This repository contains a comprehensive suite of Python scripts and Jupyter notebooks designed for ticket analysis in the Battery Smart Driver Issues team. It includes time-based ticket tracking, category-wise issue segmentation, churn driver analysis, penalty cohort studies, and automated Slack notifications for real-time alerts.
To predict the impact of the incident raised by the customer.
Traditional NLP pipeline for classifying support tickets by issue type & urgency while extracting key entities (products, dates, complaints). Built with sklearn, regex, TF-IDF, and deployed via Gradio.
Interactive dashboard uncovering ticket trends, SLA performance and backlog risks in customer support operations using Tableau and Excel.
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