Embed Size (px)
Citation preview
EMPI RICAL ARTICLE
Analysis of customer profit contribution for bankswith the concept of marketing mix strategy between4Cs and 5Ps
Tyrone T. Lin • Chia-Chi Lee • Hsiao-Chi Lin
Received: 24 October 2011 / Accepted: 20 April 2012 / Published online: 6 May 2012
� Springer-Verlag 2012
Abstract This paper takes the high-net-worth customers in the private wealth
management division of a case study bank as the research objects, and introduces the
concept of marketing mix strategy by combining the 4C (customer, cost to the cus-
tomer, convenience, and communication) model and 5P (product, price, place, pro-
motion, and people) model in the examination of the attributes of customers and
financial advisors in relation to the customer profit contribution and proposes man-
agement implications for practitioners. It attempts to establish a win–win business
mechanism or marketing strategy that is beneficial to both banks and consumers.
Keywords Marketing mix strategy � Customer profit contribution �Wealth management � Bank
1 Introduction
The rapid growth of domestic financial institutions has made banks’ business
environment face the increasingly fierce competition. The gradually narrowed deposit
spreads compress their survival space. In order to maintain the competitiveness, banks
are forced to diversify the development and attempt to seize the personal finance
T. T. Lin � H.-C. Lin
Department of International Business, National Dong Hwa University, 1, Sec. 2, Da-Hsueh Rd.,
Shou-Feng, Hualien 974, Taiwan
e-mail: [email protected]
H.-C. Lin
e-mail: [email protected]
C.-C. Lee (&)
Department of Accounting Information, National Taipei College of Business, 321, Sec. 1, Jinan Rd.,
Zhongzheng District, Taipei 100, Taiwan
e-mail: [email protected]
123
Serv Bus (2013) 7:37–59
DOI 10.1007/s11628-012-0144-z
market by the wealth management business so as to enhance their operating
performances. According to the recent report of consultancy firm McKinsey, the
accumulated wealth of the people of Taiwan is rising. In 2003, among the population
of 23 million, the number of people having idle wealth of more than NTD 3 million1
was nearly 500 thousand. By the end of 2007, this number reached 740 thousand and
would grow to 1 million in 2010. After the conservative estimation, the wealth
management market size is at least USD 100 billion. The wealth management market
has great space to grow and is regarded as a rising star by financial institutions.
The society of Taiwan is becoming more and more M-shape; the rich are
becoming richer and the concentration of wealth is quite significant. The assets
owned by the domestic customers of pyramid top rank No. 3 in Asia. Foreign and
domestic private banks rush to plunge into the market and actively hire additional
financial advisors to prepare for deeply exploring VIP financial services. With the
increase of people’s wealth, the case study bank thinks that it is imperative to do fine
segmentation to the vast wealth management customers. Therefore, banks have to
focus on the customers of pyramid top to develop the private banking business and
emphasize tailor-made professional and ‘‘customer-oriented’’ services to provide
individuals or families with extremely mysterious, low-toned, and honored private
services. That is why banks need to know well the financial management needs of
the targeted customers and provide different services for the customers of different
profit contribution.
The concept of customer profit contribution analysis used in the marketing field
has been well established for years. Because technology was not well developed in
the past, it was very difficult to measure and calculate the customer profit
contribution. In addition, the profit contributed by customers belongs to confidential
information for enterprises; it cannot be collected or obtained in the market merely
by questionnaires. Thus, there are little empirical applications on this topic. The
main contribution of this paper is to obtain meaningful information from databases
to build the customer profit contribution analysis model. It is hoped through the
empirical statistical model to define the value of different customers by the micro-
segment method to let the product department research and develop suitable
products according to different customer’s attributes, provide a reference for the
marketing department to plan marketing campaigns, and implement the differen-
tiation treatment of customer groups for the wealth management business of the
banking industry.
According to the rule of 80/20, 80 % of an enterprise’s profits come from 20 %
of customers; the remaining 20 % of the profits come from the activities spending
80 % of the enterprise’s marketing expenses. As for banks, customer profits vary
enormously and most of them are concentrated in a small number of customers. The
concept of the customer profit contribution can be used to identify the small number
of important customers and allocate the limited marketing resources. The concrete
quantified profit contribution of each customer allows banks to be more aware who
the most important customers are.
1 The NTD is ‘‘New Taiwan dollar.’’ According to the spot selling rate published by Bank of Taiwan on
February 2, 2012, 1 USD = 29.56 NTD.
38 T. T. Lin et al.
123
The paper aims to introduce the 4C Model for customers (Customer, Cost to the
customer, Convenience, and Communication) and the 5P Model for banks (Product,
Price, Place, Promotion, and People) as the two dimensions of marketing mix
strategy to perform an empirical analysis on the samples provided by the case study
bank. The purpose is to explore the effects on the customer profit contribution from
the customer’s and financial advisor’s attributes as the two dimensions. As a result,
a comprehensive marketing mix strategy model is developed by combining 4C and
5P for wealth management and provides a reference for bank practitioners.
Many studies explore the issues related to marketing or marketing strategies (e.g.,
Kadiyali et al. 2001; Kyriakopoulos and Moorman 2004; Arora 2006; Burgess and
Steenkamp 2006; Lemmens et al. 2007; Rosier et al. 2010). Banks should establish
competitive advantages, segment their customers, and provide differentiated
financial planning services in the fierce competition. It is necessary to utilize the
4C and 5P marketing strategies to pursue niches and stable growth.
The 4C marketing strategies are related to customers’ attributes. The most
important element is Customers. For the wealth management business, the key issue
is to manage the customers of different attributes and maintain customer
relationships. Banks should understand the product prices that customers are able
to take and the financial capacity of customers to provide financial planning and
products catering to their specific needs. This will allow banks to charge appropriate
processing fees, which refers to Cost to the customer as one of the 4Cs. Meanwhile,
it is also to take into account the accessibility and understandability of the services
rendered by banks to customers to better respond to the clients’ needs to create
value and motivations. It refers to Convenience as one of the 4Cs. Also, it is a
prerequisite to maintain continuous two-way communication with customers and
keep the interactions ongoing between financial advisors and customers so as to
understand the true needs of customers. This refers to Communication as one of the
4Cs. All these above arguments should be backed up on the presumption that banks
are able to clearly grasp customers’ attributes.
The 5P marketing strategies are relevant to banks. The most important element is
People, i.e., employees. The frontline employees facing customers in the wealth
management business are financial advisors. They have to be equipped with
extensive professional knowledge and sales skills so as to promote relevant financial
products at prices acceptable to customers in the form of financial planning. This
refers to Product, Price, and Promotion of 5Ps. Financial advisors should contact
customers to provide care and professional consultation over the phone or via the
internet at the appropriate time. This refers to Place of the 5Ps. All these above
arguments should be backed up on the presumption that banks employ the suitable
personnel. In other words, financial advisors play a pivotal role on the wealth
management business.
The paper would like to deeply explore the customer profit contribution, design
different marketing strategies for the customers with different contribution, and then
use different marketing activities and communication methods to reinforce
customers’ contribution. Devoting more resources to the customers of contribution
can help banks attract the customers of higher contribution and potentiality to
become loyal ones. Different from the traditional way of applying mass marketing,
Analysis of customer profit contribution 39
123
the use of the customer profit contribution can save banks’ resources, enhance
competitiveness, and enable banks to maximize operating effectiveness. The
concept of customer profit contribution analysis used in the marketing field has been
well established for years. The result of the profit contribution analysis can help
banks do market segmentation and resource allocation.
