Agent Routing Rules Using Historical Data to Balance Contact Center Queues
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Solution Overview
Problem
Existing contact center routing systems inefficiently utilize agent resources by segregating agents into queues based on call topics, leading to idle agents in non-busy queues while busy queues remain overwhelmed.
Innovation Solution
An agent routing platform uses historical call data and customer satisfaction metrics to recommend rules for routing calls based on customer categories, considering agent attributes and performance metrics, and adjusts routing based on industry-specific factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If agents are segregated into different queues based on call topics, then call routing becomes simpler and more organized, but agent resource utilization becomes inefficient
Solution Approach 1:
The patent implements universal agent queues where agents can handle multiple types of calls across different customer categories. Instead of dedicated queues for each call topic, agents are assigned to queues based on their skills and availability, allowing them to serve multiple functions and handle various customer needs, thereby improving resource utilization while maintaining organized routing
2Measurement precision
If dedicated queues are used for each customer category, then call routing precision is improved, but wait times increase when queues are full
Solution Approach 1:
The patent implements dynamic routing rules that adapt based on real-time queue status, agent availability, and customer characteristics. When a dedicated queue is full or no agent is available, the system dynamically redirects calls to alternative queues with available agents, balancing routing precision with wait time reduction through flexible, real-time decision-making
Solution Approach 2:
The patent introduces a routing rule engine as an intermediary layer between call intake and agent assignment. This engine evaluates multiple factors including queue status, agent skills, customer category, and historical performance to determine optimal routing decisions, enabling the system to balance precise routing with efficient wait time management through intelligent mediation
3Adaptability or versatility
If manual rule creation is used for routing, then company control over routing logic is maintained, but system complexity increases
Solution Approach 1:
The patent implements self-service routing rule generation where the system automatically creates routing rules by analyzing historical call data, customer satisfaction metrics, and agent performance information. The system can generate, optimize, and adjust routing rules autonomously based on learned patterns, reducing the need for manual rule creation while maintaining adaptability through data-driven insights
Data Source
AI summary
In one embodiment, an entity such as a company may desire to use agents associated with a contact center to handle calls for the company. The company may identify customer categories for the calls such as technical support and billing. Rather than have the company create the rules that are used to select agents to handle calls for each category, the contact center may use historical call data, such as performance metrics and customer satisfaction survey information, to recommend rules to the company for each category. The recommended rules may also be based on the specific industry, field, or sector associated with the company.