Real-Time Agent Guidance System for Call Centers
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Solution Overview
Problem
Current call center computer systems fail to provide real-time, customizable assistance to agents during calls, limiting their ability to effectively interact with callers.
Innovation Solution
The implementation of an agent guidance system that generates and provides real-time, customizable guidance prompts to call center agents based on ongoing conversations, using audio analysis and records and analytics data to identify appropriate templates and tasks, ensuring agents receive relevant information and instructions dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional call center computer systems are used, then agents can access account information and process orders, but the systems fail to provide real-time customizable assistance during calls
Solution Approach 1:
The system dynamically generates and updates guidance prompts in real-time based on ongoing call analysis. The guidance is not static but adapts as the conversation progresses, with the system continuously monitoring call data and adjusting prompts to match the current call scenario and agent needs.
Solution Approach 2:
The system implements a feedback loop where call data is continuously analyzed, guidance prompts are generated based on this analysis, and the system monitors whether the prompts are effective. This feedback mechanism allows the system to refine and customize guidance for different call scenarios and agent performance patterns.
2Productivity
If real-time guidance prompts are provided to agents, then agents receive relevant information and instructions, but the system complexity increases
Solution Approach 1:
The system segments the guidance delivery into distinct components: call data capture, audio analysis, template matching, prompt generation, and delivery to the agent interface. This modular segmentation allows each component to be optimized independently while managing overall system complexity.
Solution Approach 2:
The system introduces an intermediary layer (the guidance system) that sits between the call center's existing computer systems and the agents. This intermediary translates and processes information from multiple sources into customized guidance prompts, integrating with existing infrastructure without requiring complete system replacement.
3Loss of information
If the system analyzes ongoing conversations and provides customized guidance, then assistance relevance improves, but the time to process and deliver guidance may increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and analyzing call data as it becomes available, preparing guidance templates in advance based on call patterns and scenarios. This allows the system to have guidance ready to deliver with minimal delay when specific call situations arise.
Solution Approach 2:
The system changes parameters such as analysis depth, processing speed, and guidance detail based on call urgency and type. For routine calls, lighter processing is applied, while complex scenarios receive more thorough analysis, dynamically adjusting the balance between information relevance and processing time.
Data Source
AI summary
A device may capture call data corresponding to call between an agent of a call center and a caller. The device may identify a guidance template based on the call data. The guidance template may include one or more rules and/or information for assisting the agent during the call. The device may generate an agent prompt based on the guidance template and/or provide the guidance prompt to an agent device of the agent. The agent device may receive the guidance prompt and display the guidance prompt to the agent. The agent device may capture additional call data from the call and update the guidance prompt based on the call inputs.