AI-Powered Customer Sentiment Analysis

Project Overview

As the Technical Lead for this project, I oversaw the development of a comprehensive sentiment analysis system that processes customer feedback from multiple channels, including support tickets, social media, and direct surveys.

Technical Challenges

One of the major challenges was handling feedback in multiple languages and dealing with industry-specific terminology. We implemented a custom NLP pipeline with domain adaptation techniques to overcome these challenges.

Architecture

The system uses a microservices architecture with the following components:

Data ingestion services for various channels
NLP processing pipeline based on transformer models
Real-time analytics dashboard
Automated reporting and alerting system

Results

The implementation of this system led to:

35% faster response to emerging customer issues
Identification of several product improvements
Better allocation of support resources based on customer sentiment trends

Technologies Used