Virtual Universe Customer Service Avatar Allocation
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Solution Overview
Problem
In Virtual Universe environments, customer service demands are challenging due to the inability of existing systems to effectively manage customer service representatives, leading to delays and loss of high-priority customers, as they often rely on first-in first-out or round-robin methods that fail to prioritize higher-value interactions.
Innovation Solution
A system that allocates customer service representatives by cloning a primary CSR avatar into subavatars with divergent performance characteristics, assigning them based on customer profiles and store objectives, using a load-balancing algorithm to ensure timely and appropriate service, including the use of automated and human-monitored subavatars to manage customer interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If first-in first-out or round-robin methods are used to allocate customer service representatives, then the allocation process is simple and easy to implement, but high-priority customers are not prioritized leading to delays and customer abandonment
Solution Approach 1:
The system changes the allocation parameters by introducing customer priority levels, CSR performance characteristics, and store objectives as weighting factors. Instead of simple FIFO or round-robin allocation, the system dynamically calculates allocation weights based on multiple parameters including customer value, service urgency, and CSR capabilities, thereby resolving the contradiction between simple allocation and efficient service delivery
Solution Approach 2:
The allocation system transitions from static FIFO/round-robin methods to a dynamic weighted allocation mechanism that continuously adjusts CSR assignment based on real-time customer profiles, service requirements, and CSR performance metrics. This dynamic approach enables the system to prioritize high-value interactions while maintaining operational simplicity through automated calculations
2Device complexity
If a single primary CSR avatar is used to serve all customers, then the system structure is simple, but service capacity is limited leading to delays and customer abandonment
Solution Approach 1:
The system segments the single primary CSR avatar into multiple specialized subavatars, each with divergent performance characteristics tailored to different customer service needs. This segmentation increases service capacity by allowing parallel handling of multiple customer interactions while maintaining manageable system structure through a hierarchical organization of primary and subavatar entities
Solution Approach 2:
The system creates multiple copies (subavatars) of the primary CSR avatar, each copy inheriting and adapting the primary avatar's capabilities while developing specialized performance characteristics. This copying mechanism enables scalable service capacity expansion without proportionally increasing system complexity, as all subavatars are managed through the unified primary avatar framework
3Productivity
If automated bot CSRs are used to handle customer interactions, then service capacity increases, but customer satisfaction decreases for interactions requiring human attention
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor customer interaction quality, satisfaction metrics, and service outcomes. This feedback loop enables the system to learn from automated bot performance and make intelligent routing decisions, transferring complex or dissatisfied customers to human CSRs while maintaining high service capacity through automated handling of routine interactions
Solution Approach 2:
The system introduces an intelligent routing intermediary that mediates between automated bot CSRs and human CSRs. This intermediary evaluates customer needs, interaction context, and available resources to optimally allocate customers to appropriate CSR types, thereby maintaining high service capacity while ensuring customer satisfaction through appropriate human intervention when needed
4Reliability
If human-monitored subavatars are used to ensure service quality, then customer satisfaction improves, but system complexity and operational overhead increase
Solution Approach 1:
The system applies partial human monitoring rather than complete human oversight of all customer interactions. Human CSRs provide monitoring and intervention for complex or high-value customer service cases, while automated subavatars handle routine interactions independently. This partial action approach maintains service quality for critical interactions while avoiding the excessive operational overhead of full human monitoring across all service channels
Data Source
AI summary
Virtual universe customer service representatives axe cloned and assigned as a function of observing customer behavior, retrieving historical data and creating a customer profile Preferential subavatar assignment parameters are determined for a customer as a function of the customer profile, choosing a subavatar from a plurality of subavatars as a function of a correlation of a subavatar performance characteristic with the preferential subavatar assignment parameter and a store objective, and the clone is populated with the chosen subavatar Choosing a subavatar may comprise preferentially rating subavatars and determining an appropriateness threshold as a function of the subavatar assignment parameter, the performance characteristics and the stole objective. Some embodiments reset a threshold in response to time-in-queue or to repetitively observing customer behavior, retrieving customer data, determining a subavatar assignment parameter and choosing a highest-rated available subavatar meeting a revised threshold. Subavatars may comprise automated, customer service representative-controlled and jointly-controlled subavatars.