing models are implemented, then monetization effectiveness improves, but transaction and access management complexity increases
Solution Approach 1:
The patent implements automated revenue sharing and conditional access management within the monetization platform. The system automatically tracks advertising impressions, calculates revenue shares based on pre-defined agreements, and manages data access permissions without manual intervention. This self-service approach improves monetization effectiveness while containing complexity through automation.
Solution Approach 2:
The platform incorporates feedback mechanisms that automatically monitor advertising performance, data usage patterns, and revenue generation. This feedback is used to dynamically adjust access conditions, revenue sharing ratios, and targeting parameters, improving monetization effectiveness while managing complexity through automated closed-loop control.
Data Source
AI summary
The present application discloses improved capabilities for aggregating user behavioral data across multiple wireless operators and delivering content to a mobile communication facility based on that aggregation, among other factors.