How to implement Customer Relationship
Management system in third party logistics
companies
Submitted by
JONATHAN WANG
Advised by
PROF. TEO CHUNG PIAW
PROF. JOHN.III.BARTHOLDI
PROF. MOKHTAR.BAZARAA
DUAL MASTER OF SCIENCE IN
LOGISTICS AND SUPPLY CHAIN MANAGEMENT
THE LOGISTICS INSTITUE—AISA PACIFIC
DEC 2002
ACKNOWLEDGEMENTS
First of all, I want to thank to TLI-AP and my sponsor company YCH group, for giving me the
opportunity to learn in two elite universities, National University of Singapore and Georgia
Institute of Technology. It has been an enriching experience for me that I am sure will have lasting
impact for my future career.
As for the thesis, I want to first thank my advisor in NUS, Associate Professor Teo Chung Piaw,
who has given me a lot of good advice in the thesis writing and in the research. Without his kind
help, I will not be able to finish the thesis on time.
I must also give special thanks to my advisors in YCH group, Mrs. Lilian Tan and Mr. Patrick
Woo. I am grateful to them for the research topic and for answering my questions patiently during
my thesis writing. Without them, I could not have collected the needed data for the thesis.
In addition, I want to thank my advisors in Georgia Institute of Technology, Professor John. III
Bartholdi and Professor Mokhtar.Bazaraa. They help to shape the early stage of this research.
Finally, I want to give my genuine thanks to all the classmates in The Logistics Institute of
Asia-Pacific for their support and help in the thesis writing. This place, and this experience, would
have been less colorful without them.
Jonathan Wang
March 2002
Abstract
In a service sector like the 3PL industry in Singapore, customer satisfaction and retention are two
pertinent issues that have major impact on the competitiveness and profitability of a company.
Many 3PL companies are now trying to leverage on the tools of Customer Relationship
Management (CRM) to address the above issues. Successful CRM implementation cases in the
manufacturing sector have indicated that CRM is effective in increasing customer satisfaction and
in generating repeat businesses. However, most of these implementations focused mainly on data
mining and the central role of sale automation in satisfying customers. We argue in this thesis that
3PL companies in Singapore, however, should invest in customer complaint handling rather than
sales automation as the first step in CRM implementation, since the sales impact of each customer
is significantly larger than those experienced by a typical manufacturer selling to the mass market.
With the improvement in efficiency of complaint handling, staffs can zoom in on service problems
quickly. This is likely to lead to more satisfied customers and retention rate will increase. Besides,
it has the side benefits of streamlining customer handling process and leading to more enlightened
employees. In fact, the benefits of cultural change in the company that comes with CRM
implementation cannot be overemphasized. Due to capacity limitation, 3PL companies must also
identify the most valuable/critical customers for CRM implementation. This thesis proposes a
nine-cell strategy model to segment customers. The model takes both customer value and leaving
risk into account to give a comprehensive evaluation of customer status. Finally, the thesis
proposes a generic framework of CRM implementation in 3PL industry, which includes an
integration of complaint handling automation, sales automation and performance automation.
Key words: CRM, third party logistics, customer satisfaction, customer retention
Chapter1 Introduction
1.1 Overview
With increased globalization and proliferation of logistic service providers, many companies in the
3PL industry are beginning to recognize the importance of the ability to retain existing customer,
rather than attracting new one, because they contribute much more revenues than new customers.
Besides, it costs companies five times or more to attract a new customer than to keep an existing
one. (Amrit Tiwana, “The Essential Guide to Knowledge Management—E-business and CRM
Applications”, Prentice Hall, Inc 2001). A new concept, named Customer Relationship
Management (CRM), focusing on retaining and developing relationship with valuable customers,
was brought forward in the mid 80s.
In a short span of 20 years, CRM has already seen many successful implementations in both
manufacturing industry and service industry worldwide. But until today, few 3PL companies in
Singapore are familiar with CRM concept, let alone have the experience of CRM implementation.
Hence, this study seeks to explore a feasible way of CRM implementation that can be successfully
adapted to third party logistics industry in Singapore.
1.2 Research issues and achievements
One of the important issues in CRM is customer retention. As we mentioned above, CRM is used
to defend and develop the relationship with existing customers. Customer retention, therefore,
should be an important measurement. There are many factors that can affect customer retention.
By reviewing some CRM implementation cases in manufacturing industry, we find that most
manufacturers have put lots of efforts on sales automation. With shorter order cycle time and
higher sales process efficiency, companies expect to increase customer satisfaction and retention
rate as well. In contrast, customer complaint handling plays an important role in customer
satisfaction and retention in service industry. By conducting a comparison between Dell (one
example of manufacturers) and YCH group (one example of 3PL companies) in terms of business
characteristics, we find that the gap between actual quality and perceived quality in 3PL industry
can be bigger than that in manufacturing industry. Since the improvement in complaint handling
system can help to fill that gap and increase customer satisfaction, we propose to invest in
customer complaint handling as a first step of CRM implementation in 3PL industry. To support
the argument, we introduce a NAV model in chapter 3.
The second important issue we studied in the thesis is the benefits of CRM implementation. By
reflecting on the CRM implementation in YCH, two major benefits are identified. First, customer
satisfaction is increased. By automating the process of customer complaints handling, the response
cycle time is shortened significantly and the response efficiency is increased. More prevention
actions are taken during the daily operations so that the service quality is improved. As a result,
customers are more satisfied. Second, employees are able to understand better customer
requirements. With the better support of complaint handling system, employees in YCH can target
on customers’ needs more quickly and give right solutions. By analyzing the data collected from
two surveys, we discuss how YCH can achieve the two benefits through CRM implementation.
Another important issue in CRM is customer segmentation. Knowing the target customer to
implement CRM is very important to all companies. After reviewing some customer segmentation
methodologies in the literature, we propose a feasible method for customer segmentation and the
nine-cell strategy model, which can be used to determine customer priority and the corresponding
strategic responses.
Besides the issues mentioned above, we give a proposal of further implementation in 3PL
companies. The focus is about integration of sales automation, performance measurement
automation and complaint handling automation. Some new ideas such as “chain” sell are
introduced.
Chapter2 Literature Review
2.1 Overview
This chapter is to conduct a literature review on some relevant research papers in CRM
implementation. Unfortunately, there are scant literatures of CRM implementation conducted in
3PL industry. This chapter summarizes all relevant topics and literatures including CRM definition,
evolution, difference between CRM and TQM, benefits and perils of CRM, customer
segmentation, and the relationship between quality, loyalty, satisfaction, retention and profitability.
2.2 Definition of CRM
One definition from Krstin Anderson and Carol Kerr (2002) is that Customer Relationship
Management is a comprehensive approach for creating, maintaining and expanding customer
relationships. There are several words that are central to the definition of CRM. First, consider the
word “comprehensive”. CRM does not belong just to sales and marketing. It is not the sole
responsibility of the customer service group. Nor is it the brainchild of the information technology
team. While any one of these areas may be the internal champion for CRM in the organization, in
point of fact, CRM must be a way of doing business that touches all areas. When CRM is
delegated to one area of an organization, such as IT, customer relationships will suffer. More
details about why CRM suffered will be covered in the following paragraph. Likewise, when an
area is left out of CRM planning, the organization puts at risk the very customer relationships it
seeks to maintain. The second key word in the definition is “approach.” An approach, according
to Webster, is “a way of treating or dealing with something.” CRM is a way of thinking about the
dealing with customer relationships. We might also use the word strategy because CRM involves a
clear plan. In fact, we believe that the CRM strategy can actually serve as a benchmark for every
other strategy in the organization. Any organization strategy that doesn’t serve to create, maintain,
or expand relationships with the target customers doesn’t serve the organization. Finally, the
author mentioned the words “ creating, maintaining and expanding.” CRM is about the entire
customer cycle. When implementing CRM strategy, one will capture and analyze data about his
organization’s targeted customers and their targeted buying habits. From this wealth of
information, the organization can understand and predict customer behavior. Marketing efforts,
armed with customer intelligence, are more successful at both finding brand new customers and
cultivating a deeper share of wallet from current customer. Customer contacts, informed by
detailed information about customer preferences, are more satisfying. In addition, the author
claimed that the customer satisfaction is directly proportional to employee satisfaction. Therefore,
CRM not only affected one organization externally, but internally as well.
Some other definitions of CRM, such as one from Stanley A. Brown (2002) is: Customer
Relationship Management (CRM) is a combination of business process and technology that
seeks to understand a company’s customers from multiple perspectives to deliver identification,
conversion, acquisition, and retention. From Tricia Fox (2000), Customer Relationship
Management is the establishment, development, maintenance and optimization of long term
mutually valuable relationships between consumers and organizations. Successful CRM focuses
on understanding the needs and desires of the consumer and is achieved by placing these needs at
the heart of the business by integrating them with the organization’s strategy, people, technology
and business processes. All of these definitions emphasize that CRM should be comprehensive. It
is a combination of business process and technology instead of each one alone.
2.3 The evolution of CRM and difference between CRM and
TQM
Customer Relationship Management (CRM) is intimately related to Total Quality Management
(TQM), as CRM evolves from TQM philosophy. According to John Coldwell (2000), TQM says
that businesses don’t buy from businesses; businesses buy from people, and it is the people that
makes a difference with their attitude to quality. CRM is about managing the relationships
between the business and the customer—the other side of the TQM coin, in that it is not
businesses that buy from business; it is people that buy from business. TQM and CRM both
address the issues of customer satisfaction and customer retention. TQM focuses more on
improving products or services quality continuously so that the company can meet the increasing
customers’ expectation. But CRM tries to manage the customers’ data and forecast the customers’
behavior, the “behavior” mentioned here refers to customer expectations and purchasing custom.
2.4 Benefits of CRM
Companies may want to achieve different aspects of benefits by implementing CRM. For example,
Square D, a 100-year-old electric equipment maker, had multiplied its revenue, doubled the return
on capital and boosted sales per employee by 33% in 5 years after it implemented CRM. By
refining its customer strategy, New York Times, which is one of the most popular newspapers in
US, had made its circulation rise by 2% and its customer retention rate hit 94% while the industry
average was only 60%. (Darrell K.Rigby, Frederick F.Reichheld, and Phil Schefter, 2002) In
addition, Another famous US fashion magazine had cut down its marketing budget by 33% but
increased the revenue by 10% after it re-segment its customer group, making free-catalogs target
on more potential buyers. (Stanley Brown, 2002) In summary, the total benefits evolved from
CRM can be divided into two categories. One is cost reducing, including marketing cost, sales
cost and customer service cost. The other one is revenue increasing, including increasing
share-of-wallet, increasing customer retention rate and improving customer acquisition. (R.
Forsyth, 2002)
2.5 Perils of CRM
CRM has been regarded as a trend. But still 55% of the CRM projects have failed in achieving
their goals. (Darrell K.Rigby, Frederick F.Reichheld, and Phil Schefter, 2002). Some research
papers have been involved in investigating the reasons. For example, in the article, “Avoid the
Four Perils of CRM”, published in the Harvard Business Review, 2002, the authors wanted to
re-define the meaning of customer relationship management (CRM), which has been
misunderstood as a software concept instead of a business strategy concept. This distorted
understanding of CRM has generated four perils of CRM implementing:
1. Implementing CRM before creating a customer strategy. This means that the companies
buy a CRM package first and then try to retrofit their customer strategy to match the
software. Instead, the technology should be based on the good customer segmentation and
marketing goals.
2. Installing CRM technology before creating a customer-focused organization. The authors
argued that having a strategy is not enough, a CRM rollout will succeed only after the
organization and its processes—job description, performance measures, compensation
systems, training programs, and son on—have been restructured in order to better meet
customers’ needs.
3. Assuming that more CRM technology is better. Whether a CRM program is successful or
not could not be judged by the level of technology used. Merely relying on a
technological solution, or assuming that a thigh-tech solution is better than a low-tech one,
is a costly pitfall. Instead, less expensive technology should be deployed as long as the
same goal is reached.
4. Stalking, not wooing, customers. This means that the companies target on the wrong
customers who are not willing to establish the relationship with the companies while
annoying the real potential ones. This happens when the company believes that by
investing as much as possible on the new technology, the machine will automatically
retain the customers and make them satisfied. This wrong concept, which is the origin of
the four perils, has led many CRM programs to failure.
Finally, the authors claimed again that successful CRM depends more on strategy than on the
amount the companies spend on technology. Powerful IT tools are effective only when being led
by the right business strategy.
