Contact Center Routing Interval for Batch Agent Matching
Solution Overview
Problem
Conventional contact center routing systems face inefficiencies when matching incoming customer interactions with available agents, particularly when multiple interactions and agents are available simultaneously, limiting the effectiveness of ranking algorithms and impacting performance and customer satisfaction.
Innovation Solution
Implementing a computer-implemented method that introduces a routing interval where incoming interactions and available agents accumulate before being routed, allowing for batch processing and optimizing agent-customer pairings using predictive algorithms that consider interaction and agent characteristics to maximize key performance indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If immediate routing is performed for each incoming interaction, then response time is reduced, but routing effectiveness and customer satisfaction deteriorate due to limited ranking algorithm performance
Solution Approach 1:
The system accumulates incoming interactions and available agents in batches before routing, performing preliminary gathering of data to enable more effective ranking algorithm execution. This preliminary batching action allows the system to process multiple interactions simultaneously with comprehensive agent-interaction matching, improving routing effectiveness while maintaining acceptable response times through optimized batch processing intervals.
2Reliability
If batch processing with routing interval is implemented, then routing effectiveness is improved, but response time increases
Solution Approach 1:
The system dynamically adjusts the routing interval based on real-time conditions such as interaction volume, agent availability, and queue depth. This dynamic adjustment allows the batch size and timing to be optimized continuously, ensuring that routing effectiveness is improved through batch processing while response time is kept minimal by adapting the interval to current system state and workload characteristics.
3Measurement precision
If multiple interactions are processed simultaneously in batches, then agent-interaction matching quality is improved, but system complexity increases
Solution Approach 1:
The system segments the batch processing into distinct phases: interaction accumulation, agent availability assessment, ranking algorithm execution, and routing execution. This segmentation of the batch processing workflow into manageable stages reduces system complexity by organizing complex operations into discrete, manageable steps while still achieving high-quality agent-interaction matching through comprehensive batch evaluation.
Data Source
AI summary
A method for routing incoming interactions in a contact center. The incoming interactions are instigated by customers for communicating with the contact center, and the contact center includes agents between which the incoming interactions are routed. The method includes: determining a routing interval; identifying received incoming interactions for inclusion in a received interactions batch, each of the received incoming interactions being identified as ones of the incoming interactions that are received within the routing interval; identifying candidate agents for inclusion in a candidate agent group, the candidate agents being identified as available ones of the agents to whom the received incoming interactions of the received interaction batch can be routed; and subsequent to the end of the routing interval, routing the received incoming interactions included in the received interaction batch to the candidate agents included in the candidate agent group.