Airline Satisfaction

Introduction

Welcome to my Airline Satisfaction analysis. Every day, 2.9 million passengers fly in and out of U.S. airports [1 ]. My experience in the industry made me quite curious to explore a public dataset of customer survey responses. The following analysis was created as my first capstone project for the Springboard Data Analytics Certification.

Phase 1: Ask

What is the problem I am trying to solve?

To capture as many of the 2.9 million daily US passengers as possible, airlines are expected to run a reliable operation and maintain high customer satisfaction. Happy customers translate to more revenue and more customers. The key to a happy customer is understanding their expectations and needs throughout the experience.

• The business task is to identify customer demographics and key drivers of dissatisfaction.

• What is the customer demographic?

• Where does the business excel?

• How can the airline improve customer satisfaction?

Phase 2 & 3 : Prepare and Process

The data has been made publically available through John D on Kaggle. This dataset was made available through the Public Domain on Kaggle with no associated license. It should be considered fictional and not relied on for current insights to the industry.

Upon initial exploration of the data, the dataset contains almost 104,000 rows of customer survey responses. There are 25 fields including data points like age, satisfaction score, flight mileage, delay in minutes, and class of travel. After preparing and exploring the data, I chose to utilize Tableau Desktop to conduct my analysis and create compelling visualiations.