In addition, Kimberly B.Caisse (2002) also pointed out some perils of automated customer
interaction. Though admittedly the involvement of some new technologies such as interactive
e-mail and instant message can cut down the communication cost and possibly increase customer
satisfaction, the author argued that companies still should use it with caution because the
inappropriate response from the naïve system will easily annoy the customers. The author listed
some examples of using new automated response tools, ranged from robotic chat to interactive
e-mail. Being expected to perform well, but these tools seems to disappoint those advocators. Just
as Temkin, who is the principal analyst of Forrester Research, said: “Sending e-mail alerts to
customers that aren't interested can actually do more harm than good." Although this kind of
automated response tools, called self-service tech is moving forward, according to the author, it is
still a long way to go before it can be perfected, and really contributing to increase customer
satisfaction. Right now, human agents are still important and needed to respond effectively to
customers, though the use of automated systems are growing.
2.6 Determine customer value
One of the difficulties in CRM implementation is how to identify the customer value. Charles
Wilson had summarized some ideas in his book “Profitable customer” in 1996. The whole book
focuses on “customer value”. The topic ranges from how to identify customer values to how to
retain the profitable customers. First of all, the company must determine the value of each
customer. It is the fundamental ingredient of customer segmentation. By introducing the DCP
(Discounted Customer Profitability) model, the author had shown a feasible way to determine the
customer value. According to the author, DCP model is not a scientific analysis and requires a lot
of estimates and judgments. However, by formally considering the components of customer
profitability, the company can develop a more intricate understanding of where the profit
opportunities reside. The author argued that customer profitability should include the following
components: Annual sales, Gross income, Costs to interface, Net customer profitability, Expected
length of relationship and Discounted customer profitability.
Annual sales, refers to the sales for the last financial year (including after sales income). Gross income, refers to the net sales
after discounts, minus the cost of products and overheads (excluding the costs to interface). Costs to interface include the cost of
marketing, selling, distribution, service, administration, stock holding, customization, promotions etc. Net customer profitability
(NCP) refers to the gap of gross income and costs to interface. Expected length of relationship indicates how long the customer
will remain loyal.
Discounted customer profitability (DCP) reflects the comprehensive image of a customer value.
Also, these components have some relationship with each other. Gross income-Costs to
interface=NCP, NCP*Expected length of relationship=DCP. Plugging in the real data of each
customer into DCP model, companies can at least get a relative importance of each customer and
thus determine which customer is more valuable than others.
After determining each customer value, companies are then interested in how to keep those
profitable customers. The author stated seven routes to “lock in” the core profitable customers,
which are as follows:
1. Achieve and surpass current expectations
2. Elevate the relationship
3. Bond the customer to the companies
4. Prepare for future needs
5. Manage customers which are in decline
6. Reward loyalty
7. Never believe that a core customer is “safe”
First, the author argued that companies should listen carefully to the customers’ needs and
perceive the performance of their competitors. Companies can win back customers only when they
surpass their competitors’ performance. Merely satisfying its customer is not enough because the
competitor may do it better.
Elevating the relationship means that companies should make their status with the core customers
from an available supplier to an approved supplier, and then to a preferred supplier, finally to a
partner. The higher the supplier’s status, the longer the relationship with customers can last.
Bonding the customer to the company suggests a multi-link between the customer and the
company. Besides the simple communication between the sales and purchasing staffs of a
company and its customer, more linkages should be established between both the top
managements and R&D staffs of two organizations.
Companies can be obsessed with satisfying current customer needs but fail to consider future
requirements. Yet the majority of a customer’s DCP resides in the future rather than the present.
Therefore, the author reminds that companies must think about the core customer of the future and
involve customer in the R&D.
The author claimed that it is easier to recover an account in decline than when it has already
terminated business. Therefore, companies should spot the problem, which causes the decline of
the core customers, and make a response as soon as possible.
Also, the author suggested that companies should give a reward to those core customers to
encourage loyalty. The ideal reward should have a relevance to the companies’ core business and
make customers feel that they have been rewarded. In addition, those rewards should have an
effect on promoting loyalty and be justified with the total cost.
Finally, the author reiterated that companies have to be constantly on their guard to those most
profitable customers. Complaints from customers are important because the quiet customers are
more easily to leave for your competitors.
2.7 Links among service quality, satisfaction and customer
retention
Some words such as service quality, customer satisfaction, customer loyalty etc. appear frequently
in the research paper related to CRM. They are important because they have several relationships
between each other and together can affect the company profitability. Quality, by its definition, is
the measurement whether customers’ enjoyment of it exceeds their perceived value of the money
they paid for the products or services. (Chuck Chakrapani, 1998) Poor quality usually decreases
profitability by increasing costs (both visible and invisible). Chuck Chakrapani proposed a
downward spiral model in his book “How to measure service quality & customer satisfaction.”
One of the better known quality models, the SERVQUAL instrument (Parasuraman et al., 1988),
is a 22-item scale that measures service quality along five factors, namely reliability,
responsiveness, assurance, empathy and tangibles. This forms the foundation on which all other
works have been built. Interestingly, the conceptualization, dimensionality, operationalization,
measurement and applications of SERVQUAL have been subjected to some severe criticisms as
well (see Buttle, 1996). In spite of such reprehension on the efficacy of SERVQUAL across
different service settings, there is a general agreement that the 22 items are reasonably good
predictors of service quality in its wholeness. But a careful scrutiny of the 22 items reveals that the
items at large deal with the element of human interaction/intervention in the service delivery and
the rest on the tangible facets of service (such as the effect of atmospherics, design and décor
elements, appearance of equipment, employee appearance, etc.). Therefore the SERVQUAL
instrument seems to have overlooked some other important factors of service quality, namely the
service product or the core service, systematization/standardization of service delivery (the
non-human element), and the social responsibility of the service organization.
Although there is a general conformity on the distinctiveness of service quality and customer
satisfaction from a conceptual point of view, the operationalization of customer satisfaction is
somewhat hazy. For instance, Cronin and Taylor (1992) defined and measured customer
satisfaction as a one-item scale that asks for the customers' overall feeling towards an organization.
By using a single item scale to measure customer satisfaction, Cronin and Taylor's approach fails
to do justice to the richness of the construct, as it has failed to acknowledge that, like service
quality, customer satisfaction is also likely to be multidimensional in nature. Bitner and Hubert
(1994) used four items to measure the customers' overall satisfaction with the service provider.
The authors introduced the concept of encounter satisfaction, and devised a nine-item scale to
measure the same (i.e. the customers' satisfaction with a discrete service encounter).
Service management literature, on the other hand, proposes that customer satisfaction influences
customer loyalty, which in turn affects profitability. Proponents of this theory include researchers
such as Anderson and Fornell (1994); Gummesson (1993); Heskett et al. (1990); Heskett et al.
(1994); Reicheld and Sasser (1990); Rust, et al. (1995); Schneider and Bowen (1995); Storbacka
et al. (1994); and Zeithaml et al. (1990). These researchers discuss the links between satisfaction,
loyalty, and profitability. Statistically-driven examination of these links has been initiated by
Nelson et al. (1992), who demonstrated the relationship of customer satisfaction to profitability
among hospitals, and Rust and Zahorik (1991), who examine the relationship of customer
satisfaction to customer retention in retail banking. The Bank Administration Institute has also
explored these ideas, in particular Roth and van der Velde (1990, 1991).
The service management literature argues that customer satisfaction is the result of a customer's
perception of the value received in a transaction or relationship - where value equals perceived
service quality relative to price and customer acquisition costs (see Blanchard and Galloway, 1994;
Heskett et al., 1990) - relative to the value expected from transactions or relationships with
competing vendors (Zeithaml et al., 1990). Loyalty behaviours, including relationship continuance,
increased scale or scope of relationship, and recommendation (word of mouth advertising) result
from customers' beliefs that the quantity of value received from one supplier is greater than that
available from other suppliers. Loyalty, in one or more of the forms noted above, creates increased
profit through enhanced revenues, reduced costs to acquire customers, lower customer-price
sensitivity, and decreased costs to serve customers familiar with a firm's service delivery system
(see Reicheld and Sasser, 1990).
Other relevant literature is found in the marketing domain. It discusses the impact of customer
satisfaction on customer loyalty. Yi's "Critical review of customer satisfaction" (1990) concludes,
"many studies found that customer satisfaction influences purchase intentions as well as
post-purchase attitude" (p. 104).
The marketing literature suggests that customer loyalty can be defined in two distinct ways
(Jacoby and Kyner, 1973). The first defines loyalty as an attitude. Different feelings create an
individual's overall attachment to a product, service, or organization (see Fornier, 1994). These
feelings define the individual's (purely cognitive) degree of loyalty.
The second definition of loyalty is behavioural. Examples of loyalty behaviour include continuing
to purchase services from the same supplier, increasing the scale and or scope of a relationship, or
the act of recommendation (Yi, 1990). The behavioural view of loyalty is similar to loyalty as
defined in the service management literature. This study examines behavioural, rather than
attitudinal, loyalty (such as intent to repurchase). This approach is intended, first, to include
behavioural loyalty in the conceptualization of customer loyalty that has been linked to customer
satisfaction, and second, to make the demonstrated satisfaction/loyalty relationship immediately
accessible to managers interested in customer behaviour linked to firm performance.
Both the service management and the marketing literatures suggest that there is a strong
theoretical underpinning for an empirical exploration of the linkages among customer satisfaction,
customer loyalty, and profitability. The relatively small quantity of empirical research performed
on these relationships to date (Storbacka et al., 1994) is probably the result of the paucity of
organizations' measuring "soft" issues, such as customer satisfaction and customer loyalty, in
meaningful ways.
The tangible benefits of customer retention were first published by Dawkins and Reichheld (1990).
They claim that higher retention rate leads to higher net present value of customers. The attraction
of customer retention management continued to be prominently advanced in subsequent related
papers and a book (Reichheld and Sasser, 1990; Reichheld and Kenny, 1990; Reichheld, 1993,
1994, 1996). Reichheld (1996) provides comprehensive details of Bain & Company's prescriptions
(etic) of managing customer retention, drawn from its consultants' observations of clients'
practices. The benefits of customer retention, as experienced by clients and Bain & Company,
were cited frequently by marketing scholars, which reflected their acknowledgements of its
theoretical and practical relevance (see for example, Kotler et al., 1999, p. 483; McDonald, 1999,
p. 390; Gummeson, 1999, p. 188; Peck et al., 1999, p. 46).
If customer retention leads to higher profitability, as Dawkins and Reichheld claimed, do
companies proactively retain their customers? How do companies, in practice, keep their
customers? What are the gaps between theories and practice? Can the espoused strategies,
particularly those proposed by Reichheld (1996), be applied in these companies? That paper
reports a case study of four companies that examined the prevailing emic in these firms as
compared to the etic espoused by Reichheld (1996). This is part of an intensive study that
explored "how" and "why" contextual conditions shaped the way firms retain their customers in
the way they did.
From the service marketing perspective, the way to retain customers is to improve customer
service quality and satisfaction (Berry and Parasuraman, 1991; Zeithaml and Bitner, 1996, p. 176).
In a related study, Ennew and Binks (1996) examined the links between customer
retention/defection and service quality in the context of relationships between banks and their
small business customers in the UK. Their findings support the hypothesis that retention is
influenced by service quality, in terms of both functional and technical, and customer relationships.
They also found that trust in customer-banks relationships has the largest impact on potential
defection, followed by general product features. The investigation, however, did not provide
indications of the financial impacts retention had on the banks' profitability and it is implied to
refer to branch-based banking where customers' expectations on relationships are likely to be
greater than telephone or Internet banking.
From the industrial marketing perspective, the way to retain customers is by forging multi-level
bonds comprising financial, social and structural bonds. Turnbull and Wilson (1989) examined,
through a case study, the potential benefits of protecting profitable customer relationships through
not just social, but also structural bonds in the context of industrial marketing. Social bonds,
according to Turnbull and Wilson, refer to positive interpersonal relationships between the buyer
and seller. Although they did not provide an explicit definition of structural bonds they implied,
through their illustrations, that structural bonds refer to relationships that are built upon joint
investments that cannot be retrieved when the relationship ends. This may be due to the
complexity of the relationships and the cost of changing to another supplier. In terms of training of
technicians, for example, a switch to another type of machine would require total retraining of
these technicians. Structural bonds, therefore, had helped create value to the customers by saving
the costs of retraining or making a new investment with a new supplier.
