Returns Frequency Index for E-Commerce Visibility Control
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Solution Overview
Problem
E-commerce sellers face significant resource constraints due to chronic returners who frequently return items, leading to increased costs and inefficiencies in restocking and refunding processes, particularly for small retailers.
Innovation Solution
A returns frequency index is calculated based on a buyer's transaction history, allowing sellers to restrict item listing visibility to buyers with a high returns frequency, thereby minimizing the risk of item returns. This index is generated using metrics such as the total number and value of items returned versus purchased, and sellers can configure thresholds to determine visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If item listings are made visible to all users, then user accessibility and browsing experience are improved, but sellers face increased resource consumption and financial losses due to frequent returns by chronic returners
Solution Approach 1:
The system performs preliminary assessment of user return behavior by calculating a returns frequency index before allowing access to item listings. Users are pre-evaluated based on their transaction history, and those with high returns frequency indices are restricted from viewing listings, preventing resource waste before it occurs.
Solution Approach 2:
The returns frequency index serves as an intermediary mechanism between sellers and buyers. Instead of direct interaction or manual screening, the system uses this calculated index as a mediator to automatically determine listing visibility, reducing the burden on sellers while maintaining control over resource allocation.
2Reliability
If sellers manually screen buyers to prevent returns, then return prevention is improved, but seller workload and operational complexity increase significantly
Solution Approach 1:
The system enables self-service by automatically calculating and applying returns frequency indices without requiring seller intervention. The platform autonomously monitors transaction histories, computes risk indices, and manages listing visibility, freeing sellers from manual screening tasks while maintaining reliable return prevention.
Solution Approach 2:
The patent replaces the mechanical manual screening process with an automated computational system. Instead of sellers manually reviewing buyer histories, the system uses algorithmic calculation of returns frequency indices to automatically determine access rights, reducing operational complexity while maintaining effectiveness.
3Loss of energy
If chronic returners are blocked from viewing listings, then seller resource protection is improved, but user experience and fair treatment of legitimate buyers deteriorate
Solution Approach 1:
The system changes the parameter of listing visibility based on the returns frequency index. By dynamically adjusting this parameter according to calculated user behavior metrics, the system protects seller resources from chronic returners while maintaining normal access for legitimate buyers with low return indices, thus balancing protection with fair treatment.
Data Source
AI summary
A system and method of determining whether to make an item listing visible to a user are disclosed. A user is enabled to navigate an e-commerce site. A returns frequency index is calculated for the user based on the user's transaction history. The user's transaction history includes the user's history of item returns. It is determined whether or not to make an item listing visible to the user on the e-commerce site based on the returns frequency index for the user. In some embodiments, the returns frequency index is calculated using the mathematical expression (VRet/NRet)/(VPurch/NPurch), wherein VRet is a total value of items returned by the user, NRet is a total number of items returned by the user, VPurch is a total value of items purchased by the user, and NPurch is a total number of items purchased by the user.