Virtual Assistant Contact Center Adaptation
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Solution Overview
Problem
Existing virtual assistants are limited in their ability to learn from and assist during customer interactions in contact centers, as they are primarily designed to react to predefined commands and lack the capability to analyze and adapt to private conversations, leading to inefficiencies in customer support and privacy concerns regarding data usage.
Innovation Solution
An enhanced virtual assistant system that captures, analyzes, and learns from customer interactions in contact centers, providing supplemental information and adapting responses based on past interactions, using APIs to integrate with existing virtual assistants and share relevant data with customers, thereby improving the efficiency of contact center operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual assistants are designed to react to predefined commands only, then device complexity is reduced and ease of manufacture is improved, but adaptability and customer support effectiveness deteriorate
Solution Approach 1:
The patent introduces contact center data as an intermediary layer between the virtual assistant and the customer interaction history. This mediator provides structured, relevant conversation data that the virtual assistant can learn from without requiring direct access to or processing of all raw interaction data, thus improving adaptability while controlling complexity
Solution Approach 2:
The system performs preliminary analysis and structuring of contact center data before presenting it to the virtual assistant. By pre-processing interaction histories into useful formats and identifying key patterns in advance, the system enables the virtual assistant to learn effectively without bearing the full burden of data processing complexity
2Productivity
If virtual assistants capture and analyze private conversation data, then customer support quality improves through adaptive learning, but privacy concerns and data security risks increase
Solution Approach 1:
The patent extracts only the necessary and relevant portions of private conversation data that are needed for improving virtual assistant performance. By selectively taking out specific interaction patterns and contact center data rather than using all available data, the system improves support efficiency while minimizing privacy exposure
Solution Approach 2:
The system implements feedback mechanisms where the virtual assistant learns from contact center data in a controlled manner, with the ability to provide feedback on what data is useful and what should be protected. This creates a feedback loop that balances learning needs with privacy preservation
3Ease of operation
If virtual assistants are cloud-based with Internet access, then ease of operation and accessibility are improved, but reliability during Internet outages or connection issues deteriorates
Solution Approach 1:
The patent merges cloud-based virtual assistant capabilities with on-device or contact center-based support mechanisms. By combining multiple delivery channels and support systems, the solution maintains accessibility benefits of cloud-based operation while providing backup pathways that ensure reliability when Internet access is compromised
Data Source
AI summary
The technology disclosed herein includes analyzing a transcript of a communications session between a customer operating a customer device and a virtual assistant to determine a customer query; analyzing the customer query to generate supplemental information to respond to the customer query; and providing the supplemental information to the customer device by the virtual assistant.