From the 3PL industry perspective, however, not much related study has been conducted on the
way of retaining customers. First of all, 3PL companies are service providers. In this sense, they
have the same characteristics as in other service industries, such as banking and airline. The
retention rate can be increase by improving service quality and customer satisfaction. At the same
time, the retention rate can also be increased by forging multi-level bonds (such as developing
joint ventures) or developing deeper relationship. Further empirical works carried out thus far
were attempts to study and model the mechanics of customer retention, in terms of its potential
cause and effects of customer retention to companies (Page et al., 1996; Payne and Frow, 1997).
Page et al. (1996), in their retrospective study, investigate the relationship between customer's age
or tenure and customer's contribution and the firm's market share in an industrial marketing
context. If we combine all the opinions of current researches on customer retention, we can
conclude that customer retention is subjected to the following factors: customer age (or life cycle),
relationship depth, satisfaction, price sensitivity and competition environment. The mathematics
form for the relationships is: Customer Retention (CR)=f (customer life cycle, relationship depth,
satisfaction, price sensitivity, competition environment) Among the five factors, four of them
(customer life cycle, relationship depth, price sensitivity, competition environment) are very
objective or hard to change by the vendor. But 3PL companies still can do something to improve
customer satisfaction and thus increase the retention level.
Chapter3 Sales automation or complaints handling
automation?
3.1 Overview
In most successful cases of CRM implementation, companies started their implementation with
sales automation. A typical example is Dell Company, well known for pioneering the “direct
sales” mode. Dell designs a personal style web that can provides an intensive communication
between customers and Dell. With the support of strong back database, customers can better
realize self-service via website. On the other hand Dell can collect customer feedback and
purchase behavior information on web too, which can help better understand customer needs.
Most of the sales processes are automated. As a result, the order cycle time is shortened
tremendously and order process accuracy is increased. Customers are satisfied with the kind of
service provided. But the success in Dell cannot be automatically transferred to other industry. In
this chapter, a comparison between Dell and 3PL companies in terms of business characteristic is
conducted. The similarity and difference are listed. Based on the comparison, we propose that 3PL
companies should invest in complaints handling automation rather than sales automation as the
first step of CRM implementation. To support the argument, we introduced NAV calculation
model in the end of the chapter.
3.2 Business character comparison
If we want to decide whether sales automation in CRM should be the central focus in 3PL industry
just as that in manufacturing industry, we should first understand the similarity and difference
between the two industries. Therefore we conduct a thorough comparison in terms of business
characters, focus on three aspects: customer base, product features and relationship respectively.
(See table3-1)
First of all, let us compare the customer base between Dell and 3PL companies. A 3PL company
usually has companies only as its customers rather than an individual. But to dell, it can sell PC to
an individual and on the other hand, it can sell PCs to a company, like Johnson & Johnson, to
equip its IT department. So Dell can have either company customers or individual customer.
Table 3-1 Comparison of business character between Dell and 3PL companies
Dell 3PL
Customer base
customer type group or individual group
customer segmentation simple complex
customer location worldwide restricted to some area
Product features
products tangible and easy to measure intangible and hard to measure
cost structure simple complex
replacement easy difficult within some period
Product input capital and knowledge capital and human
quality control easy hard
Relationship
relationship can be terminated anytime bonded by contract
Now focus more on support Now focus on more core product
customer satisfaction service level level
Secondly, Dell’s customers can be located at any corner of the world as long as they can log onto
Dell’s website. But a 3PL’s customers are usually located within some area. The reason is that all
services provided by 3PL companies are based on some physical facilities, such as warehouses
and lorries. For example, suppose there is a Singapore based 3PL company and all its warehouses
and lorries are located at Singapore. Only those companies who are also located at Singapore may
potentially be the 3PL’s customers. In other word, it is hard to image that a European company
located thousands of miles away will use the warehouse in Singapore unless the European
company has a Singapore branch. Therefore, a 3PL’s business is strictly limited within some areas.
Thirdly, it is easier for Dell to segment its customers. The only criterion of the segmentation is
how many PCs a customer has bought annually. The more PCs a customer has bought, the more
profitable customer he is regarded. But the case in the 3PL industry will never be so simple. Here
is an example, suppose there are two customers, A and B. Customer A wants to rent the whole
warehouse for half a year but customer B wants to rent half of the warehouse for a year. Assuming
that the rental rate is the same to both customers, which one is more profitable to the 3PL
company? The answer is “it depends”. Sometimes customer A is more profitable while sometimes
customer B is more profitable. Customer A makes the warehouse full utilized for half a year. But
in the second half year, if no new customer comes in, then the warehouse will be totally empty and
generate no revenue but cost. On the other hand, customer B can generate revenue for the
warehouse for a whole year and during the year some other customers can also rent the other half
space of the warehouse and thus bring more revenues. In that case, you may consider customer B
as more profitable. But in some cases, it is on the contrary. The existing of customer B will
sometimes make the company lose some big customers. Suppose customer B has rent half of the
warehouse for a year and then another customer C wants to rent the whole warehouse for a year.
But because of the occupancy of customer B, the company cannot meet customer C’s requirement
and thus lose a big deal. The dilemma is because the service of a 3PL company is always
constrained by its capacity, thus should take capacity issues into highly account. But Dell seldom
considers its manufacturing capacity as a problem. Another issue that makes the segmentation
more complex for a 3PL company is the backhaul problem. Suppose a customer want to book a
truck to deliver something from point A to point B. He will only pay for the trip from point A to
point B. But the truck still has to come back from point B to point A. This backhaul cost is not
covered by the customer payment. So a 3PL company must try to arrange another deal on the way
from point B to point A otherwise the cost on the backhaul can bring back nothing. Another
customer has something to deliver from B to A but he is only willing to pay half of the price. In
that case, it is hard to determine the value of that customer. On the one hand, he contributes only
half of the normal customers but cost the same. On the other hand, he contributes the extra
revenue which originally expected to be loss. Too many variables make it hard for a 3PL company
to segment its customer properly.
The next aspect we are going to compare is the product. The product of Dell is obviously the PC.
It is tangible that people can easily tell whether the product is good or not before you buy it. But
the product of a 3PL is quite different. The product offered by 3PL companies is intangible service.
You rent some space from a 3PL company’s warehouse and let him take care of your goods or you
let 3PL deliver something for you at some time. All these are the products they offer you. Unlike
those physical PCs, you can hardly tell whether a service is good or not before you buy and
experience such kind of service. In addition, if one is not satisfied with Dell’s PC, he can easily
terminate the relationship, deciding not to buy a Dell Pc any more. All his loss is just the PC that
has been bought. He may choose another brand of PC immediately. But a customer of a 3PL
company will be more cautious because once a customer is going to outsource his logistics to a
3PL company, both sides usually sign a contract which lasts at least 1 year. Also, some surveys
indicate that most companies usually outsource their logistics to only one 3PL company which
means if the service provided by the 3PL cannot meet the requirement, the customer’s logistics
work will crash at all. Compared with the relationship between Dell and its customer, the
relationship between a 3PL and its customer is bonded and hard to shift within a long period. In
that reason, it usually takes long and more effort for a company to decide to whom it should
outsource its logistics work than to decide from whom it should buy some PCs.
The cost structure of two kinds of products is totally different. At Dell side, total cost of serving a
customer should include marketing cost, product cost, delivery cost and after-sales support cost.
Marketing cost refers to the cost spent on the advertisement in order to attract the customers.
After-sales support cost refers to the repair cost and free technique support cost. We can assume
that Dell pays the same marketing cost and support cost to each of its customer. The product cost
is linearly associated with the volume of product purchased and the delivery cost is also associated
with the volume in some extent. So the total cost of serving a customer is only affected by the
volume he purchase. The cost structure is simple and easy to understand. But the cost structure of
a 3PL company is not as simple as Dell’s. The cost is usually decided by some other factors
besides volume. Suppose a customer has outsourced its warehouse to a 3PL company and ships
goods from the 3PL’s warehouse. The total volume of goods is fixed every month. If the customer
wants 2 pallets of goods once, then it will take the 3PL company 3 times to ship those demand
goods every month. But if the customer can demand 3 pallets once, then it will only take the 3PL
twice to ship demand goods. As we know, it takes a 3PL company almost the same cost to ship 2
pallets or 3 pallets. But different arrangements can affect the ship times thus change the total cost.
Obviously, shipping 3 pallets once will save the 3PL’s handling cost by 33%. Now we can see that
although the volume of service purchased by the customer is same, the cost of serving a customer
will be different.
Dell has been equipped with many automation tools, such as auto sales, auto technique support
and auto call center, etc. It is possible for Dell’s customer to buy a PC without human interaction.
The same case cannot happen in 3PL industry currently. Though being equipped with AS/RS
(Auto Storage and Retrieve System), 3PL industry currently is still a human intensive industry.
Most of the logistics process cannot be realized without human interaction. For example, it is the
human that can drive a truck and deliver the ordered goods to customers. The impression of a 3PL
company to its customer is not from the website but mostly from the driver. Therefore, it is very
important to train the people, especially the drivers to be more customer-oriented instead of
implementing automation everywhere for all the 3PL companies.
The last item in the product aspect we are going to compare is the quality control. Quality can
have two dimensions of meanings, actually quality and perceived quality. (Professor Jacques
Horovitz, “The seven secrets of service strategy”, Prentice Hall, 2000) Actually quality is the real
quality that a company delivers while perceived quality is the quality that a customer perceives.
Usually actual quality differs from perceived quality. This phenomenon is more obvious in 3PL
industry, which belongs to service industry, than in manufacturing industry. Many studies have
been conducted to improve the quality of production while less efficient ways have been found out
to improve the quality of service. Why? It is because the automation of production that each tiny
process can be monitored and controlled by computers precisely. But in an industry full of human
involvement like 3PL industry, the quality is hard to control because the uncertainty of human
beings is hard to predict. Besides, some other factors such as weather can also affect the service
quality dramatically. For example, a delivery is delayed because the delivering truck is blocked by
a big storm.
The third aspect we are going to compare is customer satisfaction. A survey conducted by Dr.
Edward H. Frazelle in 2001 revealed that the customer satisfaction has three levels. The first level
of satisfaction relies on the performance of a company’s core business; the second level relies on
the support service and the highest level of the customer satisfaction relies on the emotional factor.
Table 3-2 has listed all the three levels of satisfaction between Dell and a 3PL company.
As we can see in the table, in PC manufacturers, like Dell, the core business is of course the PC
itself. If they can provide a good performance PC at a reasonable price, then customers will be
Table 3-2 Indicators of three satisfaction levels in Dell and 3PL companies
Dell 3PL
Large warehouse capacity, on-time
A good performance PC at a reasonable delivery, efficient logistics network
Core business price design
24 hrs technique support, repair service,
easy price check and order, on time 24 hrs order track, quick response
Support service delivery for the customer complaints
All the employees are courtesy and
Customized PC for different customers, professional, aiming to make
help customer realize the maximum customer's logistics part
emotional benefit at a minimum cost outstanding
satisfied. Here the good performance means both high speed and reliability. Most PC
manufacturers can reach the expectation in this level now, thus it is hard to distinguish between all
the competitors in this level currently. Competition has moved to the second satisfaction
level—support service, which includes both pre-sales and after-sales service, easy order and
on-time delivery. It has been a key battlefield for all of the PC manufacturers. Some big players
have invested a lot on building a sophisticated IT system, trying to raise the customer satisfaction
and win more market share. As a leader in PC manufacturing industry, Dell has been outstanding
in the second level and steps forward to the emotional level. Dell can help customers optimize the
PC configuration, achieving the maximum benefits at the minimum cost for customers. As long as
a customer keys in his requirement, including the expecting function, total budget and other
constraints, Dell can immediately propose an optimized purchasing plan to the customer. Also,
Dell can figure out the total savings on the optimized plan, giving a clear picture of ROI. By doing
so, all the customers realize that Dell is striving for creating values for them. Such an emotional
satisfaction is very important to establish the long-term relationship with customers. But in 3PL
industry, the key performance indicator still lies on the core business level, which includes
warehouse capacity, transportation ability, etc. Big 3PL companies have lots of cash to book in
enough capacity thus can fulfill more orders and promise its delivery time. The small players
cannot guarantee their customer’s delivery time but they are much cheaper. In this sense, CRM is
more adapted to those big 3PL companies because their customers are less price-sensitive and
have more potential demand on the support service and emotional satisfaction.
3.3 Quality measurements comparison
Dell is a representative of manufacturing industry while 3PL companies belong to service industry.
