Natural Language Interface Customization for Communication Routing
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Solution Overview
Problem
Large organizations face challenges in efficiently processing and routing incoming communications, such as emails, due to visitor confusion and inaccuracies in routing, leading to unnecessary handling time and misdirection.
Innovation Solution
A method of customizing user interfaces based on natural language inquiries, using a predefined interface to analyze user input and present a customized set of communications options, FAQs, and web support tools, reducing the need for agent intervention by providing context-sensitive information and routing options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If contact information is listed on a website, then visitors can find contact details, but visitor confusion and routing inaccuracy increase
Solution Approach 1:
The contact information is made dynamic by analyzing the visitor's natural language inquiry and automatically selecting the most appropriate contact method and agent group. The interface adapts in real-time based on the visitor's needs, transforming static contact lists into a dynamic, context-aware routing system that reduces confusion and improves accuracy.
Solution Approach 2:
The system performs self-service routing by automatically analyzing the visitor's inquiry and determining the appropriate contact method without requiring manual selection or intervention. The natural language processing system autonomously identifies the best contact option based on the inquiry content, reducing visitor confusion and improving routing accuracy simultaneously.
2Productivity
If contact information is listed on a website, then contact details are accessible, but handling time increases unnecessarily
Solution Approach 1:
The system performs preliminary action by analyzing the visitor's natural language inquiry before routing occurs. The natural language processing system processes and understands the inquiry content in advance, enabling the system to automatically determine the correct contact method and agent group before the communication is even sent, thereby reducing unnecessary handling time and improving processing efficiency.
Solution Approach 2:
The manual mechanical process of reviewing contact information and manually routing communications is replaced with an automated natural language processing system. This substitution eliminates manual intervention in the routing process, reducing handling time and improving processing efficiency by using AI-based analysis instead of human review.
3Reliability
If communications are sent to the wrong agent group, then routing can occur, but misdirection and unnecessary processing increase
Solution Approach 1:
The system incorporates feedback loops where the natural language processing system continuously analyzes the visitor's inquiry and adjusts the routing decision accordingly. This feedback mechanism ensures that the routing accuracy is continuously optimized based on the actual content of the communication, reducing misdirection and unnecessary processing by verifying the correctness of the routing decision.
Solution Approach 2:
The system changes the routing parameters dynamically based on the analysis of the natural language inquiry. Instead of using fixed routing rules, the system adjusts routing parameters such as the selected agent group and contact method based on the semantic content of the visitor's message, thereby improving routing accuracy and reducing misdirection.
4Adaptability or versatility
If a predefined interface is used for communications, then structure is maintained, but customization and user needs alignment decrease
Solution Approach 1:
The interface is transformed from a static predefined structure into a dynamic system that automatically adapts to user needs. The natural language processing system analyzes the visitor's inquiry and dynamically generates the appropriate interface elements and routing options, maintaining structural integrity while achieving high adaptability and customization without increasing perceived complexity.
Data Source
AI summary
A method for communicating over a network includes transmitting, by an application server to a remote user computing device, a predefined interface in response to a contact request by the remote user, the predefined interface being customized by the application server based on specified conditions. The method also includes analyzing, by an analysis server in communication with the application server by a communication link different from the network, a natural language inquiry from the remote user based on the type of remote user language of the contact request. The method further includes transmitting, by the application server to the remote user computing device, a customized interface, which includes a customized plurality of communications options for the remote user to route subsequent communications, and customized content based on a context of the natural language inquiry.