Adaptive Value Calculator for Online Content Payment Allocation
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Solution Overview
Problem
Current methods for compensating content providers for online content do not adequately account for a wide range of factors, actions, events, and conditions, leading to inefficiencies in revenue allocation and monetization.
Innovation Solution
A system and method using an adaptive value calculator that allocates revenue source fees based on content provider-centric, content-centric, performance-centric, and viewer-centric actions and characteristics, incorporating temporal factors to dynamically adjust payment parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If CPs are compensated based upon simple metrics like number of views or cost per impression, then the payment system is easy to operate, but it does not adequately account for a wide range of factors, actions, events and conditions
Solution Approach 1:
The payment system segments the compensation calculation into multiple independent components: base payment (CPI/CPC/CPO), performance multipliers (engagement metrics, retention rates), temporal factors (posting timing, publishing duration), and external conditions (market trends, seasonal adjustments). Each segment is calculated separately and then combined to determine the final payment, allowing complex compensation to be managed through modular, manageable components.
Solution Approach 2:
The system implements dynamic payment parameters that adjust in real-time based on changing conditions. Payment rates are not fixed but evolve based on content performance over time, viewer engagement patterns, and market conditions. The system continuously updates compensation metrics during the content publishing period, transforming static payment models into adaptive, responsive systems that reflect current value delivery.
2Measurement precision
If the payment system accounts for multiple factors including CP centric, content centric, performance centric and viewer centric actions, then the compensation accuracy is improved, but the device complexity increases
Solution Approach 1:
The payment processor is designed as a multi-functional system that simultaneously handles diverse payment models (CPI, CPC, CPO), multiple content types, various engagement metrics, and different temporal calculations through a single integrated platform. This universal system replaces multiple specialized tools, reducing overall ecosystem complexity while maintaining comprehensive measurement capabilities across all content and provider types.
Solution Approach 2:
The system introduces intermediary calculation layers and standardized metrics that bridge between raw data collection and final payment determination. Rather than directly processing all possible factors, the system uses intermediate aggregation steps, normalized performance indicators, and standardized weighting schemes to simplify the transition from complex multi-factor input to actionable payment outputs, reducing computational and operational complexity.
3Reliability
If revenue allocation is based on predetermined formulas, then the system is stable and reliable, but it cannot adapt to internal and external changed conditions during the content publishing period
Solution Approach 1:
The system implements periodic recalculation of payment allocations at defined intervals during the content publishing lifecycle (e.g., daily, weekly, or at milestone events). This periodic action maintains system reliability through structured, predictable updates while enabling adaptation to changing conditions by systematically incorporating new performance data and market information at each calculation cycle, balancing stability with responsiveness.
Solution Approach 2:
The payment system incorporates feedback loops where actual content performance data, viewer engagement metrics, and market response information continuously flow back into the calculation model. This feedback mechanism allows the system to learn from actual outcomes and adjust future payment allocations accordingly, maintaining reliability through systematic processing while achieving adaptability through data-driven adjustments that respond to real-world conditions.
Data Source
AI summary
The invention calculates, allocates and pays a Content-Provider-CP for online content with an adaptive value calculator, a payment processor computer, memory and associated web-server. The CP allocation in one system is based upon User-CP centric actions or characteristics (A-C); Content centric A-C; Content Performance centric characteristics; and Viewer centric A-C. A compiler registers Users-CPs. An uploader delivers CP content to the web-server. A tracking module monitors views and acclamations on uploaded content. A revenue tracker accounts for revenue sources on the web-server. An allocation processor calculates CP payments. Metric examples are: CP centric (famous CP or frequent CP poster); Content centric (geographically relevant or trending topic); Performance centric (views on published content); Viewer centric (comments by famous critic). A payment module pays the CP through a banking system. Metrics are time-based temporal functions.