Multi-Layer Caller-Agent Matching in Contact Center Routing
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Solution Overview
Problem
Conventional contact center routing systems rely on random or language-preference-based methods to connect callers with agents, which do not optimize for performance, cost, revenue, or customer satisfaction, leading to suboptimal caller-agent matching.
Innovation Solution
A multi-layer processing approach is implemented, using two or more models such as queue-based routing, performance-based matching, pattern matching algorithms, and affinity data matching, with a balancing layer to weight and select the best caller-agent pair for routing, potentially aided by adaptive algorithms like neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional random or language-preference-based routing methods are used, then the routing system is simple to operate, but caller-agent matching quality deteriorates
Solution Approach 1:
The routing system is divided into multiple independent models (queue-based routing model, performance-based matching model, pattern matching model, affinity data matching model), each handling specific matching aspects. This segmentation allows each model to specialize in particular matching criteria while maintaining overall system manageability and operational simplicity.
Solution Approach 2:
The patent combines multiple different routing models into a composite routing system that integrates queue-based routing, performance-based matching, pattern matching, and affinity data matching. This composite approach leverages the strengths of each individual model to achieve superior caller-agent matching quality while distributing system complexity across modular components.
2Measurement precision
If multiple computer models are used for matching, then caller-agent matching quality improves, but processing complexity increases
Solution Approach 1:
The processing architecture is segmented into distinct models that can operate independently and concurrently. Each model (queue-based, performance-based, pattern matching, affinity data) processes matching criteria separately, allowing for optimized individual processing paths while maintaining high overall matching accuracy through the aggregation of multiple specialized processing streams.
3Productivity
If conventional routing methods are used, then processing time is short, but caller等待 time increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and maintaining queue positions, performance metrics, and affinity data for agents before actual routing decisions are needed. This allows the multi-model matching process to operate more efficiently during actual routing events, reducing both processing time and caller waiting time while maintaining high routing efficiency.
Data Source
AI summary
Systems and methods are disclosed for routing callers to agents in a contact center utilizing a multi-layer processing approach to matching a caller to an agent. A first layer of processing may include two or more different computer models or methods for scoring or determining caller-agent pairs in a routing center. The output of the first layer may be received by a second layer of processing for balancing or weighting the outputs and selecting a final caller-agent match. The two or more methods may include conventional queue based routing, performance based routing, pattern matching algorithms, affinity matching, and the like. The output or scores of the two or more methods may be processed be the second layer of processing to select a caller-agent pair and cause the caller to be routed to a particular agent.