Support Ticket Classification & Prioritization System

Introduction

This project implements a Machine Learning-based Support Ticket Classification and Prioritization System designed to automate customer support workflows. The system processes unstructured ticket text, categorizes tickets into relevant departments, and assigns priority levels based on urgency and impact.

The goal is to improve response time, reduce manual workload, and optimize support operations.

Objective

The system is designed to:
Automatically classify support tickets into categories.
Assign priority levels based on issue severity.
Reduce manual ticket triaging.
Improve operational efficiency.
Enable data-driven support management.

ML & NLP Techniques Used

Text Cleaning & Preprocessing
Tokenization
Stopword Removal
TF-IDF Vectorization
Machine Learning Classification (e.g., Logistic Regression / Naive Bayes)
Priority Logic Based on Keywords & Severity Indicators

How the System Works

Incoming support tickets are cleaned and preprocessed.
Text data is converted into numerical features using TF-IDF.
A trained classification model predicts the ticket category.
A priority score is assigned based on urgency keywords and impact.
Tickets are automatically sorted for faster resolution.

Business Impact

This system helps organizations:
Reduce manual ticket sorting effort.
Improve response time.
Ensure high-priority issues are handled first.
Maintain consistency in ticket handling.
Gain insights into support trends.

Explain For Non-Technical Stakeholders

For a Support Manager

This system automatically organizes incoming support tickets by category and urgency. It ensures that critical issues are handled first and reduces the manual effort required for ticket triaging.

For a SaaS Founder

The solution improves operational efficiency by automating ticket classification and prioritization. It reduces response delays, improves customer satisfaction, and allows support teams to scale without increasing headcount.

For a Client Optimizing Operations

The system analyzes customer complaints in real time, identifies issue type and urgency, and routes them appropriately. This reduces bottlenecks and ensures faster problem resolution.

Conclusion

The Support Ticket Classification & Prioritization System demonstrates how NLP and machine learning can optimize customer support workflows. By automating ticket categorization and prioritization, the system enhances efficiency, reduces operational costs, and improves overall service quality.