2 Literature review and hypothesis development
Jennings and Reichenstein (2008) assert that a private wealth manager should
manage an individual’s extended portfolio that contains financial assets like stocks
and bonds along with non-financial assets such as human capital and future benefits
from Social Security and defined benefit pension plans. Harris (2009) points out that
the wealth management should not be done in a vacuum; it is a part of the client’s
overall financial plan. The wealth manager is concerned with the client’s goals,
including the tax implications.
2.1 The customer profit contribution
Keane and Wang (1995) define that the customer profit contribution is the cost for
obtaining and serving customers and the arising cost for maintaining or enhancing
customer loyalty over the time. Berger and Nasr (1998) point out that the customer
profit contribution is the discounted net value derived by subtracting the cash
outflows attributed to customers from the expected customers’ future cash flows.
Mulhern (1999) and Lee et al. (2010) define that the customer profit contribution is
the net amount derived by subtracting the cost of consuming resources from the
revenue generated from the individual customer. The paper aims to explore
the impact of the customer’s attributes on the customer profit contribution. The
viewpoints of Mulhern (1999) and Lee et al. (2010) are adopted to define the
customer profit contribution as the net amount derived by subtracting the cost of
consuming resources from the revenue generated from the individual customer.
Hartfeil (1996) insists that enterprises should pay attention to the customer profit
contribution rather than the product profit contribution because what make them
profitable are customers rather than products. The difference is that the customer
profit contribution will be affected by other factors like the loss of customers, the
transaction duration, and the number of transaction times. Mulhern (1999) indicates
that the customer profit contribution is significantly affected by product price, unit
cost, quantity of units, purchase frequency, and variable cost. Besides, it is still
subjected to other economic factors such as transaction duration, customer
satisfaction, and other behavior factors (like price sensitivity, brand loyalty,
purchase timing, or some factors of sensory perception, etc.). Lee et al. (2010) aim
to examine the influences of personal attributes of salaried customers, product
transaction strategies, and sales personnel as three dimensions on the customer profit
contribution in the wealth management business of the banking industry. From the
above-mentioned scholars’ studies, we find that each customer’s profit contribution
to the company is different; thus, his consuming cost is also different. The company
40 T. T. Lin et al.
123
will have to calculate the extent of each customer’s profit contribution to develop
the future business strategy.
2.2 Hypothesis of the effect of the customer’s attributes on the customer profit
contribution based on the 4C concept
Arthur (1994) proposes the RFM model, which is constituted by three character-
istics: recency, frequency, and the monetary amount of the customer’s purchase.
This model can be one of the methods used to measure the strength of the
relationship between enterprises and customers. It is also the way used to identify
the potential value of each customer to make the customer marketing strategy.
Palsson (1996) points out that under the high-risk situation, risk-averse investors
will reduce their investment. In addition, risk preference will affect the allocation of
family resources; for example, the risk propensity investors are more inclined to
invest in high-risk assets. Reinartz and Kumar (2000) indicate that enterprises
should not overlook the customers with short transaction duration and high
customer profit contribution.
Niraj et al. (2001) indicate that the customer’s purchase properties are divided into
four kinds: volume, price/gross margin, complexity factors, and efficiency factors.
The customer profit contribution will be affected by these four factors. Garland (2002)
analyzes the non-financial factors that affect the customer profit contribution and finds
that the customer’s age, annual income, transaction duration, and wallet share are
positively correlated with the customer profit contribution. In addition, whether there
is a relative account which is also one of the affecting factors.
Liu et al. (2009) study the effectiveness of brand awareness, distribution
intensity, and their interaction effects on consumer heart share and market share.
They find that consumer heart share is positively related to brand awareness. Market
share is positively related to distribution intensity and brand awareness. In addition,
the results also indicate that brand awareness can moderate the effect of distribution
intensity on the marketing outcome. Lee et al. (2010) indicate that the quantity of
the products held by customers2 and the purchasing frequency of investment
products have significantly positive influences on the customer profit contribution.
Hence, under different customer’s attributes, the customer profit contribution will be
affected by financial institutions’ differentiation of marketing strategies.
Therefore, the paper develops the hypothesis of the effect of the customer’s
attributes on the customer profit contribution based on the 4C concept as follows. In
order to understand the customer’s fund operating situation, investment capacity, and
degree of risk tolerance, the case study bank establishes the risk assessment table to
evaluate the degree of risk by a quantified method and designs the asset allocation
based on the customer’s preferential investment portfolio. The customer’s investment
2 The variable of quantity of the products held by customers refers to the monthly average number of the
deposits and investment products held by customers with the financial institution (Lee et al., 2010). Lee
et al. (2010) divide its main products into six types, i.e., deposits in NT Dollars, deposits in foreign
currencies, funds, insurance policies, linked notes/bonds, and others. The weightings are given in
accordance with the actual transactions with customers during the sampling period. The weightings range
from 1 (one of the six types) to 6 (all the six types).
Analysis of customer profit contribution 41
123
properties are divided into six grades: the customers belonging to grade one and grade
two tend to the conservative type; those belonging to grade five and grade six tend to
the active type. The customers with a higher degree of risk tolerance will accept
investment products more easily. Therefore, their contribution on fee revenues to
banks is also higher compared with non-investment products. Thus, it is expected that
the customer’s risk tolerance is positively correlated with the customer profit
contribution. Hence, the hypothesis H1 is established as follows:
H1 The customer’s risk tolerance and the customer profit contribution are
positively correlated.
The major revenue source of the wealth management business comes from fee
revenues. Therefore, the case study bank will actively encourage customers to
purchase more financial products. It is expected that the number of product types
held by the customer and the customer profit contribution are positively correlated.
Hence, the hypothesis H2 is established as follows:
H2 The number of product types held by the customer and the customer profit
contribution are positively correlated.
While dealing with the private wealth management customers, the case study
bank will give them preferential programs to strengthen the relationship with them
and their loyalty. So, the case study bank will provide different level of privileges3
for different high-net-worth customers. Therefore, the customers with a higher level
of privilege will enjoy more preferential programs. Hence, it is expected the
customer’s level of privilege is positively correlated with the customer profit
contribution. Thus, the hypothesis H3 is established as follows:
H3 The customer’s level of privilege and the customer profit contribution are
positively correlated.
The major private wealth management business of the case study bank is mainly
built on the integrated household financial services of a whole family such as long-
term customer trust, tax saving, estate, and professional financial planning. If
current customers are willing to transfer their family assets to the case study bank, it
means that they have a high degree of satisfaction and trust on the wealth
management business of the case study bank. Thus, they will be more willing to
purchase the products of the case study bank. It is expected the number of family
accounts and the customer profit contribution are positively correlated. Therefore,
the hypothesis H4 is established as follows:
H4 The number of family accounts and the customer profit contribution are
positively correlated.
3 The definition of the ‘‘level of privilege’’ is made according to the customer’s total assets in the case
study bank, only those having assets of more than NTD 3 million can be Wealth Management VIPs of the
case study bank. The level of privilege is usually divided into five levels: the lowest is level 1 (the assets
of more than NTD 3 million and less than NTD 10 million), the highest is level 5 (the assets of more than
NTD 50 million). The higher the customer’s total assets in the case study bank, the higher his level of
privilege will be, which is relatively more privileges.
42 T. T. Lin et al.
123
In general, customers’ bad experience with banks will affect their willingness to
deal with banks. If customers are willing to continue having close contacts with the
case study bank, it shows that customers have high satisfaction and loyalty on the
case study bank. With the time, they will bring more profit contribution to the case
study bank. Hence, it is expected that the customer’s transaction duration4 and the
customer profit contribution are positively correlated. Therefore, the hypothesis H5
is established as follows:
H5 The customer’s transaction duration and the customer profit contribution are
positively correlated.
