Multi-Tier Marketplace Referral Structure for Concurrent Fee Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional electronic platforms fail to provide multi-level referral fees to intermediaries and inefficiently consume processing resources by evaluating sales one-by-one without considering multiple referral levels, leading to high computation and memory constraints.
Innovation Solution
An electronic marketplace platform that utilizes a multi-level referral data structure to concurrently determine referral fees for multiple entities involved in a transaction, conserving processing and memory resources by analyzing the data structure in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional electronic platforms evaluate sales one-by-one without considering multiple referral levels, then the transaction processing is simple, but the computation and memory resources are inefficiently consumed
Solution Approach 1:
The system pre-establishes a multi-level referral data structure that organizes all potential referral relationships and fee percentages before transactions occur. This preliminary structuring allows the system to quickly query and calculate referral fees for multiple levels simultaneously, rather than evaluating each sale sequentially without prior organization.
2Adaptability or versatility
If the platform provides multi-level referral fees to intermediaries, then the incentive structure is improved, but the device complexity increases
Solution Approach 1:
The platform segments the referral fee calculation into distinct hierarchical levels, where each level represents a different tier of intermediary. The system divides the complex multi-level referral problem into manageable segments by creating a structured data model that separates referral levels, associated entities, and fee percentages into organized components that can be processed systematically.
Solution Approach 2:
The system adds a hierarchical dimension to the referral structure by organizing intermediaries into multiple levels rather than treating all referrals equally. This dimensional organization transforms the flat, single-level referral model into a multi-dimensional hierarchy, enabling the platform to provide differentiated incentive structures while managing complexity through structured data representation.
3Productivity
If the platform calculates referral fees for multiple entities concurrently, then the productivity increases, but the measurement precision requirements increase
Solution Approach 1:
The system incorporates validation and verification mechanisms that provide feedback during the concurrent referral fee calculation process. The multi-level referral data structure includes checks to ensure accurate matching of transactions with corresponding referral levels and fee percentages, maintaining precision while enabling parallel processing across multiple entities.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Systems, methods, and apparatuses are described for determining one or more referrals associated with an electronic marketplace. Search results of a search to a user device responsive to receiving the search from the user device for a product(s) or service(s) associated with an electronic marketplace platform may be transmitted. A selection, from the user device, of a product(s) or service(s) associated with the search results may be received. A service fee(s) for a transaction(s) associated with the selected product(s) or service(s) may be determined. A referral fee(s), based on the service fee(s), responsive to determining that one or more entities referred the product(s) or service(s) associated with the transaction(s) may be determined. A level(s) assigned to each of the one or more entities and a predetermined referral fee percentage(s), based on the service fee(s), for the level(s) assigned to each of the one or more entities may be determined.