AI Procurement Inquiry Management for Mixed Merchant Responses
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Solution Overview
Problem
Class B buyers in cross-border e-commerce face inefficiencies and high labor and time costs in managing procurement demands due to the need to manually compare and sort responses from multiple merchants, as existing systems lack the ability to aggregate and analyze procurement demand information effectively.
Innovation Solution
A method utilizing an AI big model to aggregate and display responses from multiple merchants, provide conversational assistance, and perform multi-dimensional comparisons, reducing the need for manual sorting and improving communication efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a Class B buyer sends inquiries to multiple merchants for procurement demands, then the buyer can compare and choose from multiple merchants, but the buyer needs to manually sort and analyze response information from multiple merchants, which requires a lot of manpower and time costs
Solution Approach 1:
The patent introduces an AI assistant as an intermediary between the buyer and multiple merchants. The AI assistant automatically receives, sorts, and analyzes response information from multiple merchants, acting as a mediator that processes information without requiring manual intervention from the buyer. This resolves the contradiction by maintaining the ability to compare multiple merchants while eliminating the time-consuming manual sorting process.
Solution Approach 2:
The AI assistant performs self-service by automatically processing, sorting, and analyzing procurement demand response information from multiple merchants. The system autonomously identifies relevant information, groups responses by procurement demand, and presents consolidated results to the buyer, eliminating the need for manual information processing while maintaining comprehensive comparison capabilities.
2Quantity of substance
If the same buyer has multiple different procurement demands and inquires to multiple merchants for each, then the buyer can obtain comprehensive quotations, but all reply information will be mixed in the same message list requiring manual sorting
Solution Approach 1:
The patent segments the mixed message list into distinct sections based on procurement demand identifiers. The AI assistant automatically groups all responses by their associated procurement demand, creating organized segments that separate different procurement demands even though they come from the same message list. This resolves the contradiction by maintaining comprehensive coverage of multiple procurement demands while making information organization automatic and easy.
Solution Approach 2:
The AI assistant serves as an intermediary that automatically sorts and organizes mixed response information from multiple merchants across different procurement demands. The system identifies and separates responses by procurement demand identifier, presenting them in an organized manner that maintains comprehensive coverage while eliminating manual sorting requirements.
3Loss of information
If the buyer manually clicks to view details of each message one by one, then the buyer can review all response contents, but the process requires a lot of manpower and time costs
Solution Approach 1:
The AI assistant performs self-service by automatically retrieving, viewing, and analyzing all response contents from multiple merchants. The system autonomously processes the complete information set, identifying and extracting relevant details without requiring manual intervention. This resolves the contradiction by maintaining complete information review while dramatically improving processing productivity through automated AI assistance.
Solution Approach 2:
The patent replaces the mechanical manual process of clicking through messages one by one with an automated AI-based information processing system. The AI assistant uses natural language processing and automated analysis to review all response contents, substituting the mechanical manual review process with intelligent automation that maintains completeness while significantly improving productivity.
Data Source
AI summary
A method for managing procurement demand information and an electronic device are provided. The method includes: determining procurement demands created by a first user; obtaining response contents of multiple second users' replies and determining corresponding procurement demand identifiers after the first user initiates an inquiry message to the multiple second users based on the procurement demands; performing an aggregated display of response contents of a plurality of second users' replies corresponding to a same procurement demand in response to a request submitted by the first user to view a response status of the procurement demand. Using the method in the present disclosure, the efficiency can be improved, and the labor and time costs can be reduced.