The industry category difference decides the different measurement in quality issues. Those
manufacturers, such as Dell, pay more attention to actual quality while 3PL companies put more
emphasis on customer perceived quality. The gap between actual quality and perceived quality
(listed in table3-3) makes quality control more difficult for 3PL companies than for manufacturing
companies, which urges 3PL companies to shrink the gap as much as possible.
Table 3-3 Comparison of Quality control between Dell and 3PL companies
Dell 3PL companies
Inventory management, Warehouse
Storage and server, notebook, management, Inbound/Outbound
desktop,network,software and transportation, freight forwarding,
Products delivered peripherals Insurance brokerage,
Inventory accuracy, delivery
mean running time without accuracy, collection accuracy,
Quality measurement error, product life cycle arrival on-time,
Gap between actual and
perceived quality small big
3.4 Customer complaints handling automation in 3PL
companies
Based on above comparisons, we noticed that sales automation plays a less important role in 3PL
industry than in manufacturing industry. In manufacturing industry, what both manufacturers and
their customers concerns about is the product. Manufacturers are concerned about how many
products they can sell annually. Customers are concerned about whether the product is in good
quality and when can they get the products. They communicate with each other through sales
sector. Each sales agent deals with hundreds of customers and hundreds of product SKUs. Such a
large quantity of information makes sales sector become the bottleneck of the whole business
process. Further more, long order process cycle time and low process efficiency damage the
customer satisfaction. In that case, sales automation can release most workload of sales agents. It
can help to shorten order process time and increase efficiency. The investment in sales automation
system can be justified by the increased sales opportunities and customer satisfaction. In 3PL
industry however, customer satisfaction is mostly associated with service quality, which consists
of logistics service quality and support service quality. As a major part of support service,
customer complaint handling becomes one of the key measurements of service quality. Both
response time and efficiency can affect customer satisfaction significantly. In addition, the
response of complaints can affect the logistics service quality as well. If 3PL companies can make
use of those complaints and make improvements accordingly, then the logistics service quality can
be improved. Unlike manufacturers who can justify the investment in sales automation by
increased sales opportunity, 3PL companies should justify the investment by customer retention
rate. The increased or decreased retention rate can directly affect the profitability.
3.5 Links between customer retention and profitability
Customer complaint handling is so important that it is linked with customer satisfaction. Customer
satisfaction is also linked with customer retention (Kaj Storbacka, Tore Strandvik, Christian
Grönroos, 1994). The concept of customer retention is appealing because, unlike relationship
marketing and service quality initiatives, improvements in retention can be correlated to an
increase in profitability (Reichheld and Sasser, 1990). Now we are interested in the relationship
between customer retention and profitability. If our assumption that the increase of customer
retention can also increase the profitability is true, then the investment in customer complaint
handling system is justified by ROI.
Suppose that YCH keep its customer retention rate at x%. That is, each year x% of the existing
customers of YCH will continue to be its customers and 1-x% of the existing customers will
terminate the contracts with YCH. Due to the capacity restriction, we assume that the number of
customer served in YCH remains stable each year, which indicates that once X number of
customers leave, then X number of new customers will come to take place. The assumption is also
to prevent that the profit is changed by the increase or decrease of the customer number. Let A
denote to the total customer number each year. Let r denote to the average annual revenue
contribution of each customer. In the meanwhile, r is a function of t, which is regarded as a time
variable. According to the statistics of finance report of YCH, function r(t) can be looked on as a
discrete function of time t, whose expression is described as follows:
r (1) if t 1
r (t ) r (2) if t 2
r if t 3
We assume that the company has to spend c1 (t ) to keep all customers (including those new
prospecting customers) and spend to c 2 prospect new customers. c1 (t ) is a function of t. In
addition, c1 (t ) is always equal to 0.9r (t ) . To make the problem easy to study, we assume that
no other costs occur to affect the profits. Let’s denote P to the profits of YCH and i to the annual
interest rate. All the variables and parameters are summarized as follows:
P—profits
A—total customer number
x—customer retention rate
r(t)—average annual revenue contribution of a customer during t year
c1 (t ) --average annual cost of keeping a customer
c 2 --average cost of prospecting a new customer
i—annual interest rate
First of all, we want to investigate the revenue of cost generation of those customers, who entered
YCH now, represented by time slot 0.
Year 0 Year 1 Year 2
Revenue Ar Axr Ax 2 r
Cost Ac1 Axc1 Ax 2 c1
Similarly, we now calculate the revenue and cost generation of those customers, who entered the
company in year 1.
Year 1 Year 2 Year 3
Revenue A(1 x)r (1) A(1 x) xr (2) A(1 x) x 2 r (3)
Cost A(1 x)( c1 (1) c2 ) A(1 x) xc1 (2) A(1 x) x 2 c1 (3)
For those customers entered the company in year 2
Year 2 Year 3 Year 4
Revenue A(1 x)r (1) A(1 x) xr (2) A(1 x) x 2 r (3)
Cost A(1 x)( c1 (1) c2 ) A(1 x) xc1 (2) A(1 x) x 2 c1 (3)
…………
After we derive the formula for those customers who entered the company in year 3, year 4 and so
on respectively, we find that the revenue and cost generation are all the same except for the year in
which the revenue and cost generated. We are interested in the Net Asset Value (NAV) of the
continuous company profit stream. We use NAV n represents the NAV of the total profits from
those customers who entered the company in year n. And we also know:
NAV NAV n
n 0
For the customers who entered the company in year 0
Axr Axc1 Ax2 r Ax2 c1 Ax3 r Ax3 c1
NAV 0 = Ar Ac1 ........
1 i (1 i) 2 (1 i) 3
1 i
= A(r c1 )
1 i x
For the customers who entered the company in year 1
NAV1 =
A(1 x)(r (1) c1 (1) c2 ) A(1 x) x(r (2) c1 (2)) A(1 x) x 2 (r c1 (3))
.......
1 i (1 i) 2 (1 i) 3
A(1 x)[r (1) c1 (1) c2 ] A(1 x) x[r (2) c1 (2)] x2
= A(r c1 )(1 x)
1 i (1 i) 2 (1 i) 2 (1 i x)
For the customers who entered the company in year 2
A(1 x)(r (1) c1 (1) c2 ) A(1 x) x(r (2) c1 (2)) A(1 x) x 2 (r c1 )
NAV 2 = ….
(1 i) 2 (1 i) 3 (1 i) 4
A(1 x)[r (1) c1 (1) c2 ] A(1 x) x[r (2) c1 (2)] x2
= A(r c1 )(1 x)
(1 i) 2 (1 i) 3 (1 i) 3 (1 i x)
After we calculate NAV1 and NAV 2 , we find that NAVn
A(1 x)[r (1) c1 (1) c2 ] A(1 x) x[r (2) c1 (2)] x2
A(r c1 )(1 x)
(1 i) n (1 i) n1 (1 i) n1 (1 i x)
when n 1
(This Formula can be proven by mathematics induction method, detail of proof in Appendix D)
1
NAV NAV n NAV0 NAV1 (1 1 i )
1
n 0
1
1 i
i 1
N A V N A V
0 1
i
1 i i 1 A(1 x)[ r (1) c1 (1) c 2 ] A(1 x) x[r (2) c1 (2)]
A(r c1 ) + {
1 i x i 1 i (1 i ) 2
x2
A(r c1 )(1 x) }
(1 i) 2 (1 i x)
After modeling the relationship between customer retention rate and company profitability, we are
going to apply the data collected from YCH into the model to see the quantitive results. The
retention cost refers to the operation cost, customer service (major in the building and maintaining
customer handling system) cost, employee training system and other administration cost. The cost
of acquiring a new customer includes sales agents’ salary, bonus, telecommunication cost, visit
cost and all kinds advertisements cost. The interest rate is according to DBS deposit rate. All
parameters are as follows:
A=20
r=2800000
r(1)=0.3r=840000
r(2)=0.7r=1960000
c1 (1) 0.9r (1) 756000
c1 (2) 0.9r (2) 1764000
c 2 =60000
i =1.25%
After plugging in the data collected from YCH, the NAV with retention rate 100% is
NAV100% 567000000 (S$)
Before YCH implemented CRM, the retention rate is 90%, then
NAV90% 500866666 (According to appendix E)
NAV profits NAV100% NAV90% 66133334
The estimated annual cost of complaint handling system is 500000, then
1 i
NAVcos t 500000 ( ) 40500000
i
NAV profits NAVcos t 25633334
Chapter4 Benefits of CRM—satisfied customers
4.1 Overview
One of the major benefits of CRM is increased customer satisfaction. To find out whether
customer satisfaction is increased after CRM implementation, we conducted a survey among 15
key customers in YCH. Some of them have been implemented customer complaints handling
automation while some others haven’t. By comparing the response time, response efficiency and
satisfaction level of two groups of customers, we can conclude whether the complaints handling
automation system can increase customer satisfaction level.
4.2 External survey
The target respondents of the survey are major customers of YCH. The survey has 2 major
purposes. 1. Investigate customer satisfaction level. 2. Figure out leaving barrier for each customer.
As mentioned before, overall customer satisfaction depends on two issues: one is customer
measurement on logistics service performance and the other one is measurement on support
service performance. In this survey, we both listed the logistics service performance measurement
and support service performance measurement. A 3-point scale is employed to measure and
quantify the survey results. For the investigation on leaving barrier, we listed 5 major indicators:
Customer life cycle
Business coverage (The ratio of logistics work that outsource to YCH to total logistics work
needed)
Performance measures
Price sensitivity
Competitors
Each customer has its own life cycle, from acquisition, retention to declination. Generally, the
average life cycle for a 3PL customer is 5 to 6 years. So it is divided into 3 periods equally, say
first 2 years is on the acquisition stage, next 2 years is on the retention stage and the last 2 years is
on the declination stage. A special case is that if a customer has spent more than 5 years in one
3PL company, then it most possibly will stay longer. In summary, the customer with staying less
than 2 years or the customer more than 5 years are supposed to stay within the company longest,
thus get the highest score, 3 points. Customers with 2—3 years, 2 points and customers with 3—5
years, 1 point. The higher the point is, the more likely that the customer will stay longer.
Business coverage is the ratio of the total demand of a customer and his actual purchase from a
supplier. To the 3PL company, the ratio is the total logistics demand of a customer and the actual
logistics service he purchases from a 3PL. It is another indicator of the mutual relationship. The
higher the coverage ratio is, the more reliable the relationship is. Therefore investigation on the
ratio can reflect the relationship. If the coverage ratio is 100%, which means the current
relationship is very healthy and the customer is very unlikely to leave. 3 points are given. The
66% ratio indicates a average relationship status, thus 2 points are given and lastly with ratio of
33% or less are given 1 point.
Whether customers are willing to build the relationship with a supplier depends on the satisfaction
on the service performance. Therefore the measurement of the performance can also indicator the
relationship status. The performance indicator is divided into 9 sub indicators, each of which
represents the performance of one kind of logistics service provided by YCH. The higher points
indicate a better performance. 3 points indicate a “Good” performance; 2 points indicate a
“Average” performance and 1 point indicates a “Poor” performance. The comprehensive
performance indicator depends on the average of the 9 sub indicators.
Price sensitivity is another indicator of the relationship status. If a customer is very price
sensitivity, then the relationship is vulnerable once the price fluctuates. Therefore the relationship
status can be reflected by the current customer attitudes. A price sensitive customer always thinks
the price is too high. Once he finds a lower price somewhere, the customer will leave soon. The
relationship indicator is given 1 point if so. Unlike those price sensitive customers, some pay more
attention to the ratio of price and quality. They are the groups who are willing to pay more for
better quality in reasonable ranges. The attitude—the price is worthwhile reflects a potential
longer relationship, thus should be given 3 points. The attitude—the price is acceptable reflects a
middle situation, thus should be given 2 points.
Finally, we consider the competition indicator. Sometimes the reason for customer loss is not
because your performance is bad but because your competitors’ performance is better. Thus
whether the relationship status is good also depends on what kind of competition is faced.
Basically, the more vendors a customer has for a type of service, the more intensive the
competition will be because the customer can easily compare the price and quality between
vendors and ask for a price discount. So if a customer only has one 3PL, the competition is
supposed to be easy and the relationship thus is most stable. The indicator is given 3 points. If a
customer has three or more 3PL vendors, the competition is most tough and the relationship is
most vulnerable. The indicator is given 1 point. If a customer has two vendors, the competition is
middle and the indicator is given 2 points.
The comprehensive barrier for each customer can be obtained by summing to points of five
indicators. A higher barrier points indicate a lower possibility of customer loss. If customer A gets
higher marks than customer B does, then customer A is less likely to leave than customer B does.
