Predictive Routing System for Contact Center Agent Matching
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Solution Overview
Problem
Current call-routing systems in contact centers often fail to efficiently connect callers to agents with the necessary expertise, leading to increased on-hold times and reduced customer satisfaction due to the use of first-in/first-out techniques, which do not account for agent specialization or customer personality types.
Innovation Solution
A system that predicts customer personality types based on identifying origination data and matches incoming communications with available agents who have the proficiency to handle those types, while excluding agents who have exceeded their work threshold, using a database module to associate customer data with personality predictions and a routing module to optimize agent allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If first-in/first-out routing technique is used, then calls are routed to the next available agent in order, but callers may be routed to agents without specialized knowledge leading to increased on-hold times and reduced customer satisfaction
Solution Approach 1:
The system changes the routing parameter from simple availability status to a composite parameter that includes agent expertise matching with customer issue type. The automatic call distributor evaluates multiple parameters simultaneously (agent skills, customer problem category, current workload) to determine optimal routing, transforming the single-dimensional first-in/first-out approach into a multi-dimensional decision process that reduces on-hold time by connecting customers more quickly to appropriately skilled agents.
Solution Approach 2:
The system applies local quality by matching specific agent expertise to specific customer needs. Rather than treating all agents uniformly, the system identifies and routes customers with specialized issues to agents with corresponding specialized knowledge. This localized matching ensures that customers receive appropriate expertise while maintaining overall system efficiency, directly addressing the problem of customers being routed to unprepared agents.
2Ease of operation
If calls are routed based on agent availability only, then routing is simple and fast, but customer satisfaction decreases due to mismatched expertise
Solution Approach 1:
The automatic call distributor is designed with multi-functionality, serving both as a simple availability-based router and as an expertise-matching system. The system universally handles different types of calls (routine inquiries, specialized technical issues, complaints) through a single platform that automatically selects the appropriate routing strategy based on call characteristics, maintaining ease of operation while improving customer satisfaction through intelligent matching.
Solution Approach 2:
The system introduces an intermediary intelligence layer between the customer call and the agent selection process. This intermediary automatically evaluates both agent availability and expertise alignment, mediating between the simplicity requirement and the reliability requirement. The intermediary performs rapid assessments of multiple factors and makes routing decisions that balance operational simplicity with customer satisfaction, eliminating the need for complex manual routing while ensuring appropriate expertise matching.
Data Source
AI summary
The methods, apparatus, and systems described herein are designed to route customer communications to the best agent or best available agent. The methods include identifying origination data for a customer contacting a contact center with a customer task, determining a predicted personality type of the customer based on the identified origination data and a customer profile, providing a routing recommendation to a communication distributor to route the customer to an agent based on the predicted personality type of the customer and historical customer data, routing the customer via the communication distributor to the agent based on the routing recommendation, and updating the customer profile.