Contents

Introduction

Purpose

Task 1 – Churn Analysis

Task 2 – Cross-selling and Up-selling

Task 3 - Customer Segmentation & Customer Lifetime Value

Analytics

Introduction

A telecommunications company is concerned about the number of customers leaving their Services. They need to understand who is leaving and why they leaving. The company's customer database includes customers who churned within the last month. In addition to information on Churn (Yes/No) for each customer, the data contains information on provided services in variables Est_Income , Car_Owner , Usage , Age group , RatePlan , LongDistance ,International Calls ,Local Calls, Dropped Calls. It also contains customer account information in variables Paymethod, LocalBilltype, LongDistanceBilltype. Finally, customer demographic information is contained in variables gender, Status, Dependents.

Purpose

The purpose of this study is, with the help of Watson Analytics examine why

customers are not used the connection of Bits Telecom Company, which

factors are influence the churn. Also see the cross selling and up-selling, also

focus on profitability and investment and find out the way for better results.

Task 1 – CHURN ANALYSIS

1.1– With the help of the Watson Analytics first do Exploration of data.

When Explore the data some starting points are Suggest by Watson.

Purpose-The purpose of this section to find out what factors influence

churn and why

What the breakdown of the number of contract by Churn?

Explore the data of contract by churn,breakdown of…in the search

box and at the window the most relevent options are shows.now

choose one option and click on it.

According to the company’s contracts the churn equally distributes.

-We can add new columns by the option “add new column”

Add a column Age group (6 type of age group)

By the visualization option can change the visualization.

The area chart shows that all the age groups are interested in company’s

contracts, but according to churn the contracts are equally popular in all the

age groups in cancelled customers and in the current customers the

popularity of contracts in two age groups is less, but all over users are equal

to canceled.

Change the visualization

- choose the bar chart.

- This chart shows clearly that the two year contract is used by only 4

age groups and month to month and one month contract are again at

equal level. Focus on Two year contract because the current customers

of this contract are not greater then cancelled customers.

Change the visualization(Line Chart)

-change the visualization option.

-Pin the chart.

- This chart shows the variation of the rate plan popularity between

current and cancelled customers.(red line)current customers, only

month to month contract raise other two are highly decrease but

overall the current customers whom used the rate plans are very less

then to cancelled.

First focus on Two year rate plans.

-Three types of customers. The status are-

Married

Single

Divorced

Which category is interested in two year rate plans -

- Only 13 customers are using the Two year plan others already canceled

it.

The Est_Income by the two year plan.

Filter – two filters apply here, that means once you choose any

field as a filter then furthers all the Exploration proceed

according to that filter. Here I select Contract (Two year)

because we analyze the two year contract popularity and other is

rate plan (all).

- Choose the filter option.

- Add a filter.

- Conditions.

- The Est_income is only 319.7k by the current customers and by the

canceled customers 24.67m. the conclusion is because of churning

the company has vey big loss.

There are 4 type of rate plans in company

- Which rate plan is used broadly in Two year contract?

- In the line chart, the current customers only use RT1, RT3, RT4 and

canceled customers used all 4 plans. The current customers are very

less.

1.2 Prediction – Which fields are drives the churn.

All the factors, which affect the churn

The Top Predictors of Churn spiral chart shows the Combination model and

various Two Field models that are more predictive of customer churn than

One Field models .The predictive strength of one field is 73% shows by the

BAR chart and the driving fields are contract and dependents.

The combination of the fields, the predictive strength is 74% and driving

factors is (contract and age group), (age group and dropped) shows by the

BAR chart…

There are three types of contract in company Month to Month, One year,

Two year

In area chart, according to age group churn position is define. Green and

Blue color area define (yes/no).

As the record the month to month contract has used more then one year and

two year contract. The age group 36-45 used this contract broadly and

greater number of current customer who is used month to month pack.

Churn ratio going down by one year and two year contract and very less

number of current customers interested in two year contract.

Now focus on Two year contract, which rate plan is used mostly in two year

contract? We should modify the two year contract.

If we see the rate plan history then by line chart it is clear that the scope of

success of rate plan 4 and but at the current time only three rate plan is used

in two year contract so the condition is very poor at that time. First talk

about the rate plan 4 applies some discount and offers for the users. You can

add some policy to attract the customers for use that service broadly.

For example check which status categories use the Two year plan and their

dependents.

The divorce status not uses the Two year plan and haven’t dependents and

The Married and single customers used it and they have dependents.

Now for example can offer them like “with one connection another

connection free” etc.

Other hand for divorced can offer like discount policy.

1.3 Assemble -Create the dashboard for the clear view of data and

create a story.

To create a dashboard, three types of templates here

Single Page,

Tabbed,

Infographics.

(Tabbed->Freeform->create)

What do you want to assemble, write in search box then it is

create in dashboard. There are 4 options for a single view box-

Delete,

Duplicate-to create a duplicate tab,

Edit Title,

Visualization.