The 5 indicators represent the top five factors that affect customers’ retention. The higher marks a
customer gets, the more satisfied a customer is with the five factors. Therefore we can measure
customers’ retention risk by looking at the total marks customers get for the 5 indicators.
20 questionnaires were sent to customers by e-mail on Aug 20. The first batch of 2 came back on
Aug 30. The second batch of 8 came back on Sep 15 and the last batch of 5 came back on Sep 22.
Totally 15 out of 20 questionnaires were returned. The return rate is 75%. 15 customers equably
spread among three business categories, which are chemicals, electronics and Fast-moving
consuming goods (FMCG). We name the first customer from chemical group C1, the second
customer from chemical group C2 and so on. We name the first customer from electronics group
E1, the second E2 and so on. We name the first customer from FMCG F1, the second F2 and so
on.
4.3 Complaints response time cycle
We have mentioned that overall satisfaction depends on two issues. One is satisfaction on support
service performance. Customer complaint handling plays a major part in support service in
logistics industry. Therefore, this section conducts a data analysis on the complaint handling
system. One of the major measurements of complaints handling is average response time. The
survey results showed that telephone and e-mail are two key channels for complaints before
implementing CRM. The average response cycle time is about 30 days. The long response time of
traditional way mostly attributes to the stunt of the information transmission. The agents need to
handle so many complaints per day and sometimes they may make mistakes. Even they can record
all the complaints accurately, the information still get lost sometimes when the agents transfer
information to the operation staffs. There is only one cause for the delay—no one is monitoring
and coordinating the process. This is the purpose of of the new complaint handling system features.
The auto escalation function can monitor and coordinate all complaints handling automatically. If
the first level users fail to give response within 1 workday after acknowledging customer
complaints, the system will automatically escalate the problem to the sector header, who is the
immediate boss of the first level user. The reason for setting escalating time is 1 working day is
that the sector heads still have 1 working day to process the complaints within 3 days after
receiving complaints. If the sector headers fail to acknowledge the solutions within 3 working
days after receiving complaints, the system will then make the level-2 escalation to the department
header, who is the boss of the sector heads. If the department headers still fail to acknowledge the
solution within 5 working days after receiving complaints, then the system will make the level-3
escalation, also the final escalation, to the company boss. Because of the pyramid-like
organization structure, such a escalation can not only make the best use of the all human resource
but also respect customer complaints in the most extent. To investigate the response efficiency of
the new system, we should figure out how many percentages of complaints are dealt with before
the first level escalation, how many percentages before the second level escalation and the third
level escalation. Figure 4-1 shows the statistics of the escalation for complaints. Due to the
accessibility of the data, we just count the complaints from customer C2, C3 and C4. The total
number of the complaints from the three customers is 70. The number of complaints from C2, C3
and C4 that have experienced the first level of escalation is 13,15,7 respectively. The total number
is 35, which means the other 35 complaints from customer have been responded within 1 working
day after receiving complaints. The number of complaints from C2, C3 and C4 that have
experienced the second level of escalation is 6, 8, and 8 respectively. The total number is 22,
35
Number of complaints 30
25
20
C4
15 C3
C2
10
5
0
Level 1 Level 2 Level 3
escalation escalation escalation
Escalation level
Figure 4-1 Auto escalation statistics
which means 48 complaints have been responded within 3 working days after receiving
complaints. The number of complaints that have experienced the third level of escalation is 13 (C2,
5, C3, 3, C4, 5), which means 57 complaints have been responded within 5 working days after
receiving complaints. Figure 4-2 shows the percentage of the complaints that is responded within
1, 3 and 5 working days. 49% of the complaints have been responded within 1 working day after
receiving complaints. 19% of the complaints have been responded within 3 working days after
receiving complaints and another 19% within 5 working days. The rest 13% of the complaints are
handled during the month meeting with customers. If we ignore the 13% of the complaints that are
handled during the meeting, the average response time for the 87% of the complaints is
(1 49% 3 19% 5 19%) 87% 2.31 (day)
19%
13%
within 1 wk day
within 3 wk days
within 5 wk days
other
49%
19%
Figure 4-2 Statistics of the response time
4.4 Customer satisfaction level comparison
As we mentioned in section 3.4, customer satisfaction level in 3PL industry consists of logistics
service quality and support service quality. Customer complaints play a major role in support
service. So the response time of complaints handling decides the quality of support service. In
section 4.3, we have compared the average response time before and after CRM implementation,
which has been proven to be a great improvement. In this section, we want to compare the
satisfaction on logistics service quality between customers who have been installed CRM and
others who haven’t. Customer C1 and C3 have implemented the system for 1 year. Customer C2
and C4 have used the system for half a year. The rest customers haven’t implemented CRM yet.
Figure 4-3 shows the comparison of the performance satisfaction between C1, C2, C3, C4 and
other customers who haven’t implemented yet. The satisfaction level of the four customers who
have implemented complaint automation system is much higher than that of the rest customers
who have not implemented the system. Customer C1 has the highest satisfaction level, which is
70% higher than that of the rest customers. The satisfaction level of customer C2, C3 and C4 is
46% higher than that of the rest customers.
2.5
2
Satisfaction level
1.5
1
0.5
0
C1 C2 C3 C4 The rest
Customer
Figure 4-3 Customer satisfaction level comparison
Besides overall satisfaction on logistics service performance, we want to know the satisfaction
difference in each of the area of logistics service between customers who have implemented CRM
and others who haven’t. The logistics service provided by YCH consists of 5 major parts, which
are:
Warehouse and distribution management: how efficient the warehouse operation is; what
is the order fulfillment rate.
Inventory management: how accurate the inventory forecast is; what is the average pipeline
inventory; how about the stock out rate
Freight Forwarding: the average processing time of custom brokerage; the total cycle time
Reverse Logistics: the accuracy of damage part identification; operation cycle time
IT consultancy: the efficiency and convenience of the information service, including order
track, online procurement and new sales enquiry etc.
Figure 4-4 shows the comparison of satisfaction on 5 type logistics services between customers
with and without CRM implementation. Customers with CRM implementation showed an average
52.3% higher satisfaction level in all types of services than those customers without CRM.
Complaints analysis. Largest satisfaction difference occurs in reverse logistics. Customers with
CRM implementation showed 81.8% higher in satisfaction level than those customers without
CRM implementation. Smallest satisfaction difference occurs in freight forwarding. Customers
IT consultancy
Service category
Reverse Logistics
Customers without CRM
Freight forwarding Customers with CRM
Inventory management
Warehouse and
distribution
management
0 0.5 1 1.5 2 2.5 3
Scoreboard
Figure 4-4 Satisfaction level comparison
with CRM implementation showed only 28.6% higher in satisfaction level than those customers
without CRM implementation. Based on the data analysis, we can conclude that CRM
implementation may increase satisfaction level.
4.5 Complaints analysis
In section 4.3, we have proven that new complaint handling automation system can shorten
response time significantly. In section 4.4, we have concluded from the survey data that customers
with new complaint handling system are more satisfied with logistics service as well. As we
mentioned in section 3.4, complaints reflect customer measurements of service quality. By
analyzing complaints, companies can better target on the service problems and make an
improvement. That may be the reason why customers with new complaint handling system are
more satisfied with service performance as well. In this section, we try to do some analysis on the
complaints collected from new complaint handling system in YCH to see how complaints can help
YCH target on the problems and make according improvements.
By counting the number of complaints received in each sector in operation, the company can then
figure out the performance of each sector. Figure 4-5 shows the histogram of received complaints
Number of customer complaint 120
100
80
Closed
60
Acknowledge
40
Outstanding
20
0
Transport Freight Information Warehouse
Technology
Support department
Figure 4-5 Complaints analysis
so far in each support sector. There are three statuses of the complaints. When a customer keys in
the complaints and the system confirms to receive the complaints, the status of the complaint is
“outstanding”. When the staffs investigate the problem and give solutions, the status of complaints
is “acknowledge”. When the customer is satisfied with the solution provided, he can then make
the complaint status to “closed”. Among all the support sectors, warehouse and freight have
received the most complaints. From 2001, 10 to so far, totally 183 complaints are received.
Warehouse sector has received 100 out of them, which is 54.6% of the total complaints. Freight
sector has received 64, which is 35% of the total complaints. Together they stand for around 90%
of the total customer complaints. It is necessary to deeply investigate on why there have been so
many complaints in warehouse and freight sector. All the complaints of warehouse sector can be
concluded into 5 categories. The complaints from each category are caused by one similar
problem. The 5 major causes are: wrong label, later or wrong delivery, damaged cargo, input error
and system error respectively. Figure 4-6 shows the percentage of the complaints that are
attributed to each cause. “Late or wrong delivery” is the most frequent cause, which is responsible
for 45% of the complaints. Both “wrong label” and “Damaged cargo” are the second frequent
causes that each is responsible for 18% of the complaints.
7% 18%
12%
Wrong label
Late or wrong delivery
Damaged cargo
18%
Input error
45% System error
Figure 4-6 Cause of the complaints in warehouse sector
“Input error” and “system error” are two less frequent causes, responsible for 12% and 7% of the
complaints respectively. Similarly, 5 major causes, wrong calculation, wrong or missed process,
input error, delayed shipping and document error, are responsible for the complaints in freight
sector. Figure 4-7 shows the percentage of the complaints that are attributed to each of the cause.
“ Document error” appears as the most frequent cause, which is responsible for 56% of the
Wrong calculation
10%
7% Wrong or missed
7% process
Input error
56% Delayed shipping
20%
Document error
Figure 4-7 Cause of the complaints in freight sector
complaints in freight sector. “Delayed shipping” which is responsible for 20% of the complaints,
is the second most frequent appearance in the complaint cause. This is followed by “wrong
calculation”, which is responsible for 10% of the complaints. “Input error” and “wrong or missed
process”, each of which is responsible for 7% of the complaint in freight, are the two least causes
for the complaints in freight. If we consider all the causes in both warehouse and freight sector and
sort them according the percentage of complaints received, we may get a clear picture on the area
where the company should make improvement in the first priority. The formula to figure out the
percentage is as follows: Global percentage=55%(if it is the cause in warehouse sector) or 35%(if
it is the cause in freight sector)* the percentage of the complaints that attributes to this cause.
Table 4-1 lists the global sequence of the causes according to this formula.
Table 4-1 Summary of complaints cause
Late or wrong delivery 24.8%
Document error 19.6%
Wrong label 9.9%
Damaged cargo 9.9%
Input error* 9.1%
Delayed shipping 7.0%
System error 3.9%
Wrong calculation 3.5%
Wrong or missed process 2.5%
* We combine two input error in both warehouse sector and freight sector into one cause.
We can conclude that the company should pay most attention to on-time delivery and verify the
international freight document.
Chapter5 Benefits of CRM—enlightened employees
5.1 Overview
Besides the benefit of increasing customer satisfaction, CRM implementation has achieved
another benefit in YCH, which is to enlighten employees to better understand customer
requirements. No matter how sophisticated the automation system is, the essence of relationship
building is between people. It is a big success if CRM implementation can “teach” employees the
right way to deal with customers. To investigate whether the implementation has enlightened
employees towards more customer-oriented, we conducted an internal survey whose target
respondents are key employees in each department of YCH. By comparing their response towards
the questions raised in the survey before and after CRM implementation, we can conclude that
whether CRM implementation has succeeded in changing employee’s concepts and behaviors.
5.2 Internal survey
The survey is by means of questionnaire. 12 questions are listed in the questionnaire to find out to
what extent the respondents understand their customers. A four-point-scale, “ Yes—4 points,
Partial—3 points, Not sure—2 points, Totally lost—1 point” is employed to measure the
understanding of customers by YCH employees. The questionnaires are distributed among YCH
employees who are involved in the CRM program. The survey is conducted twice, before
implementing CRM program and after implementing CRM program. To keep it comparable, all
respondents should be the same people during two surveys. We chose 10 target respondents who
are the supervisor of the involved sector in YCH. The first batch of 10 questionnaires was
distributed on early July, which was before the date of CRM launching and 10 questionnaires were
returned on Mid August. The return rate is 100%. The second batch of questionnaires was
distributed on Late August, until which CRM had been launched for 1 month. 9 out of the 10
questionnaires were returned. Because one employee was not in the company any more, 9 out of
the 10 questionnaires were matched in two rounds surveys. The return rate for the questionnaires
is 90%. YCH has claimed that no similar CRM program was launching during these time, which
prevents the possibility of affecting respondents’ choice by other program.
