Crowdsourced Ad Campaign Funding Platform
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Solution Overview
Problem
Current crowdfunding platforms for online advertising lack efficient mechanisms for analyzing and funding ad campaigns, leading to inefficiencies in resource allocation and yield optimization, as they rely on manual processes and limited capital for traffic acquisition.
Innovation Solution
The Crowdsource and Conversational Contextual Information Injection Apparatuses, Methods, and Systems (CCCII) create a platform that crowdsources funds for ad campaigns, providing real-time yield prediction, negative return risk assessment, and commission rate optimization, enabling automated resource allocation and efficient ad buying through a marketplace that connects online merchants with third-party funders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used for analyzing and funding ad campaigns, then platform simplicity is maintained, but resource allocation efficiency and yield optimization deteriorate
Solution Approach 1:
The system enables automated self-service through AI-powered analysis that automatically evaluates ad campaigns, predicts yields, assesses risks, and reallocates funds without manual intervention. The platform serves itself by making intelligent decisions based on real-time data processing and machine learning algorithms.
Solution Approach 2:
Manual mechanical processes for campaign analysis and funding decisions are replaced with automated computational systems. The patent substitutes human manual operations with AI-driven algorithms that process data, generate predictions, and execute fund reallocation automatically, transforming a manual system into an automated intelligent system.
2Productivity
If limited capital is available for traffic acquisition, then funding risk is reduced, but campaign yield and resource utilization deteriorate
Solution Approach 1:
The system implements continuous feedback loops where AI algorithms monitor campaign performance in real-time, predict yields and risks, and automatically adjust fund allocation based on these predictions. This feedback mechanism enables dynamic optimization of capital deployment, maximizing yields while managing risks through data-driven decision-making.
Solution Approach 2:
The system performs preliminary actions by predicting campaign yields and assessing negative return risks before funds are allocated. This advance analysis allows the platform to make informed funding decisions, pre-identifying profitable campaigns and avoiding risky investments, thereby optimizing resource utilization before actual capital deployment.
3Productivity
If automated resource allocation is implemented, then yield optimization improves, but system complexity and computational requirements worsen
Solution Approach 1:
The AI-powered platform performs multiple functions within a single unified system: analyzing ad campaign data, predicting yields, assessing risks, optimizing commission rates, and reallocating funds. This multi-functional approach consolidates complex operations into an integrated system that achieves yield optimization through coordinated automated actions.
Solution Approach 2:
The patent introduces an intermediary AI system that mediates between available capital and ad campaign funding needs. This intermediary layer processes information, makes intelligent decisions, and coordinates fund allocation, thereby managing system complexity while achieving sophisticated yield optimization through centralized intelligent control.
4Measurement precision
If real-time yield prediction and risk assessment are implemented, then funding decision quality improves, but processing time and computational resources worsen
Solution Approach 1:
The system maintains continuous useful action by implementing real-time data processing and continuous yield prediction and risk assessment. The AI algorithms operate continuously, processing incoming data streams without interruption, thereby providing ongoing accurate predictions and assessments that enable timely funding decisions through uninterrupted analytical operations.
Data Source
AI summary
The Crowdsource and Conversational Contextual Information Injection Apparatuses, Methods and Systems (“CCCII”) transforms communication data, advertising link click request, campaign generation request, campaign search request, campaign investment request inputs via CCCII components into commission settlement, vendor ad campaign data, campaign search response, campaign investment confirmation, campaign control outputs. A tracking link request is obtained from a source communication channel. A match target for the contents is determined, and an attribution link is retrieved. A tracking link configured to identify the source channel and the attribution link is generated and provided to the source channel. A tracking link click request is obtained from the receiving user. The tracking link is analyzed to determine the source channel and the attribution link. A tracking cookie is placed on the receiving user's client. The attribution link is configured using the pixel drop data. The receiving user's client is redirected to the configured attribution link.