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For an organization which is customer centric and generates revenue based on its customer service focused operations ,  we all know how important is customer retention year on year.  In order to retain our  customers , We   need to   stop the customers that are leaving the organization which in turn called as “customer churn”. In this case study we have considered a Telecom service provider  XYZ  and provided solution on how to retain its customers.

Identifying customers who are most likely to cancel the subscription. Recognizing areas effecting customer churn. Finding out most important factor that contributes to the high retention rate. Analyze the probability of churn.

Trained data to identify customer who are likely to or already have churned. Taking in to account is past 5 years of data  for Analysis.

Built  Churn analysis  that basically helps  XYZ to  understand why  there is  drop in customers . Forecast Customer churn for next year using Tableau inbuilt forecast model and help the marketing team act accordingly.

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Churn Rate Lost Customers Total Customers
Exit
O
Churn
Rate
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LOST CUSTOMERS
TOTAL CUSTOMERS
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2,650 (26.5%)
Customers Churned
$ 528,016
in Lost Revenue

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OUTCOME     This churn analysis solution provided benefits that helped the client to:

Access all the relevant data seamlessly and quickly Segment the customers based on behavior and demographics to improve retention Deliver tailored promotions and offers to positively influence their behavior Minimize acquisition costs and increase marketing efficiency Keep customers engaged and loyal

10,000
Total Customers
Contract Type
$ 1,725,165
Total Revenue
Month-to-month
2,650 (26.5%)
Customers Churned
$ 528,016
in Lost Revenue
7,350 (73.5%)
Customers Stayed
Female
0.4800
$ 1,197,149
in Retained Revenue
Churn Customer Profile
*Select State to Filter*
Male
0.4977
Two Year
One year
500
Payment Method
1000
1500
2000
Electronic Check
2500
*Select Icon to Filter*
$100,000
Nonbinary
0.0223
$150,000
o
80
200
100
400
Mailed Check
Bank Transfer(automatic)
Credit Card (automatic)
600
800
1000 1200
1400
280
1600
300
o
6
1
18
120 140 160 180 200 220 240 260
Monthly Charge Distribution (USD)
12
24 30 36 42 48 54
Tenure Distribution (Months)
60
66
72
78
$0
10
20
$50,000
30
Income Range Distribution
40
50
60
Age Distribution
70
80
90
EB Customer Churn Report Yoy_Churn_Retained cohort_analysis

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This churn analysis solution provided benefits that helped the client to :       Access all the relevant data seamlessly and  provided insights on customer churn.      Segment the customers based on behavior and demographics to improve retention .      Deliver tailored promotions and offers to positively influence their behavior .      Minimize acquisition costs and increase marketing efficiency .

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