Return Rate Feedback for Online Product Selection
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Solution Overview
Problem
Online shopping experiences higher return rates due to consumers' inability to physically interact with products before purchase, leading to issues like fit, size, color, and style mismatches, which result in increased returns and dissatisfaction.
Innovation Solution
Electronic devices equipped with a return reduction module that provides real-time return rate information and alternative product recommendations based on user preferences and previous consumer data, helping guide purchasing decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If online shopping is used to allow consumers to purchase goods using electronic devices, then convenience and accessibility are improved, but return rates increase due to inability to physically interact with products
Solution Approach 1:
The system performs preliminary actions by providing return rate information and alternative product recommendations before the consumer completes the purchase. This allows consumers to make more informed decisions about whether to proceed with the purchase, potentially reducing returns while maintaining online shopping convenience.
Solution Approach 2:
The system implements feedback by displaying return rate information based on previous consumer behavior data. This feedback loop provides consumers with relevant information about product return probabilities, enabling them to adjust their purchasing decisions accordingly and reducing overall return rates.
2Loss of information
If return rate information is provided to consumers during online shopping, then consumer decision-making is improved, but system complexity increases due to data processing requirements
Solution Approach 1:
The system extracts only the most relevant information (return rates and alternative recommendations) from complex consumer data and presents it in a simplified format to consumers. This extraction approach provides necessary information without requiring the consumer-facing system to handle the full complexity of data processing.
Solution Approach 2:
The system acts as an intermediary between complex consumer behavior data and the consumer. It processes and translates raw return data into meaningful return rate percentages and alternative product suggestions, reducing the information complexity presented to consumers while maintaining data completeness.
Data Source
AI summary
An electronic device, a method and a computer program product for reducing incidents of returns of purchased/requested items. The method includes detecting a trigger indicative of an item review context that includes a first item which was previously acquired by a previous consumer. In response to detecting the trigger, the method includes retrieving customer return data corresponding to the first item and retrieving user preferences profile data correlated to acquiring items within a merchandise category. The method includes determining if the customer return data indicates that the first item has a first return rate within a demographic of previous consumers having similar profiles. In response to the first item having the first return rate, the method includes outputting an indication or message concurrently with presenting the first item for review or selection. The first message indicates the first return rate of the first item.