The higher the customer’s annual income, the higher the amount after deducting
living expenses can be used to invest will be. Thus, it is expected that the customer’s
annual income and the customer profit contribution are positively correlated. Hence,
the hypothesis H6 is established as follows:
H6 The customer’s annual income and the customer profit contribution are
positively correlated.
2.3 Hypothesis of the effect of the financial advisor on the customer profit
contribution based on the 5P concept
The concept of relationship marketing was born in the 1980s. According to the
theory and practice of modern marketing, the defensive marketing can establish the
long-term cooperative relationship with customers (Day 2000; Rust et al. 2000).
Therefore, besides retaining the existing customers, the defensive marketing can
create customer added value at the same time through the development of customer
relationship. Crosby et al. (1990) point out that good relationship quality (e.g., trust
and satisfaction) can reduce the uncertainty of transactions, determine the future
sustained interaction, and affect the effectiveness of final sales. Therefore, the
attributes of sales people (e.g., similarity and expertise) and the behavior of
relationship sales (e.g., interaction strength, mutual disclosure, and the willingness
to cooperate) are the main factors affecting whether the long-term relationship
between buyers and sales can be maintained or not. The relationship quality
perceived by customers and the attributes of sales people will affect the opportunity
for future sustained interaction.
Avila et al. (1993) find that the first consideration of companies’ purchasers is
products and services, followed by the acceptable price range. It is necessary to
strengthen the education and training of sales people to highlight the characteristics
of products to meet purchasers’ service needs. It can be seen that the service quality
of sales people is an important key factor whether customers decide to purchase or
not. Palmatier et al. (2007) indicate that buyers’ relationship quality with both sales
people and selling firms positively affect sellers’ financial outcomes, but the effect
of relationship quality with selling firms is enhanced as the perceived selling firms’
consistency increased. Lee et al. (2010) indicate that the level of financial advisers
4 The ‘‘transaction duration’’ means the duration starting from the first transaction between the customer
and the case study bank until now (the customer still has transactions with the case study bank).
Analysis of customer profit contribution 43
123
and the degree of customers’ satisfaction have significantly positive influences on
the customer profit contribution. Because the number of financial products and the
complexity of contents are increasing, it is more necessary to develop the financial
advisors with expertise and service dedication so as to increase and retain customers
for the case study bank.
Therefore, the paper develops the hypothesis of the effect of the financial
advisor’s attributes on the customer profit contribution based on the 5P concept as
follows:
Generally speaking, the senior financial advisors possess better expertise and
marketing skills than junior ones; they also tend to have access to a wealthier and
better clientele since they tend to occupy higher positions in the banks’ hierarchy.
Hence, compared with the junior financial advisors, the senior ones can contact
customers from a wider range, maintain an in-depth relationship with them, and then
get customers’ trust more easily. On the other hand, the customers are more assured
in entrusting their assets to senior financial advisors, resulting in bringing relatively
high fee revenues to banks. Therefore, the financial advisor’s working year is
expected to be positively correlated with the customer profit contribution. Thus, the
hypothesis H7 is established as follows:
H7 The financial advisor’s working year and the customer profit contribution are
positively correlated.
The major income source of the wealth management business comes from fee
revenues; thus, when the case study bank sets the financial advisor’s performance
target, it will regard fee revenues as the key item to facilitate financial advisors to
acquire sales performance by actively selling financial products. Hence, the
financial advisor’s performance target is expected to be positively correlated with
the customer profit contribution. Thus, the hypothesis H8 is established as follows:
H8 The financial advisor’s performance target and the customer profit contribu-
tion are positively correlated.
3 Methodology
3.1 Sample and data source
The paper takes the private wealth management customers of the case study bank as
the research objects. The case study bank officially established the private wealth
management department in January, 2005, so the individual customer profit
contribution can be calculated since January 2005 and the research samples are the
high-net-worth customers defined by the case study bank. According to the
definition, those who match one of the following criteria can become private wealth
management customers:
(1) The customer’s assets exceed NTD 10 million, or the total net assets of the
customer and his family of second-grade relative exceed NTD 30 million.
44 T. T. Lin et al.
123
(2) The customer’s average annual income of the past 2 years exceeds NTD
1.5 million, or the sum of the customer’s and his spouse’s average annual
income exceeds NTD 2 million.
The data of the paper comes from the complete information of the private wealth
management customers collected from January 2005 to September 2007. A total of
1,163 records are empirically analyzed by the multiple-regression model to explore
the impacts of the two dimensions of customers’ attributes and financial advisors on
the customer profit contribution.
3.2 Multiple-regression model
The regression model can be divided into two types: simple regression (which has
only one predictor variable/independent variable) and multiple-regression (which
has two or more predictor variables/independent variables). The multiple-regression
model establishes the relationship between a criterion variable (a dependent
variable) and a set of predictor variables (independent variables). The empirical
model in this paper has only one criteria variable (dependent variable), i.e., the
customer profit contribution (PROF) and eight predictor variables (independent
variables), which are the customer’s risk tolerance (RISK), the number of product
types held by the customer (TYPE), the level of VIP privileges (VIPLEVEL), the
number of family accounts (HOUSEHOLD), the customer’s transaction duration
with the case study bank (DURATION), the customer’s annual income (INCOME),
the financial advisor’s working year (SENIORITY), and the financial advisor’s
performance target (TARGET). Besides, there is a control variable, the customer’s
total assets (CUSASSET), this model can construct the relationship between a
criterion variable (dependent variable) and a set of predictor variables (independent
variables); therefore, it is appropriate to apply the multiple-regression model. In
addition, both the criteria variable and the predictor variables in the multiple-
regression model must be quantitative; this condition complies with the regression
model developed in this paper. Therefore, this paper adopts the multiple-regression
model to construct an empirical model, and tests the relationship between a criterion
variable (a dependent variable) and a set of predictor variables (independent
variables).
According to the aforementioned hypotheses, the paper builds a multiple-
regression model as follows:
PROF ¼ b0 þ b1RISKþ b2TYPEþ b3VIPLEVELþ b4HOUSEHOLD
þ b5DURATIONþ b6INCOMEþ b7SENIORITY þ b8TARGET
þ b9CUSASSETþ e ð1Þ
where PROF is the customer profit contribution; RISK is the customer’s risk tol-
erance; TYPE is the number of product types held by the customer; VIPLEVEL is
the level of VIP privileges; HOUSEHOLD is the number of family accounts;
DURATION is the customer’s transaction duration with the case study bank;
INCOME is the customer’s annual income; SENIORITY is the financial advisor’s
working year; TARGET is the financial advisor’s performance target; CUSASSET
Analysis of customer profit contribution 45
123
is the customer’s total assets; b0 is the intercept; b1,…,b9 are the parameters of the
regression model; and e is the error term.
3.3 Measurement of the customer profit contribution
In order to avoid the impacts of new and old customers’ different joining time and
insufficient transaction duration on calculating customers’ accumulated profit
contribution, the case study bank selects the information of the customers having the
transaction duration at least more than half a year. The average monthly profit
contribution (PROF) after deducting related costs is considered as a dependent
variable. Besides, the paper is based on the measure definition of the customer profit
contribution from Lee et al. (2010). That is, PROF in the paper refers to the
accumulated revenues minus the accumulated costs and divided by the number of
transaction months from January 2005 to September 2007. The paper takes the log
nominal to this variable to make the distribution of samples more concentrated and
closer to normal distribution. The calculation formula is as follows:
The customer’s average monthly profit contribution PROFð Þ¼ LOG accumulated revenues � accumulated costsð Þ½� the number of transaction months�
3.4 Measurement of independent variables
3.4.1 The dimension of the customers’ attributes
3.4.1.1 Risk tolerance (RISK) Based on the classification of the case study bank,
the customer’s risk tolerance is divided into six levels (levels 1–6). The lower level
of risk tolerance means that the customer’s investment property is more
conservative, while the higher level of risk tolerance means that the customer’s
investment property is more active.
