Data Visualization Project
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New York University *
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Course
5000
Subject
Information Systems
Date
Dec 6, 2023
Type
Pages
8
Uploaded by ChiefTigerPerson619
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;ƺƤƲŸŶũūũğğġğƞƜ ;łłńłƺƞƜŭū
Unveiling Patterns and Insights
¦©©¬5´5x{Â5- %è
±kash ±ravindh A,esingu
Rajasekhar Reddy Kalukurthi
Shri Ram Prasadh ±rumugam
Nikhil 9iyyap Raju
MG-GY 6203 A,±T± VISU±LIZ±TION FOR 9USINI4SS INTI4LLIGI4N:%I4,
Section 9, Fall 2023
Final Project - Project Proposal, 12/01/2023
2
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Đjğđtivğ:
±nalyze customer churn in a fictional telco company
,ôtôsğt °°ourđğ:
I9M :%ognos ±nalytics Sample A,ata Sets
%ontğxt:
7043 customers in :%alifornia, Q3 data
°°tôy
mkkkğôvğ
3
BƢõôôöôƲƢõôôöô
vğğġğƞƜvňňŊňğğġğw
,ôtô Uilğs
°°izğ
,ğtôils
¾¾ğlđo_đustomğr_đhurn_
Ęğmogrôphiđs
.xlsx
7043 Rows * 9 :%olumns
䚉
This sample dashboard tracks a fictional telco company's customer
churn based on a variety of factors.
䚉
Other columns include location, monthly charges, services, and
customer lifetime value.
¾¾ğlđo_đustomğr_đhurn_
lođôtion
.xlsx
7043 Rows * 3 :%olumns
䚉
This sample story shows quarterly changes of customer churn in a
fictional telco company, and which contract and location has the
highest churn in order to decide the goals for the next quarter.
䚉
The churn label column indicates whether or not the customer left
within the last quarter.
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4
BƢõôôöôƲƢõôôöô
vğğġğƞƜvňňŊňğğġğw
,ôtô Uilğs
°°izğ
,ğtôils
¾¾ğlđo_đustomğr_đhurn_
sğrviđğs
.xlsx
7043 Rows * 31 :%olumns
䚉
This sample exploration tracks a fictional telco company's customer
churn based on a variety of factors.
䚉
The :%hurn Label column indicates whether or not the customer left
within the last month.
䚉
Other columns include location, monthly charges, services, and
customer lifetime value.
¾¾ğlđo_đustomğr_đhurn_
stôtus
.xlsx
7043 Rows * 12 :%olumns
䚉
This sample data module tracks a fictional telco company's customer
churn based on a variety of possible factors.
䚉
The churn column indicates whether or not the customer left within
the last month. Other columns include gender, dependents, monthly
charges, and many with information about the types of services each
customer has.
5
,ğmogrôphiđs
mkkkođôtion & ¥¥¥opulôtion
°°ğrviđğs
°°tôtus
%ustomğr XVV,
:%ount
Gender
±ge
Under 30
Senior :%itizen
Married
A,ependents
Number of
A,ependents
%ustomğr XVV,
Zip :%ode
Population
%ustomğr XVV,
Number of Referrals
Tenure in Months
Phone Service
Multiple Lines
Internet Type
:%ontract
Paperless 9illing
Payment Method
Monthly :%harge
Total :%harges
Total Refunds
Total I4xtra A,ata :%harges
Total Long A,istance :%harges
Total Revenue
Status IA,
%ustomğr XVV,
Satisfaction Score
:%ustomer Status
:%hurn :%ategory
:%hurn Reason
BƢõôôöôƲƢõôôöô fiğğġğŠŢŠęĘĘĚĘƤ
6
±ŭūƢõôôöôŠŢŠyƲňňŊňĒđđēđƢõôôöôŠŢŠ ¥¥œ¦¥¥§¥ŠŢŠƢõôôöôŭū
°°đğnôrio 1: ÅÅnvğiling thğ %ompğtitivğ mkkkônĘsđôpğ
Identify the top 10 Zip :%odes with the highest churn.
I4xplore reasons for churn in these areas.
°°đğnôrio 3: %yĐğrsğđurity °°ôtisfôđtion ÅÅnvğilğĘ
I4xamine low Satisfaction Scores for customers with
Online Security.
Understand concerns related to the online security
product.
°°đğnôrio 2: XVVntğrnğt ,ğviđğs ÅÅnĘğr thğ uuuiđrosđopğ
±nalyze Satisfaction Scores for customers who left due
to competitor devices and product dissatisfaction.
I4valuate the performance of Internet devices.
°°đğnôrio 4:,ğđoĘing uuuonth-to-uuuonth uuuystğriğs
Investigate the trend of churn in relation to the
contract type.
I4xplore reasons behind Month-to-Month contract
churn.
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,ôtô 4xplorôtion ônĘ %lğôning:
Nikhil 9iyyap Raju
Rajasekhar Reddy Kalukurthi
,ôshĐoôrĘ ônĘ °°tory %rğôtion
:
±kash ±ravindh A,esingu
Shri Ram Prasadh ±rumugam
°°đğnôrio XVVnvğstigôtion:
°°đğnôrio 1:
±kash ±ravindh A,esingu
°°đğnôrio 2:
Rajasekhar Reddy Kalukurthi
°°đğnôrio 3:
Shri Ram Prasadh ±rumugam
°°đğnôrio 4:
Nikhil 9iyyap Raju
8
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