Conversation Resource Suggestion Using NLP for Customer Requests
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Solution Overview
Problem
Existing methods for customer-company interaction, such as navigating websites or voice menus, are time-consuming and costly for companies, while hiring customer service representatives is expensive.
Innovation Solution
Implementing semantic processing to automate responses and assist customer service representatives by understanding natural language requests, using NLP to determine actions and suggest responses or resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If companies use traditional customer interaction methods (website navigation, voice menus, human representatives), then customers can receive service, but the interaction time increases and operational costs increase
Solution Approach 1:
The patent implements an automated message suggestion system that enables customers to independently compose and send messages without human assistance. The system analyzes conversation context and automatically generates appropriate response suggestions, allowing customers to resolve issues through self-service rather than requiring customer service representatives or complex navigation through voice menus and websites.
Solution Approach 2:
The patent replaces manual customer service operations with an automated natural language processing system. Instead of human representatives manually responding to customer inquiries or customers navigating complex menu systems, the system uses AI-driven message analysis and suggestion generation to automate the interaction process, substituting mechanical human labor with automated computational processes.
2Reliability
If companies hire customer service representatives to manually respond to requests, then customer service quality improves, but operational expenses increase
Solution Approach 1:
The system empowers customers to independently manage their communications by providing automated message suggestions based on conversation context. This eliminates the need for customer service representatives to manually draft and send messages, allowing customers to resolve their own issues while maintaining service quality through intelligent automation.
Solution Approach 2:
The patent employs cost-effective automated message suggestions that can be rapidly generated and discarded based on conversation needs. Instead of maintaining expensive human customer service operations for every interaction, the system uses inexpensive automated suggestions that are created on-demand and replaced as conversations evolve, significantly reducing operational costs while maintaining service functionality.
Data Source
AI summary
A third-party service may be used to assist entities in responding to requests of users by determining a suggested resource corresponding to a received communication. The third party service may receive a request from a first entity, such as via an application programming interface request, that includes a message in a conversation. A conversation feature vector may be computed by processing the message with a first neural network. A suggested resource may be determined using the conversation feature vector. The third-party service may then return the suggested resource for use in the conversation. The third-party service may similarly be used to assist other entities in responding to requests of users.