Text Analytics Service for Contact Center Communication Routing
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Solution Overview
Problem
Current methods for routing written communications in contact centers are inefficient, often directing messages to CSRs with non-optimal skill sets due to simplistic analysis based on limited content understanding, leading to delays and suboptimal response times.
Innovation Solution
A method involving a text analytics service module that generates communication metadata, which is then analyzed by a smart routing engine to route written communications to the most appropriate CSR or queue based on skill sets, workload, and predetermined criteria, ensuring effective distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simplistic routing procedures (analyzing To address, Subject line, or pre-filled form) are used, then the routing process is fast and simple, but the written communication is often provided to a CSR with a non-optimal skill set
Solution Approach 1:
The system performs preliminary text analysis using a text analytics service to generate communication metadata (sentiment, intent, entities) before routing. This advance processing enables the smart routing engine to make informed routing decisions based on comprehensive content understanding rather than superficial keywords, resolving the contradiction between simple operation and accurate routing.
Solution Approach 2:
The patent introduces communication metadata as an intermediary between the incoming written communication and the routing decision. The text analytics service extracts meaningful features (sentiment, intent, entities) that serve as a bridge, allowing the routing engine to accurately match communications with appropriate CSRs without requiring complex direct analysis, thus maintaining operational simplicity while improving routing accuracy.
2Reliability
If manual reassignment is performed when initial CSR cannot handle the task, then the communication reaches the appropriate CSR, but delays occur for completion of the work
Solution Approach 1:
The system performs routing analysis in advance using communication metadata generated by the text analytics service. By pre-processing the communication content and extracting key features before routing, the system makes accurate routing decisions at the initial stage, eliminating the need for manual reassignment and associated delays.
Solution Approach 2:
The smart routing engine uses communication metadata (sentiment, intent, entities) as feedback to continuously improve routing decisions. This feedback mechanism enables the system to learn from past routing outcomes and adjust routing strategies, ensuring consistently accurate routing without requiring manual intervention or reassignment.
3Reliability
If comprehensive text analysis is performed to improve routing accuracy, then the written communication is routed to the appropriate CSR, but the system complexity increases
Solution Approach 1:
The patent segments the routing system into distinct modular components: a text analytics service for generating communication metadata and a smart routing engine for making routing decisions. This segmentation allows each component to specialize in its function, improving routing accuracy while managing system complexity through clear separation of concerns and independent deployment of services.
Solution Approach 2:
The communication metadata serves as an intermediary layer between the incoming communication and the routing engine. The text analytics service extracts and structures key features (sentiment, intent, entities) into standardized metadata, which simplifies the routing decision process. This intermediary approach enables comprehensive analysis without proportionally increasing overall system complexity, as the metadata abstraction handles the analytical complexity.
Data Source
AI summary
The present invention allows text analysis and routing of written communications. The system intercepts incoming written communications for analysis by a text analytics service (TAS) software module. The TAS module analyzes the communication to generate communication metadata, which is used by a smart routing engine to route the communication to an appropriate party. This ensures that the ultimate recipient of the communication is capable of effective interaction with the sender and reduces the time required for a communication to be acted upon.