Customized Item Self-Returns System Using Return-Trust Scores
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Solution Overview
Problem
The existing item return process is often slow, time-consuming, and burdensome for users, particularly when returning items purchased online, as it requires manual handling and can be confusing, with users often waiting for items to be received back at returns locations before receiving refunds.
Innovation Solution
A system that calculates a return-trust score for users based on their transaction history and item data, allowing for unassisted self-return authorization, which includes a calculation component analyzing item and transaction data to determine if a user can return an item without assistance, and generates real-time disposition instructions for the user, enabling quick and efficient self-return processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual item returns are processed through customer service associates at return desks, then item inspection and return authorization can be performed, but the process becomes slow, time-consuming, and burdensome for users
Solution Approach 1:
The system enables users to autonomously initiate and complete return requests through a user interface component on their user devices. Users can submit return requests, provide item information, and receive authorization decisions without requiring physical presence at return desks or interaction with customer service associates, thereby eliminating wait times while maintaining authorization accuracy through automated calculation components that evaluate return-trust scores and item return values
Solution Approach 2:
The patent replaces the mechanical manual inspection and authorization process performed by customer service associates with an automated electronic system. The calculation component automatically evaluates transaction history data, item data, and return reasons to compute return-trust scores and determine authorization decisions, substituting human manual processes with computational algorithms that operate instantaneously without physical presence requirements
2Adaptability or versatility
If online-ordered items require repackaging and mailing to returns locations, then returns can be processed, but users must wait for item receipt before receiving refunds
Solution Approach 1:
The system performs preliminary evaluation and authorization of return requests before the physical item needs to be received or processed. The calculation component computes return-trust scores and the return authorization component makes authorization decisions based on user profiles, item data, and return reasons in advance, enabling refund processing to begin before physical item receipt rather than waiting for it
Solution Approach 2:
Users can initiate and complete the entire return authorization process through their user devices without requiring physical interaction with returns locations or manual inspection. The system autonomously processes return requests, evaluates authorization criteria, and provides real-time authorization decisions, eliminating the need for users to mail items or wait for physical receipt before receiving refunds
3Ease of operation
If automated self-return systems are implemented, then user convenience and speed are improved, but system complexity and authorization accuracy requirements increase
Solution Approach 1:
The authorization system is segmented into distinct functional components: a calculation component that evaluates return-trust scores based on user profiles and transaction history, a separate component that calculates item return values based on item data and return reasons, and a return authorization component that integrates these evaluations to make authorization decisions. This segmentation allows each component to specialize in specific evaluation tasks, managing overall system complexity while maintaining high authorization accuracy
Solution Approach 2:
The system incorporates feedback mechanisms where the calculation component continuously evaluates user return behavior, transaction history, and item return patterns to dynamically update return-trust scores. This feedback loop allows the system to adapt to user behavior patterns, improving authorization accuracy over time while maintaining automated operation simplicity for users
Data Source
AI summary
Examples provide customized authorization of item self-returns. A customized returns manager component calculates a customized return-trust score and a per-item return value based on analysis of item data and transaction history data. If a per-user return-trust score is within an unacceptable threshold range or an item value is within an unacceptable threshold value range, a second user is assigned to assist a first user with completion of the proposed return of the selected item. If the per-user return-trust score and the item value is within an acceptable threshold range, a return authorization component authorizes unassisted self-return of the selected item. An item disposition component determines in real-time whether to permit the first user to keep the selected item or instruct the first user to return the selected item to a designated item return area prior to completion of the item return based on a set of item disposition criteria.