Overview
Appen Enhances Contributor Satisfaction with ML-Driven Ticket CategorizationProvectus |
Analytics & Modeling - Machine Learning Platform as a Service (PaaS) - Application Development Platforms | |
Cement Education | |
Procurement Product Research & Development | |
Time Sensitive Networking Virtual Training | |
System Integration Training | |
Operational Impact
The implementation of the ML-driven ticketing system significantly improved Appen's operations. With up to 80% of tickets being categorized and resolved automatically, the Contributor Success team was able to focus on more complex issues, resolving them more quickly and efficiently. The reduction in ticket resolution time from two weeks to less than 24 hours led to increased loyalty among the platform's best contributors. The 10% increase in satisfaction resulted in less churn, indirectly improving the overall quality of training data delivered by Appen to its clients. The team was extremely satisfied with the new system, as it allowed them to prioritize contributor satisfaction, thereby increasing their own performance and productivity and positively impacting Appen's business growth. | |
Quantitative Benefit
Reduction in ticket resolution time from 2 weeks to less than 24 hours | |
Approximately 80% of tickets are resolved automatically | |
10% increase in customer satisfaction for contributors | |