Sentiment Analysis Application

Overview

The Sentiment Analysis Application is an internal tool designed to classify the sentiment of customer support tickets stored as CLOB data. Prior to migrating to ServiceNow we were using an internal tool that had no API access so we had to place mock data in an Oracle Database. The workflow helps identify support patterns and trends, enabling proactive improvements in customer service.

Features

• Automated sentiment classification of ticket descriptions
• Analysis of large-scale CLOB data
• Pattern recognition for support trends
• Integration with internal reporting tools

Tech Stack

• Node.js
• Natural Language Processing (NLP)
• Database with CLOB support
• Internal analytics/reporting tools

Challenges

Processing and analyzing unstructured CLOB data at scale required efficient parsing and NLP techniques. Ensuring accurate sentiment classification and integrating results with existing reporting systems were key technical challenges.

Lessons Learned

This project highlighted the importance of automated analysis in large-scale support environments. By surfacing sentiment trends, the tool enables more targeted and effective customer service strategies.