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

Self case study 1

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

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

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.

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

An open-source customer satisfaction dashboard

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

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

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

Use Twitter text analysis to measure client satisfaction

cryptotoken

Predict whether a future customer would be satisfied. Part of Samsung Innovation Campus Program.

Predicting Customer Satisfaction with Hybrid Basic Filter-Based Feature Selection

Simplezat

This repository contains a PowerBI dashboard to analyze an airline satisfaction survey.

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