Voice Data Behavioral Analysis for Contact Center Monitoring
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Solution Overview
Problem
Current methods for analyzing customer interactions in call centers lack objectivity and provide limited insight into the underlying behavioral characteristics of customers and agents, making it difficult to train agents effectively and improve customer relationships.
Innovation Solution
A method and system that separates telephonic communications into constituent voice data, applies a linguistic-based psychological behavioral model to analyze the data, and generates behavioral and distress assessment data to provide objective insights for training and improving customer interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If third party telephone call centers are used to handle customer inquiries, then cost effectiveness is improved, but monitoring quality and consistency deteriorate
Solution Approach 1:
The patent replaces manual monitoring methods with an automated computer-based system that uses audio analysis software to objectively evaluate customer interactions. The system automatically analyzes voice data, detects emotional states, and generates performance metrics, eliminating the need for human monitors and ensuring consistent, reliable evaluation across all calls regardless of call center location.
2Loss of information
If post-call data collection surveys are used, then customer feedback is obtained, but the process is subjective and tied to customer willingness to provide feedback
Solution Approach 1:
The system automatically analyzes the actual audio content of customer calls without requiring additional customer input or surveys. The audio analysis software independently evaluates the interaction by processing voice data, detecting emotional states, and generating objective performance metrics, making the measurement process autonomous and not dependent on customer cooperation.
Solution Approach 2:
The patent replaces subjective survey-based feedback collection with an automated computer system that objectively analyzes audio data. The system uses digital signal processing and pattern recognition algorithms to detect emotional states and evaluate interaction quality, providing precise, objective measurements that are not influenced by customer willingness to respond.
3Measurement precision
If stress analysis is performed on audio telephone calls, then customer experience is determined, but little insight is provided into the reasons for the outcome
Solution Approach 1:
The patent segments the audio data into distinct emotional state categories (e.g., anger, frustration, satisfaction) and analyzes specific acoustic features associated with each state. By breaking down the complex audio signal into identifiable emotional components and linking them to specific behavioral patterns, the system provides both the assessment outcome and the underlying reasons for that outcome.
Solution Approach 2:
The system introduces an intermediary layer of analysis that translates raw audio data into meaningful behavioral insights. The audio analysis software acts as a mediator between the raw voice data and the customer experience assessment, extracting emotional states and behavioral patterns that explain the underlying reasons for the assessment outcomes.
4Measurement precision
If linguistic-based psychological behavioral models are applied to separated voice data, then objective behavioral characteristics are identified, but the system complexity increases
Solution Approach 1:
The patent segments the complex analysis task into distinct functional modules: audio data separation, emotional state detection, behavioral pattern recognition, and insight generation. Each module handles a specific aspect of the analysis independently, making the overall complex system more manageable and easier to implement while maintaining high measurement precision through specialized processing at each stage.
Data Source
AI summary
A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into first and second constituent voice data. One of the first and second constituent voice data is analyzed. The analysis consist of translating one the constituent voice data into a text format and applying a predetermined linguistic-based psychological behavioral model to the translated voice data. In applying the behavioral model, the translated voice data is mined, and behavioral signifiers associated with the psychological behavioral model are identified in the voice data. The behavioral signifiers are automatically associated with at least one of a plurality of personality types associated with the psychological behavioral model. Behavioral assessment data is generated which corresponds to the analyzed voice data.