How profitable is a bank customer - An analysis of customer segmentation and its profitability

Seminar Paper, 2012

20 Pages, Grade: 1,3


Table of contents

1. Introduction

2. Profit sources

3. Ways of customer segmentation

4. Measuring Customer Profitability

5. Financial Key ratios for Customer Relationship Management

6. What to do with unprofitable Customers

7. Conclusion

II. List of figures

Figure 1 How a classical customer pyramid looks like

Figure 2 example of a Customer Profitability Analysis (CPA)

Figure 3 simple calculation of CLV

Figure 4 How to calculate the customer growth rate of a firm by using customer acquisition and churn rate

Figure 5 Calculation of Cross Selling Ratio

Figure 6 Calculation of Cost Income Ratio

Figure 7 example of a cost-benefit analysis


This paper gives an overview of the most important points which have to be taken into consideration when analyzing the customer profitability. One will see different methods and key ratios which are used to get an overview of the customer management. Furthermore, one sees the importance of a good customer segmentation system. Additionally, there is also a focus on the problems which a bank has to face when dealing with unprofitable customers.

1. Introduction

During the last years the competition between banks has increased a lot. After the global financial crisis and the ongoing financial problems in Europe profitability analyses has become more and more important. Customer profitability analyses allow banks to improve the cooperation between marketing, controlling and sales departments. These improvements are used to get more customers and a better customer relationship management.

Therefore this paper is divided into five different parts. Firstly one has to analyze which are the different profit sources for a bank. This is necessary to make an adequate profitability analysis. In a next step one looks at different segmentations of customers. One will see that more divisions of customer segments lead to a better quality of its analysis. Two main segmentation methods are explained. One is the simple 80/20 rule which divides customers only into two parts. An improvement of this method is the customer pyramid which enables a bank to make a deeper analysis because of additional segments. In a third step the most important analyses to calculate the profitability of a customer are explained in detail. On one hand there is a focus on the Customer Profitability Analysis (CPA). This method is used to calculate the profitability of a single customer in the past. On the other hand there is the possibility to use the Customer Lifetime Value (CLV). One should use this method to calculate the possible future profitability. Additionally one will see different key ratios that can be used to determine the changes in customer management. By using these key ratios a bank is able to improve its customer relationship management. The last chapter focuses on the relationship of banks with unprofitable customers. It is explained which possibilities a bank has to make them more profitable or to get rid of them.

2. Profit sources

Before I start to explain the different profit sources it is important to have a basic understanding of how banks work. Basically, a bank is interested in selling its own products to their customers as every other company is. But they do not have a classical product building like ordinary companies which sell their goods. Typical bank products are loans, saving accounts, credit cards, insurances, stock deposits and many more. Especially the balancing of a bank’s receivables and liabilities in terms of loans and deposit accounts is a very important issue for each bank. If a bank sells a lot of loans and not all of their clients can pay them back they will face liquidity problems. The same problem arises when banks do not sell enough saving accounts to their clients because then they cannot sell as much loans as necessary to increase their income. Due to this explanation one can see that banks have to deal with interest incomes (e.g. loans) and expenditures (e.g. deposit accounts). The important point is that banks have to balance these two types of their business to be profitable and guarantee enough liquidity.

However if one looks at a single customer it is not only interest income which generates profits. Every customer is provided with a special service which is not included in interest payments. Hence, banks get different kinds of fees depending on which products a customer has. Generally, fees can be charged for loans, saving and stock deposits and many more products. As far as loans are concerned a customer has to pay a service fee (most of the time about 1% of the loan[1] ) which is normally used to cover costs of loan preparation. For saving deposits a bank charges an annual service fee which is manifested contractually. In the case of stock deposits one can distinguish between a deposit fee and single transaction costs. Deposit fees are charged annually and are calculated by a certain percentage of the amount of stocks on the account. For each transaction which has to be done on the deposit account the bank charges a transaction fee. Most of the time it consists of a fixed payment for the transaction and sometimes a variable part is included which depends on the amount which is traded (e.g. fixed costs of 15€ per transaction plus 0,2% of the amount traded but not more than 50€)[2]. However, to make a good analysis of a customer one needs to have a good segmentation system which is explained in the next chapter.

