Contact Center Conversation Flow Mining System
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Solution Overview
Problem
Current systems for contact centers lack an efficient method to analyze and extract insights from conversation transcripts, leading to suboptimal agent guidance and customer interaction management.
Innovation Solution
A system and method for mining conversation flows, involving the receipt of transcripts, extraction of intents and slot entries, clustering into intent categories, and generating guided flows to define actions for contact center agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis of conversation transcripts is used, then agent guidance can be customized, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables automated self-service analysis of conversation transcripts using AI/ML models that automatically extract intents, entities, and conversation flows without requiring manual human analysis, thereby dramatically improving productivity and reducing time loss
Solution Approach 2:
The patent replaces the mechanical manual analysis process with an automated electronic system using natural language processing and machine learning algorithms to extract insights from transcripts, eliminating the time-consuming manual effort while maintaining or improving analysis quality
2Loss of information
If detailed analysis of all transcripts is performed, then comprehensive insights are obtained, but the computational complexity and processing time increase
Solution Approach 1:
The system segments the transcript analysis process into distinct modular components: intent extraction, entity recognition, conversation flow identification, and pattern analysis. This segmentation allows comprehensive analysis while managing complexity through organized, independent processing stages
Solution Approach 2:
The AI/ML analysis system is designed as a universal platform that can handle multiple types of transcripts across different domains and languages using the same core architecture, reducing overall system complexity while maintaining comprehensive analysis capabilities through adaptable models
Data Source
AI summary
A method for mining conversation flows according to an embodiment includes receiving a plurality of transcripts of conversations between contact center agents and users, generating a summary of each transcript of the plurality of transcripts by extracting, for each transcript, one or more intents associated with the respective transcript and one or more slot entries associated with the respective transcript, clustering the plurality of transcripts into a plurality of intent categories based on the respective summary of each transcript, wherein each intent category includes intents that are similar to one another, and analyzing each transcript within a selected intent category of to generate a guided flow for the selected intent category, wherein the guided flow defines a set of actions to be taken by a human/virtual contact center agent to resolve an intent associated with the selected intent category.