Chat Software Agent for Ecommerce via Group Graphs
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Solution Overview
Problem
Businesses have not effectively utilized group discussions in chat messaging for promoting goods and services or leveraged contextual information to influence purchasing decisions, missing opportunities to connect merchants with potential buyers.
Innovation Solution
A computer-implemented method using software agents to assist chat groups in finding suitable goods and services by creating User Graphs and Group Graphs, allowing users to search, select, and share products or services within the chat conversation, with a consumer-oriented software agent that predicts user needs and preferences using Simple Knowledge Graph Notation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If businesses use traditional referral methods with individual associates marketing products on their websites, then customers can be directed to merchant websites through referral links, but the system does not leverage group discussions or contextual information from chat messaging to identify purchasing opportunities
Solution Approach 1:
The patent introduces software agents as intermediaries that monitor chat groups and analyze contextual information. These agents act as mediators between users' casual conversations and the e-commerce system, automatically identifying purchasing opportunities from group discussions without requiring users to manually search or share product information. The agent translates natural language chat content into actionable e-commerce referrals.
Solution Approach 2:
The system enables self-service by allowing the software agent to autonomously perform tasks including monitoring chat groups, analyzing contextual information, identifying purchasing opportunities, selecting relevant products, and injecting referral links into conversations. The agent operates independently without requiring direct user intervention, automatically leveraging group dynamics and contextual cues to drive e-commerce referrals.
2Productivity
If users manually search for products, review results, select items, and share them in chat conversations, then product recommendations can be provided, but this process requires significant user effort and time
Solution Approach 1:
The software agent performs preliminary actions by continuously monitoring chat groups and pre-identifying purchasing opportunities based on contextual analysis of user conversations. Before users even express explicit purchase intent, the agent has already analyzed the discussion, identified relevant products, and prepared referral links, so that when a purchasing opportunity is detected, the recommendation can be immediately injected into the conversation without requiring users to manually search or spend time finding products.
3Measurement precision
If software agents automatically monitor and analyze chat groups to identify purchasing opportunities, then targeted product recommendations can be provided, but the system requires sophisticated analysis capabilities
Solution Approach 1:
The software agent applies local quality by focusing its sophisticated analysis capabilities on specific, localized aspects of chat conversations rather than attempting to analyze everything. It monitors for specific contextual cues, keywords, and discussion patterns that indicate purchasing opportunities, applying advanced natural language processing only where relevant. This allows the system to achieve high measurement precision in identifying purchasing opportunities while managing complexity by concentrating analytical resources on critical moments in conversations.
Data Source
AI summary
A computer-implemented method of using the Internet to promote goods and services and connect merchants with potential purchasers in chat groups who wish to obtain suitable sources of goods and services is provided, wherein a plurality of users each have a computer device provided with chat application software and software for accessing and interactively communicating via a computer network with a server provided with a search engine for searching the Internet. Users initiate a chat conversation among a group of users. One of the users invokes a search application using the search engine. The user conducts a search of the Internet for products or services, reviews the results of the search, selects a product or service located by the search, and shares the selected search result with the chat conversation. One of the users can order the selected product or service as part of the process.