Real-Time Text Analysis for Contact Center Interaction Routing
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Solution Overview
Problem
Modern contact centers face challenges in routing interactions, such as email and chat sessions, as the availability of agents cannot be determined solely by their current engagement status, given the complexities of packet-switched networks and diverse operational modes.
Innovation Solution
A system that analyzes the content of incoming messages and metadata in real-time to select the most suitable agent based on text analysis, allowing for dynamic routing of interactions to multiple destinations, including agents with relevant skills, and enabling seamless agent changes during ongoing sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If text analysis is performed on incoming messages to determine agent routing, then routing precision is improved, but processing time increases
Solution Approach 1:
The system pre-processes and stores metadata from incoming messages (such as customer ID, message type, and other contextual information) before the actual routing decision is needed. This preliminary extraction and storage of relevant features allows the routing algorithm to quickly retrieve and analyze pre-computed data, reducing the time required for text analysis while maintaining high routing precision.
Solution Approach 2:
The patent introduces an intermediary component that acts as a buffer between message reception and routing decision. This intermediary pre-processes messages, extracts key features, and stores them in a structured format, thereby decoupling the time-consuming analysis work from the critical routing path and reducing overall processing time.
2Measurement precision
If multiple agents are considered for routing based on skill matching, then routing accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the routing process into distinct modules: message reception, metadata extraction, skill matching, and agent selection. Each module handles a specific aspect of the routing decision, making the overall complex system manageable and maintainable. The segmentation allows for independent optimization of each component while maintaining high routing accuracy through skill matching across multiple agents.
Solution Approach 2:
The patent implements a universal routing framework that can handle multiple message types, agent skill sets, and routing criteria through a single standardized system. This multi-functional approach maintains routing accuracy by consistently applying skill-matching logic across diverse scenarios while avoiding the need for separate complex systems for each case.
3Reliability
If real-time text analysis is implemented for message routing, then service quality is improved, but computational resources increase
Solution Approach 1:
The system extracts only the essential metadata and key features from incoming messages that are necessary for routing decisions, rather than performing comprehensive text analysis on the entire message content. This selective extraction maintains service quality by focusing on the most relevant information while significantly reducing the computational resources required for real-time processing.
Solution Approach 2:
The patent applies partial text analysis by focusing only on specific portions of messages that contain routing-critical information, such as subject lines, customer IDs, or predefined keywords. This partial action approach maintains high service quality for routing decisions while avoiding the excessive computational cost of analyzing entire message bodies in real-time.
Data Source
AI summary
Embodiments of the invention are directed to a system and method for routing interactions. A method may include receiving a message related to the interaction. Text included in the message may be analyzed. A destination may be selected for the message based on analysis of the text. The message may be routed to the selected destination.