Multi-layer caller-agent routing with adaptive model weighting
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Solution Overview
Problem
Current contact center routing systems rely on random or simplistic methods to connect callers with agents, failing to optimize for desired outcomes such as cost, revenue, and customer satisfaction, and lack the ability to adaptively balance multiple routing models in real-time.
Innovation Solution
A multi-layer processing approach that combines conventional queue-based routing, performance-based matching, pattern matching algorithms, and affinity data to select the best caller-agent pair, with an adaptive algorithm to balance and weight outputs from different models, allowing for real-time adjustments and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional queue-based routing or round-robin methods are used to connect callers to agents, then the routing process is simple and fast, but the system cannot optimize for desired outcomes such as cost, revenue, and customer satisfaction
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 model) that each process routing decisions separately. These segmented models can be independently developed, maintained, and optimized while collectively providing comprehensive routing optimization capabilities.
Solution Approach 2:
Multiple routing models with different optimization focuses are merged into a unified routing system. The outputs from queue-based routing, performance-based matching, pattern matching, and affinity data models are combined through weighted aggregation to produce a final routing decision that balances multiple objectives (cost, revenue, customer satisfaction) simultaneously.
2Adaptability or versatility
If a single routing model is used, then the system is easy to manage, but it lacks the ability to adaptively balance multiple routing strategies in real-time
Solution Approach 1:
The routing system dynamically adjusts the weighting of different models in real-time based on current contact center conditions. The adaptive algorithm continuously monitors system state and modifies the contribution of each routing model (queue-based, performance-based, pattern matching, affinity data) to optimize outcomes for varying scenarios such as peak hours, agent availability, and caller characteristics.
Solution Approach 2:
The system incorporates feedback mechanisms where routing outcomes are monitored and used to adjust model weights. The adaptive algorithm receives feedback on routing performance and automatically recalibrates the weighting of different models to improve cost efficiency, revenue generation, and customer satisfaction metrics over time.
3Productivity
If multiple routing models are combined with adaptive balancing, then routing optimization is improved, but the computational complexity and processing time increase
Solution Approach 1:
Routing models perform preliminary processing and pre-calculation of matching scores before the final routing decision is required. Agent performance metrics, caller patterns, and affinity data are pre-analyzed and stored in ready-to-use formats, allowing the adaptive algorithm to quickly aggregate results without extensive real-time computation.
Solution Approach 2:
The system processes routing models in a prioritized sequence, with less critical models processed partially or skipped under time constraints. The adaptive algorithm can adjust the depth of processing for each model based on available time resources, ensuring that the most impactful models receive full processing while maintaining acceptable overall performance.
Data Source
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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.