Routing Decision Engine for Call Center Communication Handling
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Solution Overview
Problem
Current communication systems in call centers face inefficiencies when customers have multiple needs that require different agents, leading to increased wait times and suboptimal user experiences, as agents are often not trained to handle diverse business areas, making it costly to train every agent in all lines of business.
Innovation Solution
A system that includes a communications handling module and a routing decision engine to identify both present and unidentified needs of users, routing communications to agents trained in relevant areas, allowing a single agent to address multiple needs during a single interaction by combining identified and unidentified needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If more agents are deployed in the call center to reduce customer wait time, then customer service capacity increases, but operational cost increases
Solution Approach 1:
The patent implements a unified agent profile system where each agent is associated with multiple skill tags representing different business areas and competencies. The routing engine matches customer needs with agent capabilities by comparing service tags against agent skill sets, enabling single agents to handle diverse customer inquiries across multiple domains without requiring separate specialized agents for each function.
Solution Approach 2:
The system introduces an intelligent routing engine as an intermediary between customers and agents. This mediator analyzes customer service needs, retrieves relevant agent profiles from the database, and performs automated matching based on skill compatibility. This intermediary layer eliminates the need for customers to wait for available agents by pre-processing and optimizing the agent selection process.
2Adaptability or versatility
If agents are trained in all business areas to handle diverse customer needs, then service versatility improves, but training cost and complexity increase
Solution Approach 1:
The patent segments agent expertise into discrete, taggable skill units rather than requiring comprehensive general knowledge. Each business area and competency is represented as an independent skill tag that can be individually assigned to agents. This segmentation allows the system to compose diverse service capabilities by selecting and combining relevant skill tags for each routing decision, rather than requiring every agent to master all areas.
Solution Approach 2:
The system changes the parameter representation of agent skills from holistic competency assessments to discrete, quantifiable skill tags with associated metadata. This parameter transformation enables flexible combination and matching of skills through algorithmic comparison, allowing the routing engine to dynamically assemble appropriate skill sets for different service scenarios without requiring agents to possess fixed, comprehensive expertise.
3Reliability
If customers are placed on hold to transfer between agents for different needs, then service specialization improves, but user experience deteriorates
Solution Approach 1:
The system performs preliminary analysis of customer service needs and pre-matches with appropriate agents before the customer enters the queue. The routing engine evaluates service tags, agent skill sets, and availability in advance, preparing optimal routing decisions beforehand. This preliminary action eliminates the need for mid-conversation transfers and hold periods, as customers are connected to suitably qualified agents from the outset.
Solution Approach 2:
The patent merges multiple service considerations into a unified routing decision process. Instead of handling service specialization and customer experience as separate concerns requiring sequential handoffs, the system combines skill matching, agent availability, and service requirements into a single integrated routing algorithm that simultaneously optimizes for both specialization and user experience.
Data Source
AI summary
Systems and methods to process communications received from a user are described herein. In one example, the system may include a communications handling module that receives communications from users and a routing decision engine that selects an agent to process the communication. In another example, the method may include, receiving a communication from a user, parsing their need from the communication, and processing the communication using the need and other needs. In a further example, the method may include anticipating a service or product that may be of interest to the user and servicing that during a single interaction with an agent, where the interaction was initiated by the user for another need.