AI-Driven IVR Call Interception Heuristics
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Solution Overview
Problem
Existing IVR systems face challenges in integrating automated responses with human agent responses and determining optimal moments for human agent intervention, leading to inefficient caller satisfaction and increased response times.
Innovation Solution
The implementation of an AI engine that captures and analyzes voice inputs to provide predictive recommendations, generates machine responses, and recursively trains to improve response accuracy and efficiency, allowing for seamless collaboration between AI and human agents during interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a caller is transferred to a human agent, then the caller receives personalized attention, but the response time increases and caller satisfaction decreases
Solution Approach 1:
The IVR system performs preliminary actions by analyzing caller inputs and preparing appropriate responses before the human agent becomes fully engaged. The system pre-processes caller queries, retrieves relevant information, and formulates draft responses, so that when the human agent joins the interaction, the work is already partially done, reducing overall response time while maintaining personalized service quality
Solution Approach 2:
The IVR system acts as an intermediary between the caller and the human agent. It captures caller inputs, generates automated responses, and presents these to the human agent for review and modification. This intermediary role allows the human agent to focus on complex decision-making and personalized interaction while the IVR handles routine processing, thereby reducing response time without sacrificing caller satisfaction
2Loss of time
If the IVR system handles the interaction exclusively, then response time is reduced, but the ability to satisfy complex caller purposes deteriorates
Solution Approach 1:
The system dynamically adjusts the level of human involvement based on the complexity of the caller's purpose. For simple, routine queries, the IVR system handles the interaction exclusively, providing fast automated responses. For complex or emotionally charged situations, the system dynamically transitions to involve a human agent. This dynamic approach optimizes response time for simple cases while ensuring adaptability for complex cases
Solution Approach 2:
The interaction handling is segmented into different stages: initial caller input capture, automated response generation, human agent review, and final response delivery. The IVR system independently handles the segmentation of capturing inputs and generating draft responses, while the human agent handles the segmentation of reviewing and finalizing responses. This segmentation allows the system to maintain fast automated processing while incorporating human judgment when needed
3Adaptability or versatility
If human agents handle all interactions, then complex caller purposes are satisfied, but productivity decreases and response times increase
Solution Approach 1:
The IVR system provides self-service capabilities by automatically capturing caller inputs, analyzing query intent, retrieving relevant information, and generating draft responses. This self-service functionality handles routine processing tasks that would otherwise require human agent involvement, thereby increasing agent productivity and reducing overall response times while maintaining the ability to satisfy complex caller purposes through human review when necessary
4Ease of operation
If the IVR system integrates automated responses with human agent responses, then caller satisfaction improves, but system complexity increases
Solution Approach 1:
The IVR system serves as an intermediary layer between automated response generation and human agent interaction. It captures caller inputs, generates automated responses, and presents these to the human agent through a standardized interface. The human agent reviews and modifies responses through the same interface before delivery to the caller. This intermediary architecture simplifies integration by providing clear boundaries and standardized communication protocols between automated and human components
Data Source
AI summary
When a customer initiates an interaction with an interactive voice response (“IVR”) system, the customer may need to be transferred to a live agent. Apparatus and methods may formulate timing information for integrating a live agent into an interaction controlled by an artificial intelligence (“AI”) engine. The system may integrate machine generated responses into a customer interaction controlled by a live agent. The system may formulate timing information for intercepting the live agent with responses generated by the AI engine. The system may formulate the timing information using interactional analytics and preferences of a specific customer.