Determining the important factors that influences the customer or passenger satisfaction of an airlines using CRISP-DM methodology in Python and RapidMiner.

Know exactly what to press or say to get a human operator

Internship project that dealt with Customer Satisfaction/Dissatisfaction Analysis for a major Technology giant. Converted Voice transcipts to text, performed Text and Sentiment analysis to produce results.

Analyzing and Monitoring Net Promoter Score (NPS) Performance for Healthcare Companies using SQL and Power BI

Factors that lead to customer satisfaction for an Airline. Model built using Python and trained using Amazon SageMaker.

Self case study 1

A rating system that can be integrated with any customer satisfaction and feedback system

A comprehensive project predicting flight prices and customer satisfaction using machine learning models, deployed through interactive Streamlit apps.

This project focuses on predicting passenger satisfaction and loyalty within the airline industry using data mining techniques. The analysis is conducted using the Orange Data Mining tool, with a primary emphasis on understanding and predicting customer satisfaction and churn risk.

Sentiment analysis and forecasting on fast food restaurants using R and Shiny

Use Twitter text analysis to measure client satisfaction

cryptotoken

An open-source customer satisfaction dashboard

VoiceNote for Business is an innovative solution to revolutionize business communication, particularly for rural and multilingual markets. This project enables businesses to process customer queries via WhatsApp voice notes, breaking down language and technological barriers.

Digital Marketing (web analytics and clickstream tracking) projects, and UX (research) projects.

Predicting customer satisfaction for purchases made in Brazilian e-commerce.

Collection of interactive Tableau dashboards showcasing data visualization expertise across entertainment, real estate, and aviation industries. Features Netflix content analysis, housing market trends, and British Airways customer satisfaction metrics with advanced filtering and drill-down capabilities.

This project to determine customer satisfaction towards an airline using SQL Server

Call Centre Trends Visualising customer and agent behaviour.