3.4.1.2 The number of product types held by the customer (TYPE) It refers to the
number of product types held by the customer in the case study bank as of
September 30, 2007. The case study bank classifies the products to 14 items: NTD
deposits, foreign currency deposits, domestic funds, foreign funds, linked bonds,
U.S. government bonds, combined commodities, RP, planning-based trusts,
investment trusts, insurances, stocks, futures, and other items.
3.4.1.3 The level of VIP privileges (VIPLEVEL) According to the case study
bank’s classification, the level of VIP privileges is divided into five levels (levels
1–5). The customers having assets in the case study bank between NTD 3 million
and NTD 10 million belong to level 1; those having assets between NTD
10 million and NTD 15 million belong to level 2; those having assets between
NTD 15 million and NTD 30 million belong to level 3; those having assets between
NTD 30 million and NTD 50 million belong to level 4; and those having assets of
more than NTD 50 million belong to level 5.
46 T. T. Lin et al.
123
3.4.1.4 The number of family accounts (HOUSEHOLD) It refers to the number of
the customer’s whole family accounts in the case study bank as of September 30,
2007. The customer’s family accounts refer to the account of relationship
household, which is composed of the customer’s main account and the accounts
of second-grade relatives.
3.4.1.5 The customer’s transaction duration (DURATION) It refers to the total
months of the customer’s starting to join the case study bank as of September 30,
2007.
3.4.1.6 The customer’s annual income (INCOME) It refers to the annual income
check in the application form while the customer opening an account. This income is
divided into eight grades (grades 1–8) based on the case study bank’s classification.
Grade 1 represents the customer’s annual income is between NTD 300 thousand and
NTD 600 thousand; grade 2 is between NTD 600 thousand and NTD 800 thousand;
grade 3 is between NTD 800 thousand and NTD 1 million; grade 4 is between NTD
1 million and NTD 1.5 million; grade 5 is between NTD 1.5 million and NTD
3 million; grade 6 is between NTD 3 million and NTD 5 million; grade 7 is between
NTD 5 million and NTD 10 million; and grade 8 is more than NTD 10 million.
3.4.2 The dimension of the financial advisor
3.4.2.1 The financial advisor’s working year (SENIORITY) It refers to the
financial advisor’s working year calculated by month.
3.4.2.2 The financial advisor’s performance target (TARGET) It refers to the fee
revenues of the financial advisor’s performance target set by the case study bank.
This target is divided into three grades: NTD 450 thousand, NTD 520 thousand, and
NTD 590 thousand.
3.5 Control variable
3.5.1 The customer’s total assets (CUSASSET)
It refers to the total amount of products held by the customer in the case study bank
as of September 30, 2007. The total amount of products includes NTD deposits,
foreign currency deposits, domestic funds, foreign funds, linked bonds, U.S.
government bonds, combined commodities, RP, planning-based trusts, investment
trusts, insurances, stocks, futures, and other items. The paper takes the log nominal
to this variable to make the distribution of samples more concentrated and closer to
normal distribution.
In order to connect the past research literatures and the recommendations
provided by the professionals of the case study bank, Table 1 summarizes the
factors affecting customer profit contribution and their related logic designed in this
paper.
Analysis of customer profit contribution 47
123
Ta
ble
1S
um
mar
yo
fv
aria
ble
s
Dim
ensi
ons
Var
iable
sL
iter
ature
or
pro
fess
ional
pra
ctic
alex
per
ience
use
din
this
pap
er
Arg
um
ents
Var
iable
sdes
igned
inth
ispap
er
Dep
enden
t
var
iable
The
cust
om
erpro
fit
contr
ibuti
on
(PR
OF
)
Mulh
ern
(1999
)an
dL
ee
etal
.(2
010
)
The
cust
om
erpro
fit
contr
ibuti
on
asth
enet
amount
der
ived
by
subtr
acti
ng
the
cost
of
consu
min
gre
sourc
esfr
om
the
reven
ue
gen
erat
edfr
om
the
indiv
idual
cust
om
er.
(acc
um
ula
ted
reven
ues
-ac
cum
ula
ted
cost
s)7
the
num
ber
of
tran
sact
ion
month
s
Cust
om
er
attr
ibute
s
The
cust
om
er’s
risk
tole
rance
(RIS
K)
Pal
sson
(1996
)U
nder
the
hig
h-r
isk
situ
atio
n,
risk
-aver
sein
ves
tors
wil
l
reduce
thei
rin
ves
tmen
t.
Bas
edon
the
clas
sifi
cati
on
of
the
case
study
ban
k,
the
cust
om
er’s
risk
tole
rance
is
div
ided
into
six
level
s.
The
num
ber
of
pro
duct
types
hel
dby
the
cust
om
er(T
YP
E)
Lee
etal
.(2
010)
The
quan
tity
of
the
pro
duct
shel
dby
cust
om
ers
has
a
signifi
cantl
yposi
tive
infl
uen
ceon
the
cust
om
erpro
fit
contr
ibuti
on.
The
num
ber
of
pro
duct
types
hel
dby
the
cust
om
erin
the
case
study
ban
kas
of
Sep
tem
ber
30,
2007.
The
level
of
VIP
pri
vil
eges
(VIP
LE
VE
L)
Acc
ord
ing
toth
e
reco
mm
endat
ions
pro
vid
ed
by
the
pro
fess
ional
sof
the
case
study
ban
k.
The
case
study
ban
kw
ill
pro
vid
edif
fere
nt
level
of
pri
vil
eges
for
dif
fere
nt
hig
h-n
et-w
ort
hcu
stom
ers.
Ther
efore
,th
ecu
stom
ers
wit
ha
hig
her
level
of
pri
vil
ege
wil
len
joy
more
pre
fere
nti
alpro
gra
ms.
Acc
ord
ing
toth
eca
sest
udy
ban
k’s
clas
sifi
cati
on,
the
level
of
VIP
pri
vil
eges
isdiv
ided
into
five
level
s.
The
num
ber
of
fam
ily
acco
unts
(HO
US
EH
OL
D)
Acc
ord
ing
toth
e
reco
mm
endat
ions
pro
vid
ed
by
the
pro
fess
ional
sof
the
case
study
ban
k.
Ifcu
rren
tcu
stom
ers
are
wil
ling
totr
ansf
erth
eir
fam
ily
asse
tsto
the
case
study
ban
k,
itm
eans
that
they
hav
ea
hig
hdeg
ree
of
sati
sfac
tion
and
trust
on
the
wea
lth
man
agem
ent
busi
nes
sof
the
case
study
ban
k.
Thus,
they
wil
lbe
more
wil
ling
topurc
has
eth
epro
duct
sof
the
case
study
ban
k.
The
num
ber
of
the
cust
om
er’s
whole
fam
ily
acco
unts
inth
eca
sest
udy
ban
kas
of
Sep
tem
ber
30,
2007.
The
cust
om
er’s
tran
sact
ion
dura
tion
wit
hth
eca
sest
udy
ban
k(D
UR
AT
ION
)
1.
Rei
nar
tzan
dK
um
ar
(2000)
1.
Ente
rpri
ses
should
not
over
look
the
cust
om
ers
wit
h
short
tran
sact
ion
dura
tion
and
hig
hcu
stom
erpro
fit
contr
ibuti
on.
The
tota
lm
onth
sof
the
cust
om
er’s
star
ting
tojo
inth
eca
sest
udy
ban
kas
of
Sep
tem
ber
30,
2007.
2.
Gar
land
(2002
)2.
