Chatbot Self-Learning Algorithm for Customer Issue Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern businesses face challenges in efficiently addressing customer issues due to high volumes of unpredictable calls, leading to a need for automated systems that can quickly determine and resolve customer queries without relying on traditional call centers.
Innovation Solution
A self-learning algorithm that tracks subscriber account activities, creates hypothetical issues based on usage patterns, and provides a GUI-based chat option with a chatbot to communicate and suggest solutions, minimizing user effort and enhancing issue resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional call centers are used to resolve customer issues, then customer service can be provided, but the system becomes complex and cannot handle high volumes of unpredictable calls efficiently
Solution Approach 1:
The system enables customers to self-diagnose and self-resolve issues through the chatbot interface. The chatbot autonomously analyzes customer descriptions, identifies potential issues, and provides solutions without requiring human agent intervention, thereby increasing productivity while reducing system complexity
Solution Approach 2:
The patent replaces the mechanical call center system with an automated chatbot-based system. The chatbot uses natural language processing and machine learning algorithms to handle customer queries, substituting human agents and complex call routing mechanisms with an automated software solution that can scale efficiently
2Productivity
If automated systems are implemented to handle customer queries, then productivity increases, but the ease of operation decreases due to limited human interaction
Solution Approach 1:
The chatbot serves as an intermediary between customers and the issue resolution system. It translates natural language customer queries into structured problem descriptions, maintains conversation context, and presents solutions in an easy-to-understand format, thereby bridging the gap between automated processing and user-friendly interaction
Solution Approach 2:
The system performs preliminary analysis of customer queries to identify potential issues before full resolution is provided. The chatbot proactively suggests possible problems based on initial customer descriptions and guides users through diagnostic steps, making the interaction process smoother and more intuitive
Data Source
AI summary
A system, method, and computer program product are provided for automatically determining customer issues and resolving issues using graphical user interface (GUI) based interactions with a chatbot. In operation, a system implements a self-learning algorithm that keeps track of all activities and usages associated with a subscriber account. Further, the system prepares storylines based on the activities and usages. The storylines are used to automatically create hypothetical issues that a subscriber associated with the subscriber account may be facing. The system also provides a GUI based chat option to the subscriber to communicate with a chatbot. The GUI based chat option includes a graphical representation of created hypothetical issues, and also suggests solutions to the hypothetical issues.