Voice Recognition Engine for Dynamic Script Selection
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Solution Overview
Problem
Conventional customer experience management systems fail to accurately determine customer needs and wants in real-time during live interactions, leading to potential neglect and frustration in contact center services.
Innovation Solution
A system that utilizes a telephony-enabled device with a voice recognition engine and application server to monitor voice channels for specific keywords, phrases, and tone levels, allowing for dynamic script selection and alteration to better address customer needs and motivations during interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional customer experience management systems are used to monitor calls, then call monitoring can be performed, but the system fails to accurately determine customer needs and wants in real-time
Solution Approach 1:
The system performs preliminary analysis by monitoring voice channels during live interactions and identifying customer needs, wants, and motivations before the interaction concludes. This allows the system to proactively determine what the customer really wants at the time they want it, rather than analyzing calls after they end.
Solution Approach 2:
The system continuously monitors voice channels during live interactions and provides real-time feedback about customer needs and motivations to the interaction flow. This feedback loop enables dynamic adjustments to be made during the interaction based on actual customer state, improving both accuracy and timeliness.
2Productivity
If live agents focus on specific call goals, then call objectives can be achieved, but agents become less perceptive to customer experiences
Solution Approach 1:
The system acts as an intermediary between the agent and the customer by monitoring the voice channel and interpreting customer needs and motivations. This allows the agent to maintain focus on call objectives while the system simultaneously perceives customer experience nuances, combining productivity with perceptiveness.
Solution Approach 2:
The system replaces the human agent's need to be simultaneously focused on goals and perceptive of customer experience with an automated voice channel monitoring system. This mechanical/system-based approach handles the perceptiveness function, freeing the agent to focus on achieving call objectives.
3Loss of information
If call result data is gathered after interaction, then analysis can be performed, but improvements cannot be implemented during the interaction
Solution Approach 1:
The system performs the analysis and identification of customer needs during the live interaction itself, before the interaction concludes. This preliminary action enables improvements and adjustments to be implemented immediately during the interaction, rather than waiting for post-interaction analysis.
Solution Approach 2:
The system maintains continuous monitoring and analysis throughout the live interaction, ensuring that customer experience data is collected and acted upon continuously rather than intermittently. This continuity enables real-time improvements to be made while the interaction is ongoing.
Data Source
AI summary
A system for customer interaction includes a telephony-enabled device for receiving voice calls from customers, a voice recognition engine connected to the telephony-enabled device for monitoring the voice channel, and an application server connected to the voice recognition engine for receiving notification when specific keywords phrases or tones are detected. The system is characterized in that the application server selects scripts for presentation to the customer based at least in part on the notifications received from the voice recognition engine.