The
cust
om
er’s
tran
sact
ion
dura
tion
isposi
tivel
y
corr
elat
edw
ith
the
cust
om
erpro
fit
contr
ibuti
on.
The
cust
om
er’s
annual
inco
me
(IN
CO
ME
)
Gar
land
(2002
)T
he
cust
om
er’s
annual
inco
me
isposi
tivel
yco
rrel
ated
wit
hth
ecu
stom
erpro
fit
contr
ibuti
on.
This
inco
me
isdiv
ided
into
eight
gra
des
(gra
des
1–8)
bas
edon
the
case
study
ban
k’s
clas
sifi
cati
on.
48 T. T. Lin et al.
123
Ta
ble
1co
nti
nu
ed
Dim
ensi
ons
Var
iable
sL
iter
ature
or
pro
fess
ional
pra
ctic
alex
per
ience
use
din
this
pap
er
Arg
um
ents
Var
iable
sdes
igned
inth
ispap
er
Fin
anci
al
advis
or
The
finan
cial
advis
or’
s
work
ing
yea
r
(SE
NIO
RIT
Y)
Acc
ord
ing
toth
e
reco
mm
endat
ions
pro
vid
ed
by
the
pro
fess
ional
sof
the
case
study
ban
k.
The
senio
rfi
nan
cial
advis
ors
poss
ess
bet
ter
exper
tise
and
mar
ket
ing
skil
lsth
anju
nio
rones
;th
eyal
sote
nd
tohav
e
acce
ssto
aw
ealt
hie
ran
dbet
ter
clie
nte
lesi
nce
they
tend
toocc
upy
hig
her
posi
tions
inth
eban
ks’
hie
rarc
hy.
Hen
ce,
com
par
edw
ith
the
junio
rfi
nan
cial
advis
ors
,th
e
senio
rones
can
conta
ctcu
stom
ers
from
aw
ider
range,
mai
nta
inan
in-d
epth
rela
tionsh
ipw
ith
them
,an
dth
en
get
cust
om
ers’
trust
more
easi
ly.
Itre
fers
toth
efi
nan
cial
advis
or’
sw
ork
ing
yea
rca
lcula
ted
by
month
.
The
finan
cial
advis
or’
s
per
form
ance
targ
et
(TA
RG
ET
)
Acc
ord
ing
toth
e
reco
mm
endat
ions
pro
vid
ed
by
the
pro
fess
ional
sof
the
case
study
ban
k.
The
maj
or
inco
me
sourc
eof
the
wea
lth
man
agem
ent
busi
nes
sco
mes
from
fee
reven
ues
;th
us,
when
the
case
study
ban
kse
tsth
efi
nan
cial
advis
or’
sper
form
ance
targ
et,
itw
ill
regar
dfe
ere
ven
ues
asth
ekey
item
to
faci
lita
tefi
nan
cial
advis
ors
toac
quir
esa
les
per
form
ance
by
acti
vel
yse
llin
gfi
nan
cial
pro
duct
s.
This
targ
etof
fee
reven
ues
isdiv
ided
into
thre
egra
des
:N
TD
450
thousa
nd,
NT
D
520
thousa
nd,
and
NT
D590
thousa
nd
resp
ecti
vel
y.
Contr
ol
var
iable
The
cust
om
er’s
tota
l
asse
ts(C
US
AS
SE
T)
Acc
ord
ing
toth
e
reco
mm
endat
ions
pro
vid
ed
by
the
pro
fess
ional
sof
the
case
study
ban
k.
The
tota
lam
ount
of
pro
duct
sin
cludes
NT
Ddep
osi
ts,
fore
ign
curr
ency
dep
osi
ts,dom
esti
cfu
nds,
fore
ign
funds,
linked
bonds,
U.S
.gover
nm
ent
bonds,
com
bin
ed
com
modit
ies,
RP
,pla
nnin
g-b
ased
trust
s,in
ves
tmen
t
trust
s,in
sura
nce
s,st
ock
s,fu
ture
s,an
doth
erit
ems.
The
tota
lam
ount
of
pro
duct
shel
dby
the
cust
om
erin
the
case
study
ban
k.
Analysis of customer profit contribution 49
123
4 Results
4.1 Descriptive statistic results
The descriptive statistics of variables are shown in Table 2. PROF ranges from NTD
1 to NTD 758,827 and the average PROF per customer is NTD 7,702. PROF (after
log nominal) ranges from 0 to 5.880, with a mean value of 3.240. Concerning the
customer’s attributes, RISK is between 1 and 6, with a mean value of 4.554, which
indicates that the case study bank’s customers have higher risk tolerance. TYPE is
from 1 to 10, with a mean value of 3.402, which means the average 3.402 product
types are held by each customer. VIPLEVEL ranges from 1 to 5, with an average
level of 2.751. HOUSEHOLD ranges from 1 to 13. The customer’s average current
account number (including the master account) of 2.163 indicates that on average,
each customer at least has a second-grade relative dealing with the case study bank.
The more the number of the family accounts, the higher the customer’s recognition
of the case study bank will be. DURATION ranges from 7 to 33 months, with an
average period of 22 months, which indicates that the transaction duration between
Table 2 Descriptive statistics of variables (N = 1,163)
Dimensions Variables Mean Median Minimum Maximum SD
Dependent
variable
PROF (unit: dollars) 7,702 2,592 1.000 758,827 28,057
PROF (after log
nominal)
3.240 3.414 0.000 5.880 0.914
Customer
attributes
RISK (unit: level) 4.554 5.000 1.000 6.000 1.074
TYPE (unit: number
of types)
3.402 3.000 1.000 10.000 1.812
VIPLEVEL (unit:
level)
2.751 2.000 1.000 5.000 1.438
HOUSEHOLD (unit:
number of accounts)
2.163 1.000 1.000 13.000 1.657
DURATION (unit:
number of months)
22.125 22.000 7.000 33.000 8.473
INCOME (unit: level) 4.318 4.000 1.000 8.000 1.286
Financial
advisor
SENIORITY (unit:
number of months)
86.039 95.000 24.000 132.000 33.705
TARGET (unit:
dollars)
516,088 520,000 450,000 590,000 44,960
Control
variable
CUSASSET (unit:
dollars)
15,172,452 6,157,971 5.000 411,000,000 35,719,647
CUSASSET (after log
nominal)
6.579 6.789 0.699 8.614 1.040
Notes: 1. The variable PROF is the customer profit contribution; RISK is the customer’s risk tolerance;
TYPE is the number of product types held by the customer; VIPLEVEL is the level of VIP privileges;
HOUSEHOLD is the number of family accounts; DURATION is the customer’s transaction duration with
the case study bank; INCOME is the customer’s annual income; SENIORITY is the financial advisor’s
working year; TARGET is the financial advisor’s performance target; CUSASSET is the customer’s total
assets. 2. N is the number of observations
50 T. T. Lin et al.
123
customers and the case study bank is quite long. The grade of INCOME is between
1 and 8, with a mean value of 4.318, which shows that the customer’s average
annual income is about between NTD 1 million and 1.5 million.
Regarding financial advisors, SENIORITY ranges from 24 to 132 months, with
the average length of working year of 86 months, which shows that the advisors
who can provide service for the top-level VIP of private wealth management have
very rich financial experience. TARGET ranges from NTD 450 thousand to 590
thousand, with an average performance target of NTD 516,088.
As for the control variable, the total amount of the customer’s assets
(CUSASSET) ranges from NTD 5 to 411 million, with the average value of NTD
15,172,452. CUSASSET (after log nominal) ranges from 0.699 to 8.614, with a
mean value of 6.579.
