Online Reward System for Ad Revenue Sharing
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Solution Overview
Problem
Current online advertising systems fail to effectively incentivize both advertisers and users to engage with individually designed advertisements, as users have no control over external content and its relevance to their audience, leading to suboptimal ad effectiveness.
Innovation Solution
An online reward system that divides advertising revenue into two funds: the Advertisers' Compensation Fund and the Users' Compensation Fund, where advertisers are paid based on ad views and users are compensated for their interactions with ads, such as likes and shares, to incentivize sharing and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service providers control and manage external advertising content on sharing platforms, then the service provider can monetize user content sharing, but users have no control over the external content being presented alongside their selected user content, reducing ad effectiveness
Solution Approach 1:
The system segments the advertising content selection process by allowing users to individually select and control which advertisements appear alongside their content, rather than having service providers unilaterally control all external content. This segmentation empowers users to curate their own ad experiences while maintaining platform monetization.
Solution Approach 2:
The system implements feedback mechanisms where users can provide input about ad relevance and effectiveness, which then informs future ad selection and placement decisions. This feedback loop enables continuous improvement of ad effectiveness while respecting user preferences and control.
2Productivity
If users are compensated for sharing and engaging with advertisements, then user motivation to promote ads increases, but the system complexity for tracking and distributing compensation increases
Solution Approach 1:
The system employs a universal compensation mechanism that handles multiple types of user actions (sharing, liking, commenting) through a unified reward structure. This multi-functional approach simplifies tracking by consolidating various engagement metrics into a single compensation framework rather than requiring separate tracking systems for each action type.
Solution Approach 2:
The compensation system is designed to automatically track user engagements and distribute rewards without requiring manual intervention. The system self-monitors ad interactions, calculates compensation amounts, and distributes payments, reducing operational complexity while maintaining accurate tracking of user contributions.
3Productivity
If advertisers host ads on user platforms, then advertisers can reach targeted audiences, but users receive no direct benefit from the advertising revenue generated
Solution Approach 1:
The system establishes a feedback loop where a portion of advertising revenue is directly returned to users through compensation mechanisms. This feedback ensures that users who generate revenue through their platforms and content sharing receive direct financial benefits, creating a sustainable ecosystem where all participants gain value.
Solution Approach 2:
Users are empowered to directly benefit from ad revenue through automated compensation systems that track their contributions and distribute payments without requiring manual claims or complex redemption processes. The system self-manages the revenue sharing, ensuring users receive their entitled benefits seamlessly.
Data Source
AI summary
The present system provides users engaging with sharing platforms a method to monetize their contribution in generating ad revenue for various advertisers. The system can quantify the user contribution based on the user's behavior and action related to individual ads on the sharing platforms. The system provides a method of monetizing a user's contribution to ad revenue, thereby incentivizing users to share the selected ad to the user's audience.