AI Alert Selection for Contact Center Agents
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Solution Overview
Problem
In contact centers, agents face challenges in quickly accessing and retaining relevant customer information, particularly for visually impaired, handicapped, or aged agents, leading to longer call times and potential customer dissatisfaction due to information overload and delays in connecting with customers.
Innovation Solution
The system provides customizable in-ear prompts and AI-driven summaries of customer information, accessible through sounds or tactile means, allowing agents to receive targeted and relevant information during the ring time, enabling quicker engagement and improving call handling efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all available customer information is presented to the agent, then the agent has complete information for the call, but the agent experiences information overload and requires excessive time to read and assimilate
Solution Approach 1:
The system extracts only the most relevant customer attributes from the complete customer information set and presents them to the agent through audio cues during the ring time. This selective extraction eliminates information overload while ensuring the agent receives critical information needed for effective call handling.
Solution Approach 2:
The system performs preliminary processing of customer information before the call connects, analyzing and identifying the most relevant attributes during the ring time. This preliminary action prepares targeted information in advance, allowing the agent to receive only essential information without having to process all available data during the call setup.
2Ease of operation
If the agent is given extensive time to read customer background, then the agent can thoroughly understand customer information, but the customer waits longer on hold and system resources are tied up
Solution Approach 1:
The system extracts and presents only the most critical customer attributes through audio cues during the ring time, enabling the agent to quickly grasp essential information without requiring extensive reading time. This extraction approach maintains agent understanding while significantly reducing customer wait time.
Solution Approach 2:
The system replaces the mechanical process of the agent reading text on a screen with an audio-based information delivery system. The neural network generates audio cues that convey customer attributes directly to the agent's device, eliminating the need for visual scanning and reading, thereby reducing the time required for the agent to understand customer information.
3Productivity
If the agent scans information quickly to connect the customer promptly, then call setup time is reduced, but the agent fails to identify or retain relevant information
Solution Approach 1:
The system extracts and highlights only the most relevant customer attributes for the current call context, presenting them through audio cues during the ring time. This allows the agent to quickly receive targeted information without scanning through all customer data, ensuring both rapid call setup and accurate information identification.
Solution Approach 2:
The system applies local quality by providing different information emphasis based on the specific call context and customer attributes. The audio cues highlight particular attributes that are most relevant to the current situation, allowing the agent to focus on critical information while maintaining quick call setup speed.
4Quantity of substance
If visual text presentation is used for customer information, then information can be displayed comprehensively, but visually impaired, handicapped, or aged agents have difficulty focusing and scanning
Solution Approach 1:
The system replaces visual text presentation with an audio-based information delivery mechanism. The neural network generates audio cues that convey customer attributes through sound, making the information accessible to visually impaired, handicapped, or aged agents who have difficulty focusing on and scanning visual text on screens.
Data Source
AI summary
When an agent is about to be connected to a customer for a communication, there is a small window of time in which the agent may be presented with information determined to be relevant to the communication. After the window closes, the communication may then be connected to the customer. If too much information is presented, the agent may be unable to ascertain or retain such information. However, a neural network to determine the most relevant customer attributes and selecting cues corresponding to the most relevant customer attributes for presentation on an agent device, allowed the agent to be presented with only the most relevant information in a retainable manner.