4.2 Regression result
The ANOVA analysis and model fitness results listed in Panel A of Table 3 show
that F-statistics = 158.010, reaching a significant level of 1 %. In addition, R2 =
0.552 and Adj. R2 = 0.549, showing appropriate model fitness. The regression
model results in Panel B find that six variables (RISK, TYPE, VIPLEVEL,
HOUSEHOLD, DURATION, and INCOME) and the control variable CUSASSET
are significantly positively correlated with PROF; the expected directions are also
consistent with the hypotheses. Hence, the hypotheses H1–H6 in the dimension of
the customer’s attributes are all supported.
The customer’s risk tolerance is significantly positively correlated with the
customer profit contribution. That is, the higher the customer’s risk tolerance, the
higher the customer profit contribution will be. The returns and risks of investment-
type goods are higher than those of security-type products like Taiwanese and
foreign currency deposits. The customers bearing higher risk tolerance can more
easily accept these investment goods. Thus, their profit contribution will be also
higher. The number of product types held by the customer and the customer profit
contribution are significantly positively correlated. That is, the customers holding
more product types have higher customer profit contribution. Therefore, continuing
to develop the potential customers with financial needs and implementing the cross-
selling strategy to increase the number of product types held will enhance the
customer profit contribution.
The level of VIP privileges and the customer profit contribution are significantly
positively correlated. That is, the higher the level of VIP privileges, the higher the
customer profit contribution will be. When banks offer more privileges to
customers, it can increase customers’ good feeling of banks; thus, the customer
profit contribution will increase. However, considering corporate operating costs,
inevitably banks will not be able to provide each customer with the same privilege.
They are required to implement different marketing to the customers of different
profit contribution. The number of the customer’s family accounts and the customer
profit contribution are significantly positively correlated. That is, the higher the
number of the customer’s family accounts, the higher the customer profit
contribution will be. If customers and their second-grade relatives are willing to
Analysis of customer profit contribution 51
123
Ta
ble
3R
egre
ssio
nre
sult
of
the
whole
sam
ple
s(N
=1
,163
)
Pan
elA
:A
NO
VA
anal
ysi
san
dm
od
elfi
tnes
s
Item
sS
um
of
squ
ares
df
Mea
nsq
uar
eF
-sta
tist
ics
Pro
b.
(F-s
tati
stic
s)
Reg
ress
ion
535.7
76
959.5
31
158.0
10
0.0
00***
Res
idual
434.3
97
1153
0.3
77
To
tal
97
0.1
74
11
62
R2
=0
.552
Ad
j.R
2=
0.5
49
Pan
elB
:re
gre
ssio
nre
sult
Dim
ensi
ons
Var
iable
sP
redic
ted
sign
Coef
fici
ent
t-v
alu
ep-v
alu
e
(on
e-ta
iled
)
VIF
Hy
po
thes
is
(acc
ept
or
reje
ct)
Cu
stom
erat
trib
ute
sIn
terc
ept
-0
.288
-1
.136
0.1
28
RIS
K?
0.1
13
6.2
90
0.0
00
**
*1
.14
6A
ccep
tH
1
TY
PE
?0
.058
4.6
66
0.0
00
**
*1
.57
6A
ccep
tH
2
VIP
LE
VE
L?
0.0
95
6.4
52
0.0
00
**
*1
.37
6A
ccep
tH
3
HO
US
EH
OL
D?
0.0
24
1.9
80
0.0
24
**
1.2
06
Acc
ept
H4
DU
RA
TIO
N?
0.0
45
17
.84
80
.000
**
*1
.42
7A
ccep
tH
5
INC
OM
E?
0.0
53
3.5
68
0.0
00
**
*1
.11
4A
ccep
tH
6
Fin
anci
alad
vis
or
SE
NIO
RIT
Y?
-0
.001
-2
.238
0.0
13
**
1.0
60
Rej
ect
H7
TA
RG
ET
?0
.000
0.6
40
0.2
61
1.0
49
Rej
ect
H8
Co
ntr
ol
var
iab
leC
US
AS
SE
T?
0.1
89
9.0
30
0.0
00
**
*1
.46
4
No
tes:
1.
Var
iab
les
are
defi
ned
inT
able
2.
2.
Th
eV
aria
nce
Infl
atio
nF
acto
rs(V
IF)
val
ues
of
all
ind
epen
den
tan
dco
ntr
ol
var
iab
les
are
smal
ler
than
10
,st
ron
gly
ind
icat
ing
that
the
mu
lti-
coll
inea
rity
pro
ble
min
the
esti
mat
edeq
uat
ion
isn
egli
gib
le.
3.
*p\
0.1
;*
*p\
0.0
5;
**
*p\
0.0
1
52 T. T. Lin et al.
123
concentrate the assets in a same bank, it shows that customers have higher
recognition of the service of this bank. Therefore, when financial advisors make
financial planning for customers, they can follow the direction of the family
financial-integrated service (household) to strengthen the service for customers’
families and thus increase the number of family accounts.
The customer’s transaction duration and the customer profit contribution are
significantly positively correlated. That is, the longer the customer’s transaction
duration, the higher the customer profit contribution will be. In general, the longer the
customers keep transacting with banks, the higher the customers’ satisfaction and
loyalty will be. The customer’s annual income and the customer profit contribution
are significantly positively correlated. That is, the higher the customer’s annual
income, the higher the customer profit contribution will be. When customers have
higher annual income, the amount after deducting living expenses can be used for
investment is also higher, which can increase banks’ profits.
In addition, SENIORITY is significantly negatively correlated with PROF
(p value = 0.013), which is inconsistent with the expected direction. TARGET is
insignificantly positively correlated with PROF. Therefore, the hypotheses in the
dimension of the financial advisor, H7 and H8, are not supported. The financial
advisor’s seniority and the customer profit contribution are significantly negatively
correlated; that is, the longer the financial advisor’s working year, the lower the
customer profit contribution will be. The empirical result contradicts the expected
hypothesis; so, hypothesis H7 is not supported. Practically, the possible reason may
be that senior advisors will focus on customers’ needs to run the long-term customer
relationship. They will not recommend high-profit products to achieve their
performance targets asked by companies. Junior advisors have fewer customers in
the initial period so they will recommend high-profit products in priority to meet
their performance targets asked by companies. It results in the financial advisor’s
working year to be negatively correlated with the customer profit contribution.
Hence, the financial advisor’s seniority and the customer profit contribution are
significantly negatively correlated. In addition, the financial advisor’s financial
performance target and the customer profit contribution are insignificantly
positively correlated so hypothesis H8 is not supported either. The reason may be
due to the rise of consumers’ self-consciousness; customers will not increase their
purchases only because of financial advisors’ performance targets. On the contrary,
customers will purchase financial products based on their personal needs. Therefore,
the financial advisor’s financial performance target and the customer profit
contribution are insignificantly correlated.
4.3 Applications and links 4Cs and 5Ps in marketing mix strategy
4Cs in marketing strategies are relevant to demand, whereas 5Ps are relevant to
supply. All economic events occur when demand meets supply. In the wealth
management market, customers are demand and banks are supply. The combination
of 4Cs and 5Ps in marketing mix strategy establishes good relationships between
banks and customers. This makes it possible to make objective evaluations of stable
customer profit contribution of banks.
