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5pages report on marketing analytics : Airline Satisfaction   * https://www.kaggle.com/johndddddd/customer-satisfaction * Here is the data set

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*660pre.docx is to show you how to explain the graphs and stuff.

Next slide

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.

Next

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.

Next

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.

Next

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.

Number blah

Node 7 is the personal travel for male.

Number blah

Node 8 is the business travel for male.

Number blah

Next

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.

Next

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

Next

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

Research purpose

to understand the customer’s satisfaction and to find out the relationship to improve it and maintain customer satisfaction.

Data analysis

VariablesDiscrete or continuous
Customer IDcontinuous
satisfactionDiscrete
genderDiscrete
Customer typeDiscrete
Type of travelDiscrete
ageContinuous
Y variableX variable
SatisfactionGender, customer- type, and type of travel
Frequency Table
Marketing Implication
X Variables have strong effect on Y variable Node 2 and 7 are the main target Base on passengers’ need to improve services

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