Dynamic Agent Matching System for Personalized Service
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Solution Overview
Problem
Conventional customer service systems rely on static user and agent information for matching, leading to unsatisfactory user experiences due to the lack of consideration for user personality and agent compatibility, resulting in inefficient service delivery.
Innovation Solution
A personalized agent matching system that utilizes dynamic user information and real-time data to match users with agents based on personality and value segmentation, allowing for customized service outcomes and refined user journeys through a dynamic agent selection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static user information and static agent information are used for matching, then the system complexity is reduced, but the user satisfaction and service quality deteriorate
Solution Approach 1:
The patent applies dynamics by transitioning from static user and agent information to dynamic real-time information collection. The system now gathers real-time user data (current location, device type, network conditions) and real-time agent data (availability, current workload, performance metrics) to perform dynamic matching, thereby improving user satisfaction while managing system complexity through structured data collection protocols
2Reliability
If personality-based matching is implemented, then user satisfaction improves, but the data collection and processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex matching process into distinct modules: user information collection module, agent information collection module, compatibility determination module, and matching module. Each module handles specific aspects of data collection and processing, making the overall system more manageable while enabling comprehensive personality-based matching to improve user satisfaction
3Reliability
If real-time dynamic information is collected and used for matching, then service quality and user experience improve, but the processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-collecting and storing user information profiles and agent information profiles before actual matching occurs. User profiles contain historical data, preferences, and characteristics, while agent profiles contain skill sets, availability patterns, and performance histories. This pre-processing enables faster real-time matching decisions without sacrificing service quality
Data Source
AI summary
A request is received for connecting a user with an agent, the request identifying a user interaction with content. A second server is accessed to determine a first score of the user representing a benefit the user has generated for a client that provides the content. A third server is accessed to determine a second score of the user representing overall burden to provide services to the user by the client based on an interaction history of the user with the client. A user value is dynamically determined based on the first score and the second score using a user value determination algorithm that is specifically configured for the client. A list of agent candidates is identified from a pool of agents based on the user value and the collection of real-time data. A first communication session is established between the user and one of the agent candidates.