Airline-Data-AnalysisMarch 24, 2025 ยท View on GitHubThe dataset is from a US Airline Passenger Satisfaction survey. I have used data to allow customer profiling via different age groups. Overview: Firstly we analysed our dataset and pointed out factors on basis of whom we could profile our customers. Age, gender and type of customers were the three facotrs. We drilled down on the Age factor, and using an overview we realised how our customers are spread. Age Groups 20-60 Analysis Part 1: Through overview it is quite evident that most of our customer groups are in the range of 21 to 60 years old. Hence we need to make sure as an airline compnay that our most frequent customers are the most satisifed. We looked at leg room and how that affected the satisafaction of our customers. We can clearly see that for leg room>3, more people are satisfied. Age Groups 20-60 Analysis Part 2: Next we looked at few more factors for our customer groups are in the range of 21 to 60 years old. Ease of online bboarding and booking was an area that again showed that for hugher ease, there was higher satisfibalitiy. Age Group Under 21: Moving on the next highest segment, under 21. These are most influnced by In flight entertainement and Wifi services. Hence to see to what extent the influence exists, we checked the ratings against satisfibaility. And a similar trend of being more satisifed for higher levels of these factors existed.