Behavioral Pairing Strategy for Contact Center Agent Utilization
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Solution Overview
Problem
Traditional task assignment strategies in contact center systems, such as FIFO and PBR, often fail to optimize agent utilization and overall performance, as they do not consider historical interaction data associated with contacts' phone numbers, leading to suboptimal task assignments.
Innovation Solution
The implementation of a Behavioral Pairing (BP) strategy that uses historical information, including interaction duration, outcomes, and types, to pair contacts with agents, optimizing agent utilization and overall contact center performance by considering the historical data associated with a contact's phone number.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional FIFO or PBR assignment strategies are used, then the assignment process is simple and fast, but agent utilization and overall contact center performance are not optimized
Solution Approach 1:
The system pre-calculates and stores historical interaction data for each contact, including interaction duration, outcomes, and types. This preliminary preparation enables the behavioral pairing strategy to quickly access relevant historical information during task assignment without adding real-time computational complexity
Solution Approach 2:
The system incorporates feedback loops that continuously collect and analyze interaction outcomes to refine agent-contact pairing decisions. By using historical performance data and interaction patterns, the system dynamically adjusts assignments to improve overall contact center performance while maintaining manageable complexity through iterative optimization
2Productivity
If Behavioral Pairing strategy with historical data analysis is implemented, then overall contact center performance improves, but individual contact outcomes may be less favorable due to non-FIFO assignment
Solution Approach 1:
The system changes the assignment parameters from simple FIFO ordering to multi-dimensional behavioral parameters including historical interaction duration, outcomes, and contact types. By analyzing these parameters, the system identifies optimal agent-contact pairings that improve overall performance while maintaining fairness through structured evaluation criteria
Solution Approach 2:
The system introduces asymmetric treatment in assignments by deliberately deviating from FIFO order when historical data indicates that a different pairing would benefit the overall contact center performance. This asymmetric approach is balanced by ensuring that individual contacts still receive appropriate service through controlled randomization and fairness constraints
3Productivity
If historical interaction data is considered in assignment decisions, then agent-task pairing optimization improves, but system complexity and data processing requirements increase
Solution Approach 1:
The system extracts only the most relevant historical interaction features (duration, outcomes, types) needed for behavioral pairing decisions, rather than processing complete interaction histories. This extraction approach reduces data complexity while maintaining the ability to make optimized assignment decisions based on key performance indicators
Data Source
AI summary
Techniques for pairing contacts and agents in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for pairing contacts and agents in a contact center system comprising: assigning, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a contact to an agent based on information associated with a prior interaction of the contact with the contact center system. The assigning of the contact to the agent may result in a less favorable outcome for the contact assigned to the agent and an increase in an overall performance of the contact center system.