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MKTG 720, Customer Analytics  Students are to submit response in WORD file electronically via Blackboard.  Submission should include Students Name and Course Number.  Submissions must follow the...

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MKTG 720, Customer Analytics
 Students are to submit response in WORD file electronically via Blackboard.
 Submission should include Students Name and Course Number.
 Submissions must follow the rules of basic writing fundamental and typed in a 12-point
font, in 1.5 line spacing.
 Include all references (if you use any) in a separate Reference Page.

Customer retention.
In this assignment, students are to build a model best predicting the behavior to retain customers.
You can analyze all relevant customer data and develop focused customer retention programs.
Each row represents a customer, each column contains customer’s attributes described on the
column Metadata. The data set includes information about:
 Customers who left within the last month – the column is called Churn
 Services that each customer has signed up for – phone, multiple lines, internet, online
security, online backup, device protection, tech support, and streaming TV and movies
 Customer account information – how long they’ve been a customer, contract, payment
method, paperless billing, monthly charges, and total charges
 Demographic info about customers – gender, age range, and if they have partners and
dependents
Students are to try different models (with different combinations of variables sets), and select the
est model based on Decile tables. For example, the best model will have a highest average
Churn rate in Decile 1.
Submission:
1) Model comparison on Decile 1 Chur rates (include for all models you developed)
2) Decile table for the best model
3) Training Model Results table for the best model
4) Decile 1 Profile for the best model (Means of all the variables used in the model)
Telco Customer Churn
Assignment #4


MKTG 720, Customer Analytics
Focused customer retention programs
 customerID
 gender (female, male)
 SeniorCitizen (Whether the customer is a senior citizen or not (1, 0))
 Partner (Whether the customer has a partner or not (Yes, No))
 Dependents (Whether the customer has dependents or not (Yes, No))
 tenure (Number of months the customer has stayed with the company)
 PhoneService (Whether the customer has a phone service or not (Yes, No))
 MultipleLines (Whether the customer has multiple lines r not (Yes, No, No phone service)
 InternetService (Customer’s internet service provider (DSL, Fiber optic, No)
 OnlineSecurity (Whether the customer has online security or not (Yes, No, No internet
service)
 OnlineBackup (Whether the customer has online backup or not (Yes, No, No internet
service)
 DeviceProtection (Whether the customer has device protection or not (Yes, No, No internet
service)
 TechSupport (Whether the customer has tech support or not (Yes, No, No internet service)
 streamingTV (Whether the customer has streaming TV or not (Yes, No, No internet service)
 streamingMovies (Whether the customer has streaming movies or not (Yes, No, No internet
service)
 Contract (The contract term of the customer (Month-to-month, One year, Two year)
 PaperlessBilling (Whether the customer has paperless billing or not (Yes, No))
 PaymentMethod (The customer’s payment method (Electronic check, Mailed check, Bank
transfer (automatic), Credit card (automatic)))
 MonthlyCharges (The amount charged to the customer monthly — numeric)
 TotalCharges (The total amount charged to the customer — numeric)
 Churn ( Whether the customer churned or not (Yes or No))
The raw data contains 7043 rows (customers) and 21 columns (features). The “Churn” column is
our target.

Data source: https:
www.kaggle.com
lastcha
telco-customer-churn
Usage: Only for class assignment. Not for publishing research based on this data.
https:
www.kaggle.com
lastcha
telco-customer-churn



MKTG 720, Customer Analytics
 Students are to submit response in WORD file electronically via Blackboard.
 Submission should include Students Name and Course Number.
 Submissions must follow the rules of basic writing fundamental and typed in a 12-point
font, in 1.5 line spacing.
 Include all references (if you use any) in a separate Reference Page.

Customer satisfaction.
In this assignment, students are to build a model best predicting the customer satisfaction.
Simulated data represents customer responses to a survey about their satisfaction with different
aspects of their recent visit to an amusement park. Variables in the model are:
weekend: as the visit on a weekend
num.child: how may children were in the party
distance: how far did the party travel to the park
ides, games, wait, clean; performance rating (1-100)
overall: satisfaction rating (1-100)
Students are to try different models (with different variables), and select the best model based
on R2 and RMSE.
Submission:
1) Model comparison on R2 and RMSE (include for all models you developed, list the
variables included in the model)
2) Training Model Results table for the best model – along with interpretation

Assignment #5
assignment41-rhwtppa1.pdf assignment4data-is3kxkyu.csv assignment5-vjfxej1z.pdf assignment5data-nuqn4xz5.csv
Answered Same Day Dec 17, 2021

Solution

Swapnil answered on Dec 17 2021
151 Votes
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"dataset=pd.read_csv('data.csv')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(7043, 21)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset.shape"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"