1) Alan analyzed customer profitability data from Pilgrim Bank and found that half of the bank's 5 million customers were unprofitable. His boss asked him to analyze whether online banking customers are more profitable to help decide whether to charge fees or offer incentives for the online channel. 2) Alan collected data on 30,000 customers including their online usage, demographics, account details, and profitability. He found the average profitability of online customers was slightly higher at $116.67 than non-online customers at $110.79. 3) While this suggests online customers may be more profitable, Alan realized he needs more analysis to determine if the difference is statistically significant and account for other customer characteristics that could

1. Pilgrm Bank (A)- Customer Profitability
Alan Green looked at a chart on customer profitability that demonstrated that half of Pilgrm banks
five million customers were unprofitable. The word of his boss, Ravi Raman who had just left his
office, lingered in his mind.
Alan we have a meeting at the end of the week with Senior management to discuss our internet
strategy. There is a substantial disagreement in our group on whether we should start charging fees for
use of the online banking channel or if we should begin customer incentives such as rebates and lower
service charges to encourage greater use of the channel. The debate really hinges on whether online
customers are indeed better customers, and if adoption of the online channel actually produces better
customers. Why don’t you spend the weekend looking over relevant data. Lets meet Monday morning
to discuss your findings.
Alan met Raines an experienced analyst for his help- I need to do some analysis to figure out if the
online customers are better for the bank and what are the implications are for our online banking
product. As a first step I was thinking about comparing balance levels between online and offline
customers. Raines said – Balances are only part of the story. If you are interested in how profitable
customers are the look at profits directly. You don’t have to use balances as proxy for profit, as
balances are subset of our profitability measure. The two are related as follows:
Profits=Balance in deposit amounts* Net interest spread + fees + interest from loans – cost to serve
Customer accounts generated three types of revenues:
1. Investment income from deposit balance – This revenue was represented by net interest
margin-the rate the bank paid on deposit account and the rate at which it was able to invest
that deposit through for example commercial and mortgage lending.
2. Fee income –Increasingly important source of revenue in light of recent decline in net interest
margins fees were variously assessed for checking accounts, late payments and overdrafts.
3. Loan interests and base lending rates-Loans were the dominant asset in bank’s portfolio and
loan interest a primary revenue source.
The relevant costs included:
1. Transaction related costs – The costs of customer interactions with banks varied. A teller
transaction was generally more costly than a transaction that utilised an electron distribution
channel such as ATM network.
2. Allocated fixed costs –The cost of indirect supporting resources such as electricity, physical
infrastructure, salaries. These were fixed only in short term as increasing transactions or
demand reulted in banks investing in more resoruces such as braches, ATM, Call centers,
personnel and computers.

2. The relationship between balances and customer profitability is as shown in following graph:
Managing Profitability
Understanding profitability at the customer level was particularly important in retail banking because
customer transactions generated incremental costs but typically did not generate incremental
revenues. In addition customer behavious seemed to be a component of customer profitability. For
example given two customers with same checking accounts and balances, one who routinely called
the bank to see if checks had been cleared or visited an branch to get help with checkbook balancing
would be far less profiatble that one who rarely with the bank apart from writing checks. Banks had a
history of channel innovations begining with ATM more than 30 years ago, followed by 24 hours call
center, automated voice response and most recently online bamking. Each additional channel had
provided an opportunity to reduce cost per transaction over the previous channel. The irony was that
with the introduction of these lower cost channels came a higher overall cost structure as customers
increased the number of transactions with the additon of each new channel rather than replacing one
channel (the bank for example).
Reatil banks reacted to the extraordinary variation in customer profitability with a variety of
approaches to migrate customers from lower to higher profit tiers. Some customers for example
offered their most profitable customers discounts on mortgage rate or higher interest rate on deposits
and routed their telephone calls to specially trained personnel in the call center. Instituting fees for
certain services was an attempt to encourage customers to migrate their transactions from high cost
channels such as branches to lower cost channels such as internet and ATMs.
Energised by his conversation with raines, Green visited Erica- head of IT services and asked her for
customer data. She said “We have data on 5 MN customers. How many customers do you want and
what sort of information do you need besides customer profitability?”. Green said “Can you give me
30000 customer data?”. Erica said “That seems like a very large sample, but I am sure you know what
you are doing. I will also put some demographic information there”

3. Returning to his office Green sorted customers from most profitable to and charting percent
cumulative customers he created the profitability skew shown below:
Formatting the data and calculating the summary statistics Alan produced following table:
Summary Statistics from Sample Customers
Customer
ID
1
1999
Online
a
usage
1999
Age bucket
b
(1-7)
1999
Income bucket
c
(1-9)
1999
Tenure
(years)
9Profit
1
2
3
4
…
31,633
31,634
Mean
Standard
deviation
1999
Annual
profit
9Online
9Age
9Inc
9Tenure
1999
Geographic
region (1100,
d
1200, or 1300)
9District
21
-6
-49
-4
…
92
124
111.50
272.84
0
0
1
0
…
1
0
0.12
0.33
not available
6
5
not available
…
1
3
4.05
1.64
not available
3
5
not available
…
6
6
5.46
2.35
6.33
29.50
26.41
2.25
…
5.41
17.50
10.16
8.45
1200
1200
1100
1300
…
1200
1300
n/a
n/a
a
Online use: 1 = uses online banking; 0 = does not use online banking.
b
Age buckets are as follows: 1 = less than 15 years; 2 = 15-24 years; 3 = 25-34 years; 4 = 35-44 years; 5 = 45-54
years; 6 = 55-64 years; 7 = 65 years and older.
c
Income buckets are as follows: 1 = less than $15,000; 2 = $15,000-$19,999; 3 = $20,000-$29,999; 4 = $30,000$39,999; 5 = $40,000-$49,999; 6 = $50,000-$74,999; 7 = $75,000-$99,999; 8 = $100,000-$124,999; 9 = $125,000
and more.
d
The three geographic regions are designated 1100, 1200, and 1300.
Alan subsequently found that the average profitability of customers who used online banking was
$116.67 which compared to $110.79 for those who did not. Alan knew that he will have to determine
if the difference was meaningful but wondered what conclusions he might be able to draw. Did the
online channel make customer more profitable? And what did this imply for the management decision
regarding fees or rebates of the channel? Alan glanced at the columns of data on customer
demographics such as age, income and geographical region and wondered if there might be more to
the story.