Select column chart

Dashboard properties-

Themes- apply a theme.

General Style- Change the style.

Pinning Service – Pin (save) the tab.

Slide Show

Select BETA slide show option.

Select a Template.

Create.

Open pin Charts.

Drag the chart at tab.it will be create at dashboard.

Adjust the chart in the dashboard.

Allow full screen.

Conclusion is, in the two year contract, very few customers interested. It is

affecting the churn. So focus on two year contract and in this contract, the

Rate Plans, to increase the customers.

Task – 2 Cross-Selling and Up-Selling

2.1 EXPLORE the data,

What is the breakdown of Usage by Long distance bill type and local bill

type? (In the long distance bill type 2 categories are Standard and

International discount and in Local bill type 2 categories are Budget

(postpaid) and free local (prepaid)).

According the data the international discount bill type

Customers are use this services not as much of. The other

category used broadly.

The purpose of this section is to create new ideas and How to implement those ideas,

for the better Income and selling. In this section we focus on Bill types and usage of

the customers and analyze that how to get more income in business.

Now focus on International discount.

Add a filter (LongDistanceBilltype -> Select International

Discount)

The average of total usage, 16.13% utilize by free local bill type

service and 28% utilize by Budget.

Means, Budget category use the service broadly.

Now see the difference according the calls type.

Add another filter “Usage”.

Three types of calls system are present in company.

Local Calls

Long distance Calls

International Calls

Here we analyze that which type of calls are more utilize and

which payment method they use.

Three facilities of payment

CC (Credit card)

CH (Check)

Auto (Cash)

Local Calls

Budget (Postpaid) bill type Category utilize Local calls higher then Free

local (Prepaid).

And the pay methods of this category.

Add 3 filter local bill type, select free local (prepaid).

They are use Auto and CC mostly and CH is not much popular.

So, for this category can offer some policy to CC company to increase profit

and CH category like banks here we can offer the banks others beneficial

plans for example if bank offer their customers some plans including our

company policy to promote telecom company and also with CH facilities

then we provide the connections free of cost or with discount.

Long Distance Calls

Almost use by both category. Now focus on free local (prepaid).

The pay methods of this category.

Add 3 Filter Local Bill Type, select Free local (prepaid).

Auto (Cash) method is popular, should add some plan in top ups.

For example- When Customers buy the pack then offer them same type of

pack with extra balance or 3G balance but price is high.

CH (check), collaborate with banks and apply some other policy to promote

this service.

International Calls

Postpaid Connection Customers utilize international calls broadly and

prepaid customers are not use to much. Now focus on free local type

(prepaid).

The pay methods of Free local Bill type customers.

Add 3 filter Local Bill Type, select Free local (prepaid).

Only CC customers use broadly the service.

Auto customers very less, offer some discount, if they choose cash payment

option. CH (check), collaborate with banks and apply some other policy to

promote this service.

Conclusion is, Prepaid Connection is not using the services broadly. In the

Payment methods we should focus and then add some policy to promote the

company.

2.2 PREDICTION

The main focus of the business owner at income.

Select the target.

Top Predictors of Estimated income are Local Calls and 8 others. Shows in

decision tree.

Top Decision rules, predicting Estimated income to be high.

The Local calls highly influent the income. Also long distance calls and local

bill type, as seen in exploration part should focus on these factors.

2.3 ASSEMBLE

Create a dashboard and story.

Create full story of analysis for clear view.

Task 3 - Customer Segmentation & Customer

Lifetime Value Analytics

3.1 EXPLORE the data,

If divide the customers age group according to income. The estimation is

that highest income by 16-25 age group customers.

Customers are base of the any business and for the better result the long term

business relationship with customer is important. In this section we focus on

customer’s priority according their involvement in our company also plan some

offers for the users whom used our service from long time according their needs

and status.

Now observe the dependents of the particular age group. As shows in

tree map chart that age group which has no dependents, the income is

high and other which have dependents, the income is less.

So, focus on that group which have dependents here if offer that groups

some kind of plan like “connection free” or some application like, “at one

connection discount for other connection”.

Conclusion is, the customers with dependents, here better scope of selling

company’s plans.

Other hand, the income is high by customers who haven’t car.

What is the breakdown of estimated income by car owner?

Conclusion is, these customers are very important for company here we

should offer them some special offers, it is beneficial for company. The car

owners (think that they can afford some expensive offers so, can offer them

some expensive plans with long validity).

3.2 PREDICTION –

Top predictors of car owner – the top predictor is estimated income and 6

other input.

Decision tree shows all inputs.

Highest decision rules for that that haven’t car with

statistical details.

Highest Decision rules for who have car.

Top predictor is estimated income for car owner as discussed in exploration

part we should focus on both type of customers.

3.3 ASSEMBLE – create Slide Show.

Conclusion is, Income is high by those customers whom haven’t car. They

are important customers for company so we should offer them some good

plans.