3. Ways of customer segmentation

Generally, each bank can choose its own system of customer segmentation. E.g. they can use demographic information like age or gender on which they base a profitability analysis. A more commonly usage is the division into private and business customers. One can find this segmentation especially in the annual reports of each bank.

In Storbacka (1997) the author argues that customer segmentation is necessary for each company in order to enhance their marketing operations. One can distinguish segmentation into a retrospective and a prospective part. The retrospective part is only built on historical data. In the case of a bank this means that one has to look at all accounts of each customer to get an overall knowledge of the client’s needs. With the help of this information one can focus on the prospective part which enhances the relationship between the clients and the bank. Furthermore the author argues that segmentation can be based on sales volume, profitability, demographics etc. but even more important is the fact that good customer segmentation can improve a bank’s marketing strategy.[3]

In the article of Valentine (2004) it is argued that a lot of banks try to focus too much on some details. Therefore, they try to shape every account of their clients perfectly but overall they forget to look at a general view of different client groups. It is not that important if the annual deposit fee is 2 € or 2.05 € because only the planning time and costs will exceed the utility of this increase of the fee.[4]

Nowadays banks are interested in looking at their different customer groups to enhance their service offers to them. Before the 90s almost no bank saw a connection between service quality and profitability. Due to the help of the modern Customer Relationship Management (CRM) Software it has become easier to analyze the special needs of every client. Before the implication of this computer system many banks invented a simple “80/20 rule”.[5]

This rule is only a simple classification into profitable (best) and less profitable/unprofitable (rest) customers. More precisely it means that 20 percent of bank customers are responsible for 80 percent of the bank’s profit.[6]

Although the 80/20 scheme is a first approach to divide customers into groups, there are a lot of disadvantages which go with it. Especially when one wants to analyze the group with the less profitable customers it will falsify the results. The problem becomes clear if one looks at an example by Zeithalm et. al. (2001). The research team took data from a major US bank to look whether service quality improves a single customer’s profitability. They chose 796 customers randomly including information about their average account balance, profit from the account, age, gender and income. By multiplying the account balance times its profits gave them information how profitable each customer is. After making these calculations they were able to divide the 796 customers into the top 20% and the remaining 80%. Each group had to make a survey to answer the question what the important service drivers are. During the next eight months the bank focused on the important key drivers for both groups. After these eight months they checked how the profitability had changed over time. “The top tier had a higher percentage of women than the lower tier, an average account balance about five times as big, and average profit about 18times as much….The Top 20 % produced more profit per volume of business, with an average profit per account balance of 2.53%, versus 0.71 % for the lowest 20%.”[7] It was no surprise that the average age of the top 20% was higher than of the other customers. All profits from the accounts of the top 20% added built about 82% of the total profits. Therefore, the other 80% of the customers produced about 18% of the total profits, which fits the “80/20 rule” quite well.

According to the survey the top 20 % of the customers said that attitude, reliability and speed are the key drivers for a good service quality. If one only looks at the lowest 20% they are only concerned about attitude and speed. Additionally, the survey team put all clients into one group. After doing this it seemed as if every client thought that the same factors are important for his/her service quality. This result is one of the first pieces of evidence that putting customers into smaller groups can lead to wrong implications.[8]


[1] Hartmann-Wendels, Pfingsten and Weber (2010)

[2] Tolkmitt (2007)

[3] Storbacka (1997)

[4] Valentine (2004)

[5] Zeithalm V.A. et. al (2001)

[6] Zeithalm V.A. et. al (2001)

[7] Zeithalm V.A. et. al (2001), p.122

[8] Zeithalm V.A. et. al (2001)

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How profitable is a bank customer - An analysis of customer segmentation and its profitability
University of Innsbruck
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ISBN (Book)
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Bankkunde, Profitabilität, profitability, customer segmentation, Kundensegmentierung, Segmentierung, Analyse, segmentation, Finanzkennzahlen
Quote paper
Oliver Baumgartner (Author), 2012, How profitable is a bank customer - An analysis of customer segmentation and its profitability, Munich, GRIN Verlag,


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