5pages report on marketing analytics : Airline Satisfaction * https://www.kaggle.com/johndddddd/customer-satisfaction * Here is the data set
Use my materials only, no outside sources
*660pre.docx is to show you how to explain the graphs and stuff.
My goal is to understand and figure out the customer’s satisfaction and to find out the relationship to improve it and maintain customer satisfaction.
There 129880 observations in the data set. And from the data set, I only chose 7 variables: customer ID, satisfaction, gender, customer type. Type of travel, and age. The y-variable is the satisfaction, and the x-variables are gender, customer-type, and the type of travel because they are the discrete variables.
From the observations, 54% of the customers (71,087) are satisfied with the airline, 45.3% (58,793) are neutral or dissatisfied with the airline.
If we look at the satisfaction by gender, we found that (65,899) 50.7% are female and (63,981) 49.3% are male.
Then we look at the customer type, we found that disloyal customer are 18.3%,23780. Loyal customers are 81.7%, 106100.
Then we look at the type of travel, we can see that business travel are 69.1%, 89693. Personal travel is 30.9%, 40187.
Here is my tree model. Node 0 is whether the customer is satisfied or neutral or dissatisfied. Then I split into node 1 which is the royal customer. Number blah blah
and node 2 which is disloyal customer. Number blah blah.
From the loyal customer, node 3 represents the female customers which have Number blah blah
And node 4 represents male customers which have Number blah blah
Then I categorized both female and male customers into personal and business travel type.
Node 5 is the personal travel for female. Number blah
Node 6 is the business travel for female.
Node 7 is the personal travel for male.
Node 8 is the business travel for male.
These tables are the most significant information for the airline company. As we can see, the customer type has 44.3%
The gender variable has 32.1%
And the type of travel is the most important factor because it has 100% independent variable importance.
From the terminal node identifier satisfaction crosstabulation table,
Node 5,6,8 have good experience with the airline service
node 2 and node 7 have the most neutral or dissatisfied.
Node 2 number blah
Node 7 number blah
Gender, customer- type, and type of travel have a strong effect on satisfaction.
Since Node 2 and 7 have the most neutral or dissatisfied experience with the airline service, they are the main target for the airline. The airline company will need to improve their services in order to gain their trust. More, they can do things such as creating a good image for the company. Getting feedback from passengers can also improve satisfactions.
Marketing Analytics Airline Satisfaction
to understand the customer’s satisfaction and to find out the relationship to improve it and maintain customer satisfaction.
|Variables||Discrete or continuous|
|Type of travel||Discrete|
|Y variable||X variable|
|Satisfaction||Gender, customer- type, and type of travel|
|X Variables have strong effect on Y variable Node 2 and 7 are the main target Base on passengers’ need to improve services|