Dynamic Script Engine for Tele-Agents
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Solution Overview
Problem
Current static scripts used by tele-agents in sales interactions do not account for real-time industry trends, customer needs, or product ownership, limiting their ability to provide relevant and dynamic responses during customer calls.
Innovation Solution
A dynamic script engine that utilizes real-time industry trend data, machine learning, and graph databases to create contextually relevant scripts for tele-agents, dynamically reordering or adding sentences based on current industry scores and customer-specific information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static scripts are used for tele-agent interactions, then the script structure is simple and easy to implement, but the script cannot adapt to real-time industry trends, customer needs, or product ownership changes
Solution Approach 1:
The patent transforms static scripts into dynamic scripts that automatically adapt to real-time industry trends, customer needs, and product ownership changes. The system continuously updates script content based on current data without requiring manual rewriting, enabling the tele-agent to respond appropriately to varying customer situations while maintaining a manageable system architecture through automated processes.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor industry trends, customer interactions, and product data in real-time. This feedback loop enables the script to automatically adjust its content and recommendations based on current conditions, ensuring the tele-agent receives up-to-date information without increasing operational complexity for the user.
2Reliability
If dynamic scripts incorporating real-time data are implemented, then customer interaction quality improves, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent introduces an intermediary data processing layer that sits between the tele-agent interface and the raw data sources. This intermediary layer aggregates, filters, and processes real-time industry trend data, customer information, and product ownership data into actionable insights. By centralizing this complex data processing in a dedicated intermediary system, the overall architecture remains manageable while reliably providing context-aware script recommendations.
3Adaptability or versatility
If real-time data processing is performed during customer calls, then script relevance to current events improves, but the time required for script generation increases
Solution Approach 1:
The system performs preliminary data aggregation and processing before the actual customer call occurs. Industry trend data, customer historical information, and product ownership details are pre-fetched and processed in advance, so that when the call begins, the script is already optimized with relevant context. This preliminary action eliminates the need for time-consuming real-time data processing during the call itself, maintaining both script relevance and call efficiency.
Data Source
AI summary
Embodiments of the present invention include a dynamic script engine for tele-agents including a statistics engine configured to receive, during a sales call, real-time industry trend data from one or more remote industry resources; create a current industry score in dependence upon the industry trend data and current products available to a customer on an active call; and transmit the current industry score to a script generator; and a script generator configured to receive the current industry score from the statistics engine and dynamically reorder in real-time and in dependence upon the industry score one or more sentences of a dynamic script to be read by a sales agent to the customer during the sales call.