5.3 Data analysis and discussion
Except for the last question, which is “Are you ready to implement CRM with your department”,
all the rest questions can be divided into two categories. The first category is about “know what”,
which includes “ know top 5 customers”, “know customers’ needs”, “know the gap between
customer expectations and what they are getting”, “ know the process that contribute to the gap”
and “review and identify the pitfall”. The other category is about “do what”, which includes
“provide customer support to customers”, “measure service quality”, “receive customer feedback”,
“develop improvement according to feedback”, “share customer feedback across departments”
and “receive preventive initiation from the department”. The 4-point score stands for a most
positive response while the 1-point score stands for a most negative response. The 2-point score
and the 3-point score are in between. The score gained from the 12 questions represents the status
of the respondent’s attitude towards his customers. The higher the score a respondent get, the more
positive his attitude towards his customers. Figure 5-1 shows a comparison between the average
score of the respondent samples before CRM implementation and the one after CRM
implementation. As we can see in the figure, the average score of the respondents before CRM
implementation is 37.22 (the full mark is 48)
After CRM
43.00
survey time
Before CRM
37.22
34.00 35.00 36.00 37.00 38.00 39.00 40.00 41.00 42.00 43.00
score scale
YCH employees' score
Figure 5-1 Internal survey scoreboard I
while the average score after CRM implementation is 43. The average score has increased by
15.53%. From the statistics result, we can conclude that CRM implementation do have an effect
on the employees’ attitudes towards customers. Besides the impression of the general picture, we
want to investigate whether CRM implementation has a greater effect on understandings or on
actions. Figure 5-2 shows the comparison. Employees’ response on “ know what” type questions
can represent the understanding of CRM while the response on “do what” type questions can
reveal their real action towards CRM.
3.70
3.60
3.50
score scale
3.40
3.30 Before CRM
3.20
After CRM
3.10
3.00
2.90 After CRM
2.80
Before CRM time
Know What
Do What
questions types
Figure 5-2 Internal survey scoreboard II
Before implementing CRM, the average score on “know what” type of questions is 3.13 and the
average score on “ do what” type of questions is 3.2, with only 2.25% gap. After implementing
CRM, the average score on “know what” type of questions is 3.49 and the average score of “do
what” type of questions is 3.63, with 4.03% gap this time. It implies that CRM implementation
may affect the actions a little more than the understandings. The explanation for this may be that
some employees actually are doing something positive to their customers but they do not aware
why they should do so and the potential benefits for doing so. Now we narrow down the scope to
each of the two question categories to make a further investigation on the collected data. Figure
5-3 shows a histogram of each question’s score before CRM implementation. We can find from
the figure that question No. 4 received the lowest scores, which is 2.67. No.4 is the question “Do
you know the gap between customers’ expectations and what they are getting?” It indicates that
most employees either do not understand customers’ expectations or are not clear about what they
are actually delivering.
Highest Score
Lowest Score
After CRM
After CRM
4.50
4.00
3.50
3.00
Score scale
2.50 Average score before CRM
2.00 Average score after CRM
1.50
1.00
0.50
0.00
1 2 3 4 5 6 7 8 9 10 11 12
Question No.
Lowest Score
Highest Score
Before CRM
Before CRM
Figure 5-3 Comparison of employee response before and after CRM implementation
On the other hand, we find that question No.1 got the highest score, which is 3.67. The question is
“ Do you know who are your top 5 customers”. Such a response reflects that most employees
already have a concept of customer value and priority. After beginning CRM implementation,
Question No.5, which is “Do you know what are the processes that contribute to the gap”,
received the lowest score (3.11). It seems that after CRM implementation, most employees have
realized the gap existing between customer expectations and the actual service quality but still
they have no idea about how to fill in the gap. This is the main task of further CRM
implementation. Question No.1 is still the one that received the highest score after CRM
implementation, which is 3.89. The result almost reaches the full mark, which are 4. It shows that
almost all employees can identify their top 5 customers after several months of CRM
implementation. We also notice that the score received by question No 11, which is “Do you
receive preventive in initiation from the department” has increased by 24% after CRM
implementation. The increase rate is the highest among all the questions. Most respondents
revealed that the new implemented complaint handling system can provide them most preventive
suggestions. On the other hand, only 3.11% has increased in the scores received by question No. 6,
which is “Are your operation or service being measured”. This is also the lowest increase among
all the questions. But since the score itself for the question is 3.67, which is already high, the space
for the improvement has been limited. Therefore we cannot regard CRM implementation has least
effect on the quality measurement.
Based on the data analysis, we can conclude that CRM implementation can enlighten employees
to better understand customer requirements. The impact is more obvious on employees’ behavior
than on their concept. Further implementation is necessary for changing their CRM concept.
Chapter6 Customer segmentation
6.1 Overview
CRM is expensive therefore not all customers are worth implementing CRM. Before
implementing any system, companies should determine customer values. The investment in CRM
implementation is then justified by the determined value. There are a lot of criteria to determine
customer value, such as profits, revenues, volume, etc. Different companies may find out their
own suitable criteria to determine customer value. This chapter introduced a profits-based rule to
determine customer value. But unfortunately, the model cannot be applied in YCH case because of
lack of some data. Alternatively, we propose a revenue-based criterion to determine customer
value in YCH. Besides value, customers are differed in relationship status as well. We use leaving
barrier to measure the relationship status. A higher leaving barrier usually means a better
relationship status. The leaving barrier is determined by five indicators, which are life cycle,
relationship depth, satisfaction, price sensitivity and competitions. By conducting an external
survey among 15 key customers of YCH, we collected their response in those 5 indicators and
quantified the results. Then, we segment all customers in YCH in terms of two dimensions. One is
the value dimension and the other one is the leaving barrier dimension. With different
combinations of two dimensions, we create a nine-cell strategy model in order to segment
customers and decide their priority to allocate company resource.
6.2 Heuristic customer profitability model
This model was first brought forward by Charles Wilson in his book “Profitable customer” 1996.
The criterion used in the model to determine customer value was profitability. Unlike other
models, it introduced an idea of lifetime profitability instead of annual profitability. It argued that
companies should compare customer values in terms of the profits created by customers during
their whole life cycle. Therefore, if customer A generates 30% higher annual profits than customer
B does, but the life time of customer A is half of that of customer B, then the model considers that
the value of customer B is higher than that of customer A. The model is described as follows:
Variable parameters:
S—recent annual sales
r—anticipated sales increase/decrease rate of the industry
e—expected relationship length from now
OC—operation cost
IC—interface cost (including sales & marketing, customer service and administrating cost)
CP—customer profitability in its lifetime
CP S (1 r ) e (OC IC ) e
This model can be used in 3PL industry to figure out the profitability of customers. Instead of
some stationary model, this model employs a dynamic concept, which considers the profit of a life
long concept. In addition, the exponential index e rather than simple multiple e takes the industry
trend into account as well.
6.3 Customer value segmentation in YCH
Besides profitability, other parameters can also measure customer value, such as revenue, cost and
volume etc. The reason for choosing profitability as the primary measurement is because it can
reflect both revenue and cost thus give a comprehensive picture of customer value. Unfortunately,
for some confidential issues, the profit data from the YCH is not accessible. Therefore, the
Customer Profitability model does not work due to lack of some cost parameters. But still we can
estimate the customer value approximately by comparing the revenues instead. By comparing both
revenue and volume, we can thus rank all the customers and regard it as the value rank also.
Basically, the sample 3PL YCH has three business categories, which are electronics, chemicals
and fast-moving consuming goods (FMCG). The annual revenue for each business category is
shown in figure 6-1. As we can see in the figure, electronic contributed highest revenue, tightly
followed by chemical. FMCG was the least revenue generators. Such a revenue structure is
reasonable because the value of both electronic and chemical products per square feet is much
higher than that of FMCG products. Therefore electronics and chemical customers generated more
revenues than FMCG customers did. Although electronic currently generated a little more revenue
than chemical did, chemical customers seem to be more important to the company. The reasons
are as follows:
1. The chemical industry is more stable than electronic industry. Electronics industry is usually
30
25
Annual revenue
20
S$ mil
15
10
5
0
Electronic Chemical FMCG
Business category
Figure 6-1 Total revenues for three business categories
affected by its life cycle, which causes large variable in revenues between peak period and
recession period. Such a large variance affects not only YCH’s revenue directly but also
volumes as well. Sometimes YCH has to make a sudden adjustment according to the variance.
During the recession period, some electronics manufacturers are forced to cut cost in order to
survive. Then they ask a lower rate for logistics or terminate the contact even. No matter how
satisfied they are to the 3PL partner, they still have to terminate the relationship because of the
business recession. But chemical industry develops in a stable pace. It is rare that a satisfying
chemical customer will terminate the 3PL contract because of the economics factor. Therefore,
the relationship with chemical customers is much easier to maintained.
2. Another recession in electronic industry is expected while chemical industry is expected to
develop continuously. Currently, chemical contributes only a little less than electronic does
but it seems that the revenue from chemical can exceed that of electronic in the near future.
Among all chemical customers, four of them together contributed 80% of the whole group’s
revenue. These four customers, who are C1, C2, C3 and C4, are identified as the most valuable
customers. One electronic customer, named E1, contributes 60% of the total revenue of the
electronics group. So E1 is also regarded as one of the most valuable customers. All other
electronic customers, E2, E3, E4 and E5 and the rest chemical customer C5 are divided into
second valuable customer group and five FMCG customers, named F1, F2, F3, F4 and F5 are set
as the least valuable customer group according to their revenue contribution. Table 6-1
summarized the customer segmentations
Table 6-1 Customer segmentation
Customer Chemical Electronic FMCG
Value Hierarchy C1 C2 C3 C4 C5 E1 E2 E3 E4 E5 F1 F2 F3 F4 F5
First class
Second class
Third class
6.4 Customer leaving barrier
Besides customer value, relationship depth is another factor that should be considered in customer
segmentation. We want to know the possibility for a customer to be retained. Therefore we
introduce the concept--customer-leaving barrier, which is used to measure the possibility for a
customer to leave. The higher the barrier is, the lower possibility the customer is going to leave.
To measure the leaving barrier quantatively, we employed five indicators: customer life cycle,
business coverage, performance satisfaction, price sensitivity and competitors. We conducted a
questionnaire survey among the 15 customers and determined the leaving barrier according to
their response to the survey. Each customer can have a total score by summarizing five indicators’
scores. And the leaving barrier for each customer can be measured by the total score. The higher
the score is, the higher the barrier is. Figure 6-2 shows the average barrier status of all sample
customers in different value hierarchies. The figure reveals that the leaving barrier for the first
class customers is much higher than that of second class and third class customers. Recall the
internal survey result that most Y’s employees can identify their top 5 customers. Therefore it is
reasonable that the employees may take more care of those top 5 customers’ business. Usually the
top 5 customers always belong to the first class valuable customers. The additional care from the
company may make the barrier for the first class customers higher than that of second and third
class customers.
14
12
10
Barrier
8
6
4
2
0
First Class Second Class Third Class
Customer hierarchy
Figure 6-2 Leaving barrier for three class customers
6.5 Nine-cell strategy model
Since we already have customer value and leaving barrier, we can combine two variables together
to form a matrix, which is used to identify customer priority. The matrix consists of two
dimensions. One is value status and the other one is leaving barrier status. Each dimension of
status can be divided into three levels, high, middle and low. Thus the area is divided into a 9-cell
grid, as shown in figure 6-3. Each customer can be
Customer value
High
Middle
Low
Low Middle High
Leaving barrier
Figure 6-3 Nine-cell strategy model
Located at one of the nine cells according the following rules:
1. First class customers are regarded as high value, second class customers are regarded as
middle value and third class customers are regarded as low value
2. We purposefully set average points for all five indicators as middle level of the barrier. If a
customer’s barrier is higher than the average points by 10%, then we regard the customer has
a high leaving barrier. If lower than the average points by 10%, then we regard the customer
has a low leaving barrier. Otherwise, the customer has a middle level leaving barrier. Figure
6-4 shows the new 9-cell grid with all customers located.
C2
C1
C3
High E1
C4
Customer value
E2 E3 E4
E5 C5
Middle
F1
F4 F5 F2
F3
Low
Low Middle High
Leaving barrier
Figure 6-4 Updated nine-cell with customer allocated
Figure 6-4 shows a picture of customer segmentation based on customer value and leaving barrier.
The segmentation itself is meaningless until we set different strategy to different segmentation.
