AI Contact Center Resolution Using Accuracy-Scored Knowledge Retrieval
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Solution Overview
Problem
Contact centers face challenges such as lengthy agent queues and after-hours communication difficulties, leading to inefficient first interaction resolution and client dissatisfaction.
Innovation Solution
Implementing an AI system that analyzes user issues through natural language processing, retrieves solutions from a knowledge base, provides accuracy-scored suggestions, and escalates to human agents when necessary, updating the knowledge base with new solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an AI system is implemented to handle client interactions, then first call resolution rate is improved, but system complexity increases
Solution Approach 1:
The patent introduces an AI system as an intermediary between clients and contact center agents. The AI system includes natural language processing components, knowledge base retrieval, and solution recommendation mechanisms that automatically handle client interactions, thereby improving first call resolution rates while managing system complexity through modular architecture
Solution Approach 2:
The AI system enables self-service capabilities by autonomously analyzing client issues through natural language processing, retrieving relevant solutions from a knowledge base, and providing recommended solutions without requiring immediate human agent intervention. This self-service approach directly improves first call resolution while the modular design keeps complexity manageable
2Reliability
If more agents are staffed to handle interactions, then client service quality is improved, but operational cost increases
Solution Approach 1:
The AI system performs self-service by automatically analyzing client issues, retrieving solutions from the knowledge base, and providing recommendations. This automation replaces the need for additional human agents to handle routine interactions, maintaining service quality while reducing operational costs associated with staffing
Solution Approach 2:
The system changes the operational parameter from human agent quantity to AI processing capacity. By transforming the service delivery mechanism from human-based to AI-based, the system maintains or improves service quality while significantly reducing the operational costs associated with hiring, training, and managing additional agents
3Measurement precision
If natural language processing is used to analyze user issues, then interaction accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary action by pre-processing and indexing knowledge base entries before actual client interactions. The knowledge base is organized and tagged in advance, allowing the AI system to quickly retrieve relevant solutions during client interactions. This preliminary preparation reduces processing time during actual issue resolution while maintaining high accuracy through comprehensive natural language analysis
Solution Approach 2:
The system implements feedback mechanisms where the AI learns from successful issue resolutions and refines its natural language processing models. This continuous feedback loop improves issue identification accuracy over time while the system optimizes processing pathways to reduce response times based on learned patterns from previous interactions
Data Source
AI summary
A system for artificial intelligence assisted first interaction resolution in a contact center system according to an embodiment includes analyzing an interaction between the artificial intelligence system and an end user of the contact center system using natural language processing to identify a user issue to be addressed, retrieving possible solutions to the user issue from a knowledge base, providing the end user with a most likely solution to the user issue based on a respective accuracy score of each possible solution, wherein each accuracy score is indicative of a number of times the respective possible solution has successfully resolved the user issue, and providing the end user with one or more options to receive an agent-provided solution to the user issue from a contact center agent in response to determining that the most likely solution to the user issue is unsuccessful in resolving the user issue.