Vistico Airline Customer Satisfaction Data Report Using Tableau

Introduction:

The objective of this report is to analyze customer satisfaction levels based on a data set from airline passengers.

The dataset includes information such as Gender, Customer Type, Age, Type of Travel, Class, Flight Distance, Inflight wifi service, Departure/Arrival time convenience, Ease of Online booking, Gate location, Food and drink, Online boarding, Seat comfort, Inflight entertainment, On-board service, Leg room service, Baggage handling, Checkin service, Inflight service Cleanliness, Departure Delay in Minutes, Arrival Delay in Minutes, and satisfaction.

By analyzing this data, the aim was to identify the areas in which the airline can improve to ensure customer satisfaction.

Overall Customer Satisfaction:

The overall customer satisfaction is at 43% which is a negative satisfaction rate as it is below 50%. On exploring the data further, it unveiled other crucial insights that can be used to improve customer satisfaction rates.

Key findings:

1. Gender-based satisfaction

Both genders reported a significantly low level of satisfaction. With Males having 49.3% and Females having 50.7%. Therefore, ruling out gender as a factor contributing to the low level of satisfaction.

It is important to improve the quality of the service to ensure satisfaction among both genders.

2. Customer Type Satisfaction

According to the customer type, both loyal and disloyal customers reported 18.27% and 81.73% respectively. The loyal customers appear to be more satisfied than the disloyal customer.

The airline should focus on retaining loyal customers while addressing the needs of the disloyal customers to improve the overall satisfaction of both customers.

3. Age-based satisfaction

There was no correlation between age and satisfaction. Ages across reported a significantly low satisfaction rate. The airline should consider tailoring its services and addressing the specific needs and preferences of different age groups to enhance customer satisfaction.

4. Type of travel

Business travelers demonstrated a higher level of satisfaction (69%) compared to Personal travelers (31%)

Tailoring the services and the amenities to their specific needs can increase overall satisfaction.

5. Class-based satisfaction

Business class expressed a high level of satisfaction (47.8%) as compared to its counterparts. The eco and eco plus classes reported a satisfaction level of (44.99%) and (7.21%) respectively.

6. Average delay and departure in minutes

The average delay and departure is 15 minutes.

Please note that Data storytelling and reporting vary across organizations and companies, with each adopting its own frameworks. In this blog, I aim to provide insight into my personal approach, although it may differ from others.

In the course of this project, I utilized a combination of Kaggle, Excel, PostgreSQL, and Tableau. Excel served as my primary tool for data cleaning, while PostgreSQL and Looker Studio were employed for exploratory purposes and data visualization, respectively.

I like to compare the process of data analysis to dating. Just as spending more time with someone allows you to know them better, spending time with a dataset yields a deeper understanding.

Therefore, regardless of the specific tools at hand, my initial step is to upload the dataset to Google Sheets (Excel). During this stage, my focus is on observation and note-taking rather than attempting to fix any issues.

Following this initial phase, I determine the most suitable tools for the task at hand. Depending on the circumstances, I may choose to clean the data in Excel or employ Python or SQL for data exploration and manipulation. The choice ultimately depends on personal preference and what works best for the specific project.

For the project at hand, I opted to explore the data using PostgreSQL. If you’re interested, I can certainly provide query snippets for future projects upon request.

Happy coding!