Figure 6-5 is the strategy option for the nine-cell grid model. The number in each cell represents
the priority of resource allocation for each status of customers. CRM is very expensive since it
needs a lot of investment in manpower, capital, time and effort. Such a priority illustration gives a
general rule of how to allocate the limited company resource to all customers. For example,
customers with high value and high leaving barrier are given the first priority of resource
allocation. Customers with high value but middle leaving barrier are given the second priority of
resource allocation. And so on. The rule behind the priority allocation is like this:
Develop selectively Develop Defend and maintain
High
4 2 1
Customer value
Maintain selectively Maintain Attract
7 5 3
Middle
Withdraw Maintain selectively Attract selectively
9 8 6
Low
Low Middle High
Leaving barrier
Figure 6-5 Nine-cell strategy
The position of each customer is decided by two dimensions. We give different scores for different
positions in two dimensions. For value dimension, the “high” position is given 3 points; the
“middle” dimension is given 2 points and the “low” dimension is given 1 point. For leaving
barrier dimension, the “high” position is given 2.5 points; the “middle” position is given 2 points
and the “low” position is given 1.5 points. To most 3PL companies, it is much more easier to
increase leaving barrier level by satisfying customers than to increase customer value. Therefore
the customer position in value dimension should be considered in a little bit more weight than that
in leaving barrier dimension. The comprehensive customer status can be reflected by the summary
of two dimensions’ scores. The higher the score is, the higher the priority is. For example, the
position of customer A is with high value and middle level leaving barrier. The position of
customer B is with middle level value and high leaving barrier. The score of customer A therefore
is 3+2=5. The score of customer B is 2+2.5=4.5. Customer A has higher priority than customer B.
According to the rule, we decide all priorities for all nine-cells, as shown in figure6-5.
Besides the number that represents the priority of resource allocation, the nine-cell grid model also
includes nine strategy options for each status. (The original nine-cell grid model is cited from
chapter 3, Ken Burnett, “The handbook of key customer relationship management”, Prentice Hall,
2002) The exact meanings for each strategy option is as follows:
Defend and maintain—defend the customer’s contribution, prevent the share wallet
from the competitors. Maintain the leaving barriers by increasing customer’s
satisfaction.
Develop—strengthen the barrier by increasing customer satisfaction and solving their
problems.
Develop selectively—strengthen the barrier that maximizes the input-output-ratio and
give up some low input-output ratio options.
Attract—snatch the customer’s wallet share from the competitors thus increasing the
customer value.
Attract selectively—selectively invest on the customers that have the potential to be
higher value customers.
Maintain—Maintain the current customer value and leaving barrier level but will not
invest more.
Maintain selectively—Maintain either the current value or leaving barrier level
according to maxim input-output rule, sometimes reduce the investment.
Withdraw—Stop investing on the customers until the status change.
Combine the results of figure 6-4 and figure 6-5, each customer has been set a priority of resource
allocation and according strategy. We summary the results as follows:
Customer C1, C2, C3, C4
Priority: 1st
Strategy: defend and maintain
Customer E1
Priority: 2nd
Strategy: develop
Customer E3, E4, C5
Priority: 3rd
Strategy: maintain
Customer F3
Priority: 4th
Strategy: attract selectively
Customer E2, E5
Priority: 5th
Strategy: maintain selectively
Customer F2, F5
Priority: 6th
Strategy: maintain selectively
Customer F1, F4
Priority: 7th
Strategy: withdraw
Chapter7 Recommendation of further implementation
7.1 Overview
Customer complaint handling system is just one part of CRM implementation. It can affect the
relationships with customers in some extent but not that much. Some other components must be
added in so that they can help to strengthen the relationship in the whole business cycle. This
chapter is going to introduce other components of CRM application, which includes sales and
marketing automation and performance measurement automation. In addition, separate
components cannot be regarded as a CRM system unless they are integrated into a system. This
chapter gives a comprehensive picture on how to combine components together and make them
work as a system.
7.2 Sales and marketing automation
Sales department is an important sector in all industries, not exclusively in 3PL industry. The
factor is that when sales suffer, the whole company will suffer. All business relationships start
from sales. The performance of sales in any company is a key factor to affect customer satisfaction.
Besides, the performance of sales is also a major measurement of CRM implementation. Why
companies invest so much in building relationship with customers? It is because they want to
retain these profitable customers and keep them generating more profit for the companies. Given a
good pass, an excellent striker could make a perfect finish and help his team win. Same situation
happens in CRM implementation. Having invested so much in customers, the company expects
that the sales agents could make more business with the satisfied customers.
7.2.1 How CRM can change the traditional sales methods
CRM employs some software tools to automate sales procedures, reducing average sales cycle and
increasing sales efficiency. The software consists of a back database and some front application
tools, such as forecasting, data matching and data-mining. In 3PL industry, quotas and forecasting
are two key issues in sales. The more exact the quota is, the more likely the company can win the
deal. But it is complex to determine the quota for all companies. If the quota is too high, then
customers will definitely accept the competitor’s deal. If the quota is too low, the company may
make less profit even make a loss from the deal. Before providing a quota, company’s sales agents
need to collect a lot of information, both customers’ preference and competition status. So much
information makes sales agents tired and could do nothing else. The software tools act as a
decision-make supporter, helping sales agents to make accurate responses quickly. The database
contains all customer information and can sort out useful information according to agents’
requirements. For example, the agent can easily browse the latest deal of a customer and plot the
trend, whether is up or down. Better understanding customers’ requirements, an agent can hit on
target more accurately. Besides quotas providing, forecasting is another tough issues for traditional
sales. Because constrained by the resource capacity in warehouse or trucking load, the demand is
highly associated with the quotas. In the traditional sales method, each agent only followed up his
own sales progress and didn’t know others’. It is not convenient for the sales manager to
coordinate and form a comprehensive forecasting. With sales automation system, each agent can
clearly get all of the prospecting information, making a good forecasting on total demand. In
addition, CRM can bring another benefits to sales force. Traditionally, the relationship between
customers and the company are controlled by sales agents. The agent may understand his
customer’s preference and have won the customer’s trust. But no documentaries are left in the
company. Someday, when the agent leaves the company, he also takes away the existing
relationship with his customer since no one except him really understands the specific customer.
Therefore, it is highly risky for the company to let sales agent go because he has customer profile
data. Someday the relationship with customers will be won by the competitors together with the
sales agent. CRM can prevent such a risk. It can help companies to build a sophisticated customer
information database. In that case, if the former agent leaves, the successor can take over easily by
reading all the existing data from the database. The relationship is more likely to be retained in the
company.
7.2.2 The concept of cross-selling/up-selling in 3PL industry
Cross-sell refers to selling one product to some sub customer account that belongs to one customer.
In 3PL industry, sub customer accounts can be regarded as worldwide branches of a multi-national
company and the selling product is of course the logistics service. Many 3PL companies
themselves are also multi-national companies, such as Bax Global, Exel, TNT etc. Many MNC
companies prefer to outsource their logistics work to one 3PL companies worldwide unless local
3PL companies can provide a much better job. In addition, the venture movement of those big
companies often implies a good business potential in some places. If the 3PL companies can catch
that information from customers and follow up, they can get more sales opportunities.
Up-sell refers to selling one product to one customer but with higher version. In 3PL industry, it
means providing a more integrating logistics service. YCH, for example, classifies all its logistics
services into three categories: intribution, intrabution and retrogistics. Intribution is an integrating
logistics service to manage the flow of raw materials, information and financial transactions
between a manufacturer and its suppliers. Intrabution seeks to bridge the complexity in goods
distribution up to retailers and end customers. Retrogistics is a reverse logistics operation,
managing the return of salvaging parts from customers to manufacturers. Customers of YCH can
choose any or all of the three integrating services. For those customers who choose one of the
three services, YCH may up-sell the other two to the customers. If a customer uses both
intribution and intrabution services, then he is regarded as a node customer. Otherwise he is a
branch customer.
S1
C1
S2 C2
A
S3 C3
Figure 7-1
Figure 7-1 shows a simplest model of the relationship in a supply chain. Company A has 3
suppliers, named S1, S2 and S3. It also has three customers, named C1, C2 and C3. Now A is
using both intribution and intrabution service. It is the node customer of YCH. Because of the
features of intribution and intrabution, both suppliers and customers of customer A are all YCH’s
customers. But since they only use either intribution or intrabution service, they are only branch
customers. All these branch customers have the potential to be node customers. Since each
supplier may have at least three own suppliers, totally 9 potential new customers will be
introduced into the system. Due to the capacity restriction, YCH cannot prospect all the new
customers at one time. Just as the idea that all customers have different value, all suppliers have
different value too. Therefore we should segment all suppliers in terms of profitability and the
relationship status with customer A. Figure 7-2 shows an expanded supply chain relationship.
Suppose that S3 has been developed to a new node customer and it has three another suppliers,
namely S5, S6, S7. Besides company A, S3 also has another 2 customers, namely B and C. By
developing S3 to a node customer, YCH has prospected another 5 new branch customers; S5, S6,
S7, B and C. Originally, most of customers in YCH are separate individuals without relationships.
Now customers are linked by the supply chain.
S1 C1
C2
S5 S2 A
C3
S6 B
S3
S7 C
Figure 7-2
Such an up-sell solution can create a win-win situation for both YCH and its customers. The
benefits for YCH to do so is as follows:
1. It can bring YCH more node customers. Since node customers are the major revenue
contributor. So more node customers can bring more revenues.
2. It can bring YCH more new branch customers. They are potential node customers in the future
and can generate some revenues.
3. It can increase the involvement of YCH in supply chains. By repeating the up-sell process in a
supply chain, more and more key players of the supply chain will be YCH’s customers. More
involvement for YCH in a supply chain may increase the customers’ shift cost therefore can
retain customers in that supply chain because it is not easy for them to switch all relationship
along the supply chain to another 3PL company. The more important relationship between a
supplier and its customer, the more likely both the supplier and the customer keep loyal to
YCH. Because as a logistics provider, YCH is the key tier of such an important relationship
between the supplier and the customer.
Besides the benefits to YCH, it can also bring benefits to YCH’s customers as well, which is as
follows:
1. It can increase the visibility and reliability of the order fulfillment among the supply chain.
Suppose there is a simplest supply chain, including one supplier, one manufacturer and one
customer. If the supplier and the manufacturer have different 3PL providers, then the logistics
job will be more complex because of the coordination between 3PL companies. Different
systems between 2 3PLs companies may decrease the visibility of the order fulfillment. When
the customers want to know the status of the order, neither of the 2 3PL companies could
exactly answer. In addition, the more parties involved in a supply chain, the more variable it is.
Most variance in a supply chain is due to the error occurred between two individual parties,
such as between different 3PLs or between suppliers and manufacturer, etc. This is key factor
that lengthens the cycle time. So less 3PL companies in a supply chain can increase the
efficiency and reliability of the supply chain.
2. Customers can have discounts from the result of cost reduction from YCH. We still use the
above supply chain as the example to explain the reason. Compare the two cases. Case 1, both the
supplier and the manufacturer have their own 3PLs. The supplier’s 3PL ships all raw materials
from the supplier’s plant to its warehouse. When the manufacturer places an order, first the
supplier’s 3PL ships the order to the warehouse of the 3PL of the manufacturer. Then the
manufacturer’s 3PL ships the materials to the manufacturer. Case 2, the supplier and manufacturer
have the common 3PL. The 3PL ships raw materials from the supplier’s plant to its warehouse.
When the manufacturer places an order, the 3PL do not need to physically move the materials.
Instead, it can just change the ownership of the materials. It can save a lot of transportation and
material handling cost.
7.2.3 Components of sales automation
Data warehouse
Basically, A data warehouse is a huge database, which develops an institutional memory.
Companies have built data warehouses to unleash the business value locked away in their
operational systems. Like a conventional reporting system, a data warehouse contains information,
which ranges from the general background information of a customer to the transaction record
information of a customer. The difference is that a data warehouse extracts information from
existing internal and external sources, then standardizes and consolidated that information, and
finally stores it for easy access and retrieval. In summary, a data warehouse combines the
following:
One or more tools to extract fields from any kind of data structure (flat, hierarchical,
relational, or object; open or proprietary), including external data
The synthesis of the data into a nonvolatile, integrated, subject-oriented database with
a metadata "catalog"
Account Management Module
This module is used to record each customer account’s profile information. It can help sales agents
to quickly be familiar with customers’ backgrounds and requirements. Customers may feel they
are dealing with their old friends who know each other well rather than a stranger who is hard to
communicate. Generally, the module records such kind of information, including:
Customer background information
Contact person preference
Credit status
Contract status
Payment history
Total revenue contribution
Current business development trend
Customer complaints history
Solution
Once a new customer approaches to a sales agent, the customer’s information will be input into
the database. When the customer comes again, the system will know who is the customer and can
reflect all related information to sales agents. Also, the system can sort out information according
to agent’s specific requirements. For example, it can list the top 5 deals history and plot a trend
diagram. Also, it can reveal the total revenue contribution among all customers to see whether the
customer is a key customer.
