Sentiment Analysis System for Automated Support Ticket Prioritization
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Solution Overview
Problem
Existing game development systems face inefficiencies in processing support tickets, usability improvement comments, and product feedback due to the lengthy and time-consuming process of determining priority and urgency, and the need for comprehensive questionnaires that may not capture all necessary details.
Innovation Solution
A video and audio sentiment analysis system that captures user interface recordings, audio streams, and user input to identify baseline characteristics, perform sentiment analysis, and automatically generate support tickets, prioritizing issues based on urgency and providing relevant training material, thereby streamlining the submission process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of support tickets is performed to determine priority and urgency, then accurate prioritization is achieved, but the process becomes lengthy and time-consuming
Solution Approach 1:
The system enables automated self-service prioritization by analyzing support tickets, user data, and scenario information without requiring manual reviewer intervention. The automated analysis determines priority and urgency levels, freeing reviewers from routine classification tasks while maintaining consistent prioritization standards across all tickets.
Solution Approach 2:
The patent replaces the mechanical manual review process with automated computational analysis. Machine learning models and natural language processing algorithms analyze ticket content, user behavior patterns, and scenario data to determine prioritization, substituting human cognitive processes with automated systems that operate faster and without fatigue.
2Loss of information
If comprehensive questionnaires are required for each issue submission, then detailed information is collected, but the submission process becomes burdensome for users
Solution Approach 1:
The system performs preliminary data collection and analysis automatically before the user completes the full questionnaire. By pre-gathering available information from user profiles, device data, and contextual sources, the system reduces the burden on users while ensuring comprehensive information is ultimately captured for support ticket creation.
Solution Approach 2:
The system provides dynamic feedback during the questionnaire process, adapting subsequent questions based on earlier responses and automatically populated data. This feedback mechanism guides users through only the necessary fields, reducing perceived burden while maintaining information completeness through intelligent question routing and conditional logic.
3Loss of information
If detailed questionnaires are required for each submission, then comprehensive details are obtained, but the system cannot efficiently process the volume of feedback
Solution Approach 1:
The system extracts and separates critical information elements from the comprehensive questionnaire data, identifying and prioritizing the most relevant details for support processing. By extracting key information automatically through NLP and data analysis, the system processes detailed feedback efficiently without requiring manual review of every questionnaire field.
Solution Approach 2:
The patent segments the comprehensive questionnaire into multiple processing stages, with different levels of analysis applied to different data elements. Critical information receives detailed automated analysis, while less critical fields are processed through summary statistics or routing rules, enabling efficient handling of complete detailed feedback through hierarchical processing.
Data Source
AI summary
Some embodiments of the present disclosure include a video and audio sentiment analysis system. The video and audio sentiment analysis system can capture video and audio of workflows while a game developer is working on a game development tool. The video and audio sentiment analysis system can use speech-to-text transcription to log requests and suggest help for a game developer. The video and audio sentiment analysis system can capture the recordings for a time period before the error occurs to provide the support team with a recording of the steps that led to the concern. The video and audio sentiment analysis system can package the video stream, transcription of audio, and user interface recordings to the development team such that the support system can replay the scenario of the user to get a full picture of the user's actions and concerns.