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Maven Airlines | Airline Passenger Satisfaction Report

Tools used in this project
Maven Airlines | Airline Passenger Satisfaction Report

About this project

Overview

This dashboard provides a comprehensive overview of passenger satisfaction during airline travel. It presents key metrics such as the total number of passengers, the average flight distance, and the average arrival and departure delay in minutes. Additionally, the dashboard offers insights on various factors related to passenger satisfaction, including class, customer type, travel type, food and drink options, onboard service, gender, cleanliness, check-in service, and seat comfort. By analyzing these different factors, the dashboard aims to provide a detailed understanding of the overall passenger experience and identify areas for improvement.

About the Dataset

The dataset comprises customer satisfaction ratings provided by over 120,000 airline passengers. It also includes supplementary details about each passenger's flight, type of travel, and assessments of various factors such as cleanliness, comfort, service, and overall experience.

Challenge Prompt (Recommended Analysis)

Since we don’t know whether recent demand will be long-lasting, I want to investigate how Jimmy Shoo Limited might increase the output of shoes without having to expand to a new factory.
I will use a Power BI report to answer these questions:

  1. What is the percentage of satisfied airline passengers, and does it differ by customer type or type of travel?
  2. What are the characteristics of a frequent airline passenger's customer profile?
  3. Does the flight distance impact customer preferences or travel behavior?
  4. Which factors have the most significant impact on customer satisfaction, and which ones lead to dissatisfaction?

ETL and Data Modeling

I loaded a dataset containing over 120,000 ratings given by airline passengers and assessed various factors linked to passenger satisfaction such as class, customer type, travel type, food and drink options, onboard service, gender, cleanliness, check-in service, and seat comfort. To prepare the data for analysis, I used Power Query to clean and eliminate unnecessary columns. This streamlined the dataset and made it more manageable for analysis in Power BI.

Insights

  1. Among a total of 129,880 passengers, only 44% expressed satisfaction with the airline's services.
  2. Returning customers are commonly middle-aged individuals (aged 40-59) who take medium-leg flights (ranging from 932 to 2485 miles) for business purposes and prefer to travel in business class. This group of passengers has an overall satisfaction score of 71%, although there is room for improvement in the airline's in-flight Wi-Fi service, online booking and gate location.
  3. Out of all the passengers, 70,678 individuals or 54% opt for short-leg flights that cover a distance of up to 932 miles. They usually travel in economy class and are predominantly young adults aged 20-39, as well as middle-aged people aged 40-59, with an average age of 39. Their overall satisfaction score is 63%, with various aspects that require improvement such as the quality of in-flight Wi-Fi service, entertainment, cleanliness, online booking, gate location, and online boarding.
  4. Based on these findings, it is advisable for the airline to focus on making improvements in the identified areas to improve the travel experience for passengers.

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