Automated Software Selection for Customer Service Agents
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Solution Overview
Problem
Providing efficient customer service is challenging for large companies as customer service agents often struggle to quickly address customer issues due to dispersed customer data and complex company policies across different applications, making it difficult to identify relevant applications and policies during interactions.
Innovation Solution
A customer service system that analyzes various factors, including call transcriptions, customer data, and agent interactions, to automatically select and present relevant applications and policies to agents during calls, using rules and machine learning models to improve accuracy over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If customer data and policies are dispersed across different applications, then comprehensive customer service functionality is available, but agents have difficulty quickly identifying and accessing relevant applications during interactions
Solution Approach 1:
The patent introduces an automated software selection system that acts as an intermediary between the dispersed customer service applications and the agents. This system monitors interaction data, analyzes customer needs, and automatically selects and presents relevant applications to agents, eliminating the manual search process while maintaining access to comprehensive functionality.
Solution Approach 2:
The system performs preliminary analysis of interaction data and customer information before the agent needs to access applications. By pre-identifying relevant software based on monitored interactions and customer profiles, the system prepares and presents applications in advance, reducing the time agents spend searching during live interactions.
2Adaptability or versatility
If multiple software modules are available to assist agents, then comprehensive customer service capabilities are provided, but agents face difficulty selecting the appropriate modules during interactions
Solution Approach 1:
The automated selection system enables self-service by autonomously analyzing interaction data, customer profiles, and service requirements to automatically select appropriate software modules. This eliminates the cognitive burden on agents to manually evaluate and select from multiple available modules, while the system adapts its selections based on learned patterns from historical data.
Solution Approach 2:
The system implements feedback loops where it monitors agent performance, customer satisfaction metrics, and interaction outcomes to continuously refine its software selection algorithms. This feedback mechanism allows the system to learn from actual usage patterns and improve its ability to present the most relevant modules, making the system increasingly accurate over time.
3Reliability
If customer data is distributed across multiple applications, then complete customer information is accessible, but agents struggle to quickly access relevant information during calls
Solution Approach 1:
The system extracts and isolates only the relevant customer information and application modules needed for each specific interaction, separating them from the broader distributed data ecosystem. By pulling out precisely what is needed based on interaction analysis, it provides complete relevant information quickly without requiring agents to navigate through all available data sources.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automating software selection are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, user interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, user summary data that reflects characteristics of the first user. The actions further include, based on the user interaction data and the user summary data, determining, by the computing device, an application that is relevant to the interaction between the first user and the second user. The actions further include, based on determining the application that is relevant to the interaction between the first user and the second user, providing, for output to the second user, an interface of the application.