Multi-layer caller-agent routing balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current contact center routing systems rely on random or language-preference-based methods to connect callers with agents, which do not optimize for factors like cost, revenue, or customer satisfaction, leading to suboptimal caller-agent matching.
Innovation Solution
A multi-layer processing approach that combines different models such as queue-based routing, performance-based matching, pattern matching algorithms, and affinity data matching, with a balancing mechanism to select the best caller-agent pair based on desired optimizations, and an adaptive algorithm to adjust and improve over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If round-robin routing is used to connect callers to agents, then the routing process is simple and fast, but the matching quality is poor and does not optimize for cost, revenue, or customer satisfaction
Solution Approach 1:
The routing system is divided into multiple independent computer models, each specializing in a specific matching criterion (e.g., one model for customer satisfaction, another for cost optimization). Each model processes routing decisions independently and contributes to the overall routing outcome, allowing the system to maintain speed while improving matching quality through specialized processing.
Solution Approach 2:
Multiple computer models that each excel at different aspects of caller-agent matching are combined into a single integrated routing system. The outputs of these individual models are aggregated and balanced to produce a final routing decision, thereby combining the strengths of different models to achieve both speed and high matching quality simultaneously.
2Manufacturing precision
If multiple computer models are used to optimize caller-agent matching, then the matching quality improves, but the system complexity increases
Solution Approach 1:
An intermediary balancing mechanism is introduced that receives outputs from multiple complex computer models and transforms them into a single coherent routing decision. This intermediary layer harmonizes the outputs of different models, managing the complexity by providing a unified interface that simplifies the overall system architecture while preserving the benefits of multiple specialized models.
Solution Approach 2:
The routing system is designed with multi-functional computer models that can handle multiple objectives simultaneously (e.g., optimizing for both customer satisfaction and cost reduction). This universality reduces the need for separate specialized models for each objective, thereby improving matching quality while controlling system complexity through versatile, multi-purpose components.
3Ease of operation
If conventional routing methods are used, then the system is easy to operate and maintain, but it cannot optimize for multiple objectives simultaneously
Solution Approach 1:
The routing system dynamically adjusts parameters such as weighting factors for different optimization objectives based on current contact center conditions and business priorities. By changing these parameters, the system can optimize for different combinations of objectives (e.g., prioritizing customer satisfaction during peak hours, or cost reduction during off-peak hours) without requiring complex manual reconfiguration, thereby maintaining ease of operation while enhancing adaptability.
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.