Open Conversation Interface for Channel-Agnostic Customer Support
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Solution Overview
Problem
Existing user interface systems for customer support require cumbersome natural-language-based free-form inputs and lack a seamless, consistent experience across channels, failing to utilize background intelligence from prior interactions.
Innovation Solution
An open conversation user interface on a client computing device that initiates a conversation with a member services representative, utilizing automated or manual determination of next inquiries based on prior exchanges and background intelligence, allowing for graphical interface responses and input methods like touch, voice, or free form, enabling modification of responses and seamless channel switching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural-language-based free-form inputs are used in chat box format, then customers can communicate with MSRs, but the interaction becomes cumbersome and requires multiple edits of prior responses
Solution Approach 1:
The system pre-presents structured response options to customers based on the conversation topic and context, eliminating the need for customers to manually type out responses. The background intelligence data and conversation history are used to anticipate and prepare relevant response choices in advance, allowing customers to simply select from predefined options rather than composing free-form inputs.
Solution Approach 2:
The system automatically generates and updates response options based on the conversation flow and background intelligence, without requiring manual intervention from either the customer or MSR. The interface dynamically adapts by presenting relevant choices that evolve as the conversation progresses, making the interaction self-adjusting and efficient.
2Adaptability or versatility
If separate channel-specific interface systems are used for different customer support channels, then each channel can be optimized, but the user experience becomes inconsistent and background intelligence cannot be shared
Solution Approach 1:
The system implements a universal interface framework that works consistently across all customer support channels (chat, email, phone, etc.). The core conversation management logic, background intelligence processing, and response option generation are channel-agnostic, providing a unified user experience. Each channel can still have its specific input methods while sharing the same intelligent backend that maintains consistency and enables intelligence sharing across channels.
Solution Approach 2:
The patent merges previously separate channel-specific systems into a single unified conversation interface that handles multiple channels through one consistent framework. The background intelligence layer is combined across all channels, allowing insights and context to be shared universally, while the presentation layer adapts to each channel's specific capabilities.
3Productivity
If chat box interfaces are used without background intelligence integration, then simple conversations can occur, but prior interaction data cannot be utilized to simplify exchanges
Solution Approach 1:
The system continuously analyzes conversation exchanges and background intelligence data to dynamically adjust and refine response options presented to customers. Prior interaction data is fed back into the system to improve the relevance and accuracy of suggested responses. The conversation history and background intelligence mutually reinforce each other, with each exchange informing future response recommendations.
Solution Approach 2:
Background intelligence data from prior interactions is processed in advance to pre-configure relevant response options and conversation pathways. The system proactively prepares contextualized response choices based on historical data before the customer even provides their input, enabling faster and more relevant interactions without requiring manual analysis of prior communications.
Data Source
AI summary
Disclosed are systems and methods for conducting an open conversation user interface and more particularly, to a channel-agnostic user interface experience which can utilize automated background intelligence to simplify the exchange between a software system or member service representative (MSR) and a member, and avoids the need for web-based free form inputs.