Service Call Routing via Customer-Agent Attribute Matching
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Solution Overview
Problem
Conventional contact center routing methods, such as 'round-robin' approaches, often fail to provide a high-quality customer experience as they do not consider individual customer needs or agent capabilities, leading to inefficient service delivery.
Innovation Solution
A method that collects and analyzes data on customer service experiences to select the most suitable agent based on attributes such as language skills, educational level, and past interactions, ensuring that incoming customer requests are routed to agents who can best meet their needs.
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 customer service quality deteriorates because individual customer needs and agent capabilities are not considered
Solution Approach 1:
The patent changes the routing parameters from simple round-robin selection to attribute-based matching. The system analyzes customer attributes (language, education level, technical knowledge) and agent attributes (language skills, expertise areas, certification levels) to dynamically select the optimal agent, transforming the routing decision from a static algorithm to a dynamic parameter-matching process
Solution Approach 2:
The system performs preliminary analysis of customer attributes and call nature before routing occurs. By pre-processing customer data (language preferences, education level, technical knowledge) and comparing it against agent capabilities in advance, the system prepares the optimal routing decision before the actual call connection, ensuring both speed and quality
2Reliability
If data collection and analysis on customer service experiences is implemented, then the quality of service interactions improves, but the system complexity increases
Solution Approach 1:
The patent creates a multi-functional analytics engine that performs multiple functions: collecting customer feedback data, analyzing service interaction quality, identifying patterns in customer experiences, and generating routing recommendations. This single unified system handles diverse tasks that would otherwise require separate systems, managing complexity through functional integration
Solution Approach 2:
The analytics engine acts as an intermediary layer between the existing contact center operations and the routing system. It collects data from various sources, processes this information through analysis, and provides refined routing recommendations to the routing engine, mediating between raw data and routing decisions without requiring complete system restructuring
Data Source
AI summary
A method for routing customer service requests to call centers includes collecting data associated with customer service experience between a customer and a call center regarding a completed customer call. The collected data is analyzed to determine a quality of customer service for one or more completed calls between the customer and the call center. A nature of an incoming customer call is determined. The incoming customer call is routed to a call center based upon making reference to the analyzed collected data such that the nature of the customer call matches with corresponding one or more favorable attributes of the call center.