Analysis of customer profit contribution 53
123
The empirical results find that all the six variables in customers’ attributes report
significantly positively correlations with the customer profit contribution. This
finding completely supports the research hypotheses. As the customer factors
developed by 4Cs have significant influences on the customer profit contribution, it
is advised that banks should fully leverage 4C ? 5P marketing mix strategy in
accordance with the customers of varying attributes. Regarding the two variables of
the attributes of financial advisors, the financial advisor’s seniority reports a
significantly negative correlation with the customer profit contribution, whereas the
financial advisor’s financial performance target has no significant influence on the
customer profit contribution. To sum up, the bank factors developed upon 5Ps do
not have stable influences on the customer profit contributions. In contrast, the
influences of customer factors are greater than those of bank factors. This is because
the customers interested in purchasing banks’ products may have actively gathered
product information. Meanwhile, they have formed preliminary ideas on the content
of financial planning so it is difficult for financial advisors to influence their
purchase intentions and product perceptions. Banks should strive to enhance the
sales skills of financial advisors so as to fulfill the synergies of 4C ? 5P marketing
mix strategy.
The paper connects the empirical results in Table 3 and the marketing mix
strategy consisting of 4Cs at customers’ end and 5Ps at banks’ end. The results are
summarized in Table 4, which shows the correlation between customer profit
contribution factors and 4C ? 5P marketing mix strategy. It is suggested that banks
should develop the appropriate dynamic marketing mix strategy according to the
varying attributes of customers and financial advisors.
The customer’s risk tolerance (RISK), as a customer’s attribute, can be taken into
account in conjunction with Customer and Cost to the customer in the 4Cs and
Product and Price in the 5Ps of marketing mix strategy. In other words, banks
should establish a deep understanding of the required product portfolio (Product) to
its wealth management customers (Customer) at prices that the customers can afford
and are willing to pay (Cost to the customer and Price). Such an understanding can
Table 4 The combination between the empirical variables and 4C ? 5P marketing mix strategy
Dimensions Variables 4C 5P
Customer
attributes
RISK Customer ? Cost to the
customer
Product ? Price
TYPE Convenience ? Cost to the
customer
Product ? Price
VIPLEVEL Customer ? Convenience Product ? Price
HOUSEHOLD Customer ? Convenience Product ? Place
DURATION Customer ? Communication Product ? Place
INCOME Customer ? Cost to the
customer
Product ? Price
Financial advisor SENIORITY Communication Product ? Promotion ? People
TARGET Customer ? Communication Product ? Promotion ? People
Note: Variables are defined in Table 2
54 T. T. Lin et al.
123
shed light to the development of customer segments for different levels of risk
tolerance and customized financial products (Product). The number of product types
held by customers (TYPE) can be taken into account in conjunction with
Convenience and Cost to the customer in the 4Cs and Product and Price in the
5Ps of marketing mix strategy. Namely, banks hope customers can hold as many as
product types as possible so as to create higher customer profit contribution. The
first step is to enable customers to understand what products (Product) are available
and know how convenient it is to purchase products (Convenience). After that, it is
necessary to design a suitable product portfolio (Product) at a cost affordable to
customers (Cost to the customer) to enhance the value of this portfolio. The final
step is to come up with a reasonable price (Price), i.e., service charges. The pricing
must be set at a level where banks can make profits and customers can accept to
enhance banks’ customer profit contribution by increasing the number of product
types held by customers.
The level of VIP privileges (VIPLEVEL) and the number of family accounts
(HOUSEHOLD) can be taken into account in conjunction with Customer and
Convenience in 4Cs as well as Product and Price (for VIPLEVEL) and Product and
Place (for HOUSEHOLD) in 5Ps of marketing mix strategy. Usually, the higher the
level of customers, the more the VIPs they are (Customer), and the more the
customer profit contribution they generate for banks. Banks can design high-priced,
premium (Price), and bespoke products (Product) for these customers and make it
convenient for them to purchase these products (Convenience). This can increase
banks’ customer profit contribution. Meanwhile, the more the number of family
accounts of customers (Customer), the loyal they are. In addition to convenience in
product purchases (Convenience), these customers should be addressed to for their
particular needs (Products). Banks should contact them over the phone or via the
internet (Place). This will enhance banks’ customer profit contribution.
The customer’s transaction duration with the case study bank (DURATION) can
be taken into account in conjunction with Customer and Communication and in the
4Cs as well as Product and Place in the 5Ps of marketing mix strategy. Generally
speaking, the longer the history of dealing with banks, the loyal and the closer the
customers are (Customer). Banks should maintain communication with customers
(Communication) at the right time (Place) to understand their needs and changes to
the preference and requirements of products (Product). The appropriate product
planning (Product) and operational strategy adjustments are required. The
customer’s annual income (INCOME) can be taken into account in conjunction
with Customer and Cost to the customer in the 4Cs as well as Product and Price in
the 5Ps of marketing mix strategy. The customers with higher annual incomes
(Customer) are more able to afford higher product costs (Cost to the customer and
Price) for the product portfolios (Product). Thus, banks can design the products with
higher price for these customers (Product and Price) to increase banks’ customer
profit contribution.
In addition, the financial advisor’s working year (SENIORITY) can be taken into
account in conjunction with Communication in the 4Cs as well as Product,
Promotion, and People in the 5Ps of marketing mix strategy. In other words, the
financial advisors (People) equipped with professionalism and good sales skill have
Analysis of customer profit contribution 55
123
to possess good communication with customers (Communication) to make relevant
products and financial planning concepts understandable for customers. They should
not push products regardless of the true needs of customers. Hence, two-way
communication is the key element (Communication) whether financial advisors can
meet the needs of customers. The sale of products (Product) requires extensive sales
experience (Promotion) to establish trust from customers, and this enhances
customers’ purchase motivations and banks’ customer profit contribution. The
financial advisor’s performance target (TARGET) can be taken into account in
conjunction with Customer and Communication in the 4Cs as well as Product,
Promotion, and People in the 5Ps of marketing mix strategy. The sales targets of
financial advisors (People) are usually set by banks based on their experience and
tenure. As a general rule, the financial advisors (People) entrusted with high targets
for commissions maintain active contact and interaction with customers (Commu-
nication and Customer). They resort to excellent customer relationship management
(CRM) to enhance their relationships with customers to sell products to customers
(Promotion, Product, and Customer). This helps them to achieve the goal for banks
and enhance banks’ customer profit contribution.
5 Conclusions
This paper takes the private wealth management customers of the case study bank as
the research objects to explore the impacts of customers’ attributes and financial
advisors on the profit contribution of private wealth management customers. The
regression result shows that the customer’s risk tolerance, the number of product types
held by the customer, the level of VIP privileges, the number of the customer’s family
accounts, the transaction duration between the customer and the case study bank, and
the customer’s annual income are significantly positively correlated with the
customer profit contribution. Hence, the hypotheses H1–H6 are supported.
This paper provides the following conclusions and recommendations: (1)
According to the regulations of the Financial Supervisory Commission Executive
Yuan, R.O.C., while operating the wealth management business, banks need to
establish an operating norm of risk attributes and make financial product allocation
based on different customer’s risk tolerance to avoid sales people’s improper
recommendation. So, in the selling process, the case study bank will ask customers to
do the risk-rating scale to understand their risk attributes and then recommend them
suitable financial products. Financial advisors can in priority deal with the customers
with a higher level of risk tolerance to improve the customer profit contribution. (2)
The empirical result confirms that purchasing more product types can indeed bring
higher profits for the case study bank. Hence, the case study bank can sell the existing
customers other products to increase the product types purchased by customers to
increase profits and deepen the customer relationship. (3) Providing more preferential
VIP privileges can increase customers’ willingness to deal with banks and the
customer profit contribution. Therefore, the case study bank can use the customer
profit contribution to segment the preferential VIP privileges; customers’ VIP
privileges will be improved only when their profit contribution is increased. On the
56 T. T. Lin et al.
123
contrary, if the customer profit contribution is decreased, their VIP privileges will also
be reduced to achieve the objective of cost control. (4) The higher number of
customer’s family accounts can indeed increase the customer profit contribution;
hence, the case study bank is recommended to provide the integrated and tailored-
made services and the integrity of financial planning for customers’ families so as to
improve the customer profit contribution and customers’ loyalty. (5) The longer the
transaction duration, the higher the customer’s loyalty and the customer profit
contribution will be. The case study bank can regularly give the initial customers
after-sales service such as care phone or payment reminding to strengthen the
customer relationship and increase the opportunity of purchasing products. (6) As
the spread of deposits is shrinking, the wealth management business becomes the
important market for banks. If banks can in advance identify the high-quality
customers and effectively manage the customer relationship, it will help them
increase their wealth management market share. Therefore, the financial advisors of
the case study bank can in priority develop the customers of white-collar workers.
The operating principle of the case study bank’s private wealth management
business is to establish the professional financial planning such as asset management
of customers’ whole family, long-term trust, tax saving, and real estate. Therefore, it
is recommended to design tailored products to strengthen the difference of services
to meet customers’ needs and to increase the number of customers’ purchase
products and customers’ transaction willingness. In the aspect of marketing
strategies, the VIP customers’ privileges should be applied to extend the transaction
duration between customers and the case study bank.
In addition, the empirical results reveal that the dimension of financial advisors
does not support the two expected hypotheses. A further in-depth interview reveals
that the senior financial advisors of the case study bank are indeed more familiar
with expertise and marketing skills. Therefore, in establishing the customer
relationship, senior advisors are more oriented to manage the long-term customer
relationship from the perspective of ‘‘customers’ needs’’, which subverts the past
‘‘product-oriented’’ marketing concept. Achieving the corporate performance target
not by selling high-margin products is also in line with the case study bank’s
operating concept in the development of private wealth management.
On the other hand, the financial planning of the case study bank’s financial
advisors for the top wealth management VIPs is oriented to customers’ financial
management needs, which replaces the past product selling orientation by a full
range of financial planning and demands financial advisors to take care of each
customer’s assets carefully. For these above reasons, the dimension of financial
advisors has a less significant impact on the customer profit contribution.
Different from the past studies on the customer profit contribution by the wealth
management business, the paper introduces marketing theories into the analysis of
customer profit contribution and links sales performance indicators as an element in
finance, sales strategy, and CRM. This makes research findings more robust and
closer to reality. The paper introduces the concept of 4Cs and 5Ps in marketing mix
strategy and develops the attribute factors relevant to the customer profit
contribution from the perspective of both customers and banks. At the customer
end, the attribute variables are identified based on the sampled wealth management
Analysis of customer profit contribution 57
123
customers. At the bank end, the attribute variables are identified based on the
sampled financial advisors. These two dimensions are connected and the empirical
model concerning the relationship with the customer profit contribution is hence
developed. This can assist banks to operate their wealth management business and
formulate relevant marketing strategies. Meanwhile, the factors that influence the
customer profit contribution go beyond customers. The bank-related factors are also
in the mix. The paper constructs the customer profit contribution model by taking
into account both customer factors and the most important bank factor, i.e., financial
advisors. Different from the studies exploring the influence on the customer profit
contribution based on single factor, the paper constructs a more robust model. The
paper further proposes a set of references to the marketing mix strategy based on the
factors that influence the customer profit contribution. These can serve as a
foundation for banks to adjust their 4C ? 5P marketing mix strategy for the wealth
management business according to the customers and financial advisors of different
attributes. This can enhance customers’ loyalty, deepen the relationship with
customers, and enhance banks’ customer profit contribution. Besides, for banks, the
findings can also provide a set of dynamic marketing strategies to their financial
advisors dealing with the customers of varying attributes.
Finally, this paper suggests that coming researchers may use other methods such
as the structural equation modeling (SEM) or other multivariate analysis techniques
to assess and compare the empirical results under different methods to further
clarify the causal relationship among the variables and to make researches to be
more complete and stringent.
Acknowledgments The authors would like to thank the National Science Council of the Republic of
China, Taiwan for financially supporting this research under Contract No. NSC 98-2410-H-259-010-
MY3 and NSC 99-2410-H-141-007-MY2.
References
Arora N (2006) Estimating joint preference: a sub-sampling approach. Int J Res Mark 23(4):409–418
Arthur H (1994) Strategic database marketing. Probus Publishing, Chicago
Avila RA, Dodds WB, Chapman JD, Mann OK, Wahlers RG (1993) Importance of price in industrial
buying: sales versus purchasing perspectives. Rev Bus 15(2):34–38
Berger PD, Nasr NI (1998) Customer lifetime value: marketing models and applications. J Interact Mark
12(1):17–30
Burgess SM, Steenkamp JBEM (2006) Marketing renaissance: how research in emerging markets
advances marketing science and practice. Int J Res Mark 23(4):337–356
Crosby LA, Evans KR, Cowles D (1990) Relationship quality in services selling: an interpersonal
influence perspective. J Mark 54(3):68–81
Day GS (2000) Managing market relationships. J Acad Mark Sci 28(1):24–30
Garland R (2002) What influences customer profit contribution? Service-profit chain: non-financial
drivers of customer profit contribution in personal retail banking. J Target Meas Anal Mark
10(3):233–248
Harris RL (2009) Life insurance and wealth management: a perfect combination for the ultra-affluent.
J Wealth Manag 11(4):114–118
Hartfeil G (1996) Bank one measures profit contribution of customers, not just products. J Retail Bank
Serv 18(2):23–29
Jennings WW, Reichenstein WR (2008) The extended portfolio in private wealth management. J Wealth
Manag 11(1):36–45
58 T. T. Lin et al.
123
Kadiyali V, Sudhir K, Rao VR (2001) Structural analysis of competitive behavior: new empirical
industrial organization methods in marketing. Int J Res Mark 18(1–2):161–186
Keane TJ, Wang P (1995) Applications for the lifetime value model in modern newspaper publishing.
J Direct Market 9(2):59–66
Kyriakopoulos K, Moorman C (2004) Tradeoffs in marketing exploitation strategies: the overlooked role
of market orientation. Int J Res Mark 21(3):219–240
Lee CC, Lin TT, Chen CJ (2010) The determinant of customer profitability on the financial institution.
Serv Ind J 30(14):2311–2328
Lemmens A, Croux C, Dekimpe MG (2007) Consumer confidence in Europe: united in diversity? Int J
Res Mark 24(2):113–127
Liu HW, Huang HC, Lin YL (2009) Asymmetric effect of distribution intensity on marketing
performance: the moderating role of brand awareness. Asia Pac Manag Rev 14(3):251–262
Mulhern FJ (1999) Customer profitability analysis: measurement, concentration, and research directions.
J Interact Mark 13(1):25–40
Niraj R, Gupta M, Narasimhan C (2001) Customer profitability in a supply chain. J Mark 65(3):1–16
Palmatier RW, Scheer LK, Houston MB, Evans KR, Gopalakrishna S (2007) Use of relationship
marketing programs in building customer-salesperson and customer–firm relationships: differential
influences on financial outcomes. Int J Res Mark 24(3):210–223
Palsson AM (1996) Does the degree of relative risk aversion vary with household characteristics? J Econ
Psychol 17(6):771–787
Reinartz WJ, Kumar V (2000) On the profitability of long-life customers in a noncontractual setting: an
empirical investigation and implications for marketing. J Mark 64(4):17–35
Rosier ER, Morgan RE, Cadogan JW (2010) Marketing strategy and the efficacy of procedural justice: the
mid-level marketing manager in industrial service firms. Ind Mark Manag 39(3):450–459
Rust R, Zeithaml VA, Lemon KN (2000) Driving customer equity: how customer lifetime value is
reshaping corporate strategy. The Free Press, New York
Analysis of customer profit contribution 59
123