Opportunity Management Module
It is important to make use of any sales opportunity. By tracking all customers’ information, CRM
seeks to help companies identify each opportunity and make accurate actions as soon as possible.
This is the main function of opportunity management module. The sales opportunities can be
classified into two categories.
Prospecting new contracts
In 3PL industry, sales cycle is usually divided into three steps, which are:
Proposal Negotiation Deal close
It is particularly important to realize contract expiration dates because it is a good
opportunity to prospect new contracts. It is common that customers may take highly
account into the proposal that comes in the first place. Therefore it maybe too late for a
3PL company to submit a proposal when the customer is asking for. The real situation is
that the customer already has some good proposals on desk and just want to compare the
price. But it is quite hard to just compete on price with all competitors. So in most case,
the latter one will lose the game. Sales automation may trigger the new sales campaign
when contract expiring dates are coming, giving enough time to sales agents to prepare
for the incoming campaign.
Up-selling an existing contract
People are motivated to act when there is discrepancy between that person’s perception
of reality and the desired results. That discrepancy may be perceived as a problem or an
opportunity:
Problem perception—a situation where actual performance is below
expectations—provides the highest probability of sales success. It has been said
that fear of loss is a greater motivation than desire for gain and, provided that the
person is aware that there is a problem, the bigger the problem, the more urgently
the solution options will be explored. Some customers may have outsourced part of
their logistics to 3PL companies and keep the rest inside. Then some problems
occur in logistics and damage the total business. If the 3PL companies can identify
the problems which are caused by the internal logistics part and convinced the
customers how big are the problems, then they can provide a solution that
outsource the rest part of logistics also.
Opportunity perception is a situation where actual performance is meeting or,
perhaps, exceeding expectations but the person can see opportunities for improved
performance.
Both problems and opportunities can be a trigger for customers to buy a new service.
Opportunity management module can help to find out the problems and opportunities
according to customer feedbacks.
Marketing Management Module
Marketing is another stage that communicates with customers frequently. It both sends out the
prospecting information and collects customer feedbacks. One of the measurements is marketing
efficiency, which is the ratio of sales revenues divided by marketing costs. Though the revenues
cannot all attribute to marketing effect but to some extent, the effect of marketing may change the
revenues gradually in long-terms. The evaluation of the marketing effect is to check the on-target
hit rates, which is distributing a right advertisement to the right person at right time. Marketing
management module is the one that aims at exploring the requirements of each customer. Using
data-mining tools, this module can recall the history of the customer purchase behavior and
anticipate the customer’s current needs, making a good advertisement on the right people. For
example, a 3PL company has installed a ASRS system in its warehouse recently. Now it is a good
opportunity to let customers know the updated facility and build a good image for further
prospecting. Since the company has many customers and mass marketing is costly and low
efficient. Marketing management module is the exact tool to handle with the situation. By
reviewing the customer database, the system can then sort out some customers who had asked
about the ASRS system. Of course, some fast-goods moving products manufacturers may be the
best candidates. Some high tech companies with highly innovation may also a good target on
marketing. The system may intelligently search the customers’ contact preference and suggest a
most efficient contact way. For example, if some customers like telemarketing while some prefer
to receive e-mail.
7.3 Performance measurement automation
It is hard to win a game without a scoreboard. In 3PL industry, performance measurement from
customers is the scoreboard. The performance measurement is a “free” hint to tell the company
what should be improved and whether the investment on some facility is justified. A typical way
to do performance measurement is to send out a survey form. Table 7-1 shows a typical
performance measurement form in 3PL companies. Traditionally, all customers may receive the
Table 7-1 Sample performance measurement form
Operation Efficiency Scorecard parameters Score given
Cycle Count Inventory Accuracy
Material Handling Careful Inventory Handling
Business Administration Regular Business Reporting
Receiving Efficiency Prompt Processing
Flexibility Flexibility in Operation
Total
same survey form. This may lead to a disadvantage. The survey form cannot be designed in too
detail because different customers may have different services. Only common questions are listed.
But a detail answer may better help a 3PL company understand the real problems. Therefore
scoreboard should be customized. But it is tough for any person to design different scoreboards for
each customer manually since so much information is involved. CRM expects a computer-based
tool to make it complete automatically. The steps are as follows:
Step 1. Design a complete scoreboard with all services and parameters included manually.
Step 2. Key the scoreboard into the system.
Step 3. Let system match the customers with the service they are currently having.
Step 4. Let system match the services with related service parameters
Step 5. Let system match the customers with the according scoreboards.
Step 6. System generates a customized scoreboard for each customer.
Additionally, some improvements may be added into the traditional scoreboard. We want to make
it further customized. A score weight is employed to make the scoreboard more flexible. Even for
the customers who have the same service from a 3PL company, the emphasis on the perceived
quality may be different. Some customers may take highly account into inventory accuracy since
inventory is very expensive to them but some customers concern more about on-time delivery
because the products are highly perishable. So after the above 6 steps to generate a customized
scoreboard, one more step is to be added, which is to decide a weight according to customers’
business features and requirements. Table7-2 shows the updated performance measurement form
with weight attached. A five-scale measurement is used, ranged from 1 to 5. 1 means the
parameter is least important which only stands for 10% of the total score while 5 is the most
important parameter which may stand for 50% of the total score.
Table 7-2 Advanced sample measurement form
Operation Efficiency Scorecard parameters Weight(1--5) Score given
Cycle Count Inventory Accuracy
Material Handling Careful Inventory Handling
Business Administration Regular Business Reporting
Receiving Efficiency Prompt Processing
Flexibility Flexibility in Operation
Total
7.4 How to put things together
In above section, all the components of CRM have been introduced one by one. In this section, it
is going to combine all the components together and illustrate a flow chart of these components
working together as a system. As shown in figure 7-3, the system is divided into three function
New customers
Add into existing customer
Prospecting
Investment
Operations
Sales & Marketing
Cross-selling/up-selling
/ contract renewal
Customer Complaint Solution
Solution
Finance Customers Customer Service
Revenue
Customer Complaint
Customer Feedback
Management
Investment decision Scoreboard Weight
Investment
Information flow
Capital flow
Sales & Marketing Automation
Customer Complaint Automation
Performance Measurement Automation
Figure 7-3 Proposed integrated CRM system flow chart
areas, which are sales & marketing automation, customer complaint automation and performance
measurement automation respectively. All arrows are divided into two types, blue one and yellow
one. The blue arrow represents the information flow, including decision, complaint, solution and
marketing information. The yellow arrow represents the capital flow, including all the
investmentsand revenues. When customers find some problems during the service, he can log on
the system and the Complaint Automation module will be triggered. Customer can key in the
complaint according to the instructions. Then the system will “recognize” the complaint and
distribute the complaint to the support section in operations. The operation staffs may investigate
the problems and take appropriate actions towards the problems. Then system may send back the
solution to the customer. If the customer is satisfied with the solution, then the system will close
the complaint and record both the complaint and solution to the database otherwise the system will
escalate the complaint to the higher level manager of operations to seek for the further solution
and so on until the customer is satisfied with the solution given. The system will generate a
monthly report to reflect the number of complaints received for each section and service. In return,
the highest number of complaints related to a service offered by the section shall be awarded a
higher weight and link to the Performance Measurement Automation. The Performance
Measurement Automation may update the parameter after receiving the parameters from customer
complaint automation and generate a customized measurement form for each customer. Every
month the system will automatically send out the forms and collect customers’ feedback. From the
feedback, the system can investigate customer satisfaction level according to YCH’s criteria.
When the system identified whichever service is below satisfaction level, it will then track from
the Customer Complaint Handling Automation. This linkage allows the staff to take reference
from the complaints and evaluate whether there is a necessity to take further actions to improve
the situation. On the other hand, the Performance Measurement is also linked to the Sales ans
Marketing Automation. It equips the sales personnel an understanding of the satisfactory level of
the customers on various services. This is highly important as it gives an indication what services
should be emphasized and what services should not. By such, the CRM implementation can be
effective and efficient only when these 3 automation components are able to integrate as one.
Chapter8 Conclusion
8.1 Research overviews
Customer Relationship Management is a effective weapon for 3PL companies to build and
develop a good relationship with customers. Under current circumstance, new customers are hard
to acquire to those 3PL companies because of the keen competition. An alternative way to
prospect new customers is to attract the customers from the competitors. As a result, those 3PL
companies have to prevent their customers from being attracted by their competitors. Though
CRM has come into existence for ten more years, the application of CRM in 3PL industry is still a
new topic to study. In this thesis, we first review several literatures on some issues of CRM
implementation, including the definition of CRM, the evolution of CRM, the benefits and perils of
CRM implementation, the way to determine customer value and the relationship between
customer satisfaction, customer retention and profitability. By reviewing these literatures, we
understand the general process of CRM implementation and the important issues in CRM
implementation. Unfortunately, few literatures have been conducted on CRM implementation in
3PL industry. We therefore conduct a comparison between neo-manufacturing industry,
represented by Dell and 3PL industry in order to find out the similarity and difference between
them in terms of CRM implementation. Our idea is that if some similarities do exist in both
industries, then some of the successful implementing experience in manufacturing industry can be
applied in 3PL industry. Two major differences are found during the comparison. First, Dell is a
manufacturer while 3PL companies are one type of service provider. Customers of Dell pay more
attention to actual quality of the products but customers of 3PL companies are more emphasized
on perceived quality. Second, 3PL companies concern more about capacity limitation, which is a
most important criterion in decision-making. But it is not a big problem for manufacturers. Due to
the business character difference, manufacturers prefer sales automation while 3PL companies
take customer complaints handling automation into high account. We conducted two surveys. One
is for YCH employees and the other one is for key customers of YCH. By analyzing the data from
the survey, we find out two major benefits of CRM implementation achieved in YCH. 1. Increase
customer satisfaction 2. Enlighten YCH employees. After that, we mention customer segmentation,
which is to target on right customers. By reviewing a heuristic customer profitability model, we
propose a feasible methodology of determine customer value in YCH. And then we introduce the
concept of leaving barrier, which is to measure the possibility of a customer to leave. Combined
both value and leaving barrier dimension, we propose a nine-cell strategy model, which is to
identify the priority among all customers and set an according strategy to each type of customers.
Finally, we give a proposal on adding sales automation and performance automation modules to
current CRM system in YCH and the integration of these three components.
8.2 Major findings and industrial implications
8.2.1 Major findings
1. By increasing customer retention rate, company profitability can also be increased. This is a
unique feature in service industry, especially in 3PL industry. In YCH case, with the customer
retention rate increase from 90% to 100%, the NAV of profit can increase 5%. (See Chapter 3)
2. New customer complaint handling automation system can shorten the response cycle time in
91% and increase customer satisfaction in 52% (See Chapter 4)
3. Warehouse sector received most complaints (54.6%) from customers, followed by freight
sector (35%). The most frequent cause in warehouse problems is wrong or delayed delivery
(45%). The most frequent cause in freight problem is document error (56%). (See chapter 4)
4. Employees in YCH are enlightened to better understand customer needs. With 11.5% increase
in understanding customer expectations and 13.4% increase in customer requirement
fulfillment, the overall increase in employees’ attitudes towards customers is 15%.
8.2.2 Industry implications
Currently, 3PL companies prospect new customers mostly according to customer individual
profile or even at random. Instead we propose to prospect new customers along a supply chain
intentionally. The idea is that it is much easier to build a long term relationship with several
members in a supply chain as a group than to do so with several separate customers in different
supply chain as individuals. The more involvement of a 3PL company is in a supply chain, the
more bargain power it has to negotiate with customers in the supply chain. Since both suppliers
and customers may have certain relationship with 3PL companies, we propose that those 3PL
companies should take advantage of such a relationship and expand it within a supply chain as
much as possible.
8.3 Research limitations and Further study
Due to the data availability, we cannot investigate more 3PL companies in Singapore in terms of
CRM implementation. Therefore the results and conclusions drawn above may have some bias
and lose universality in some extent. In addition, due to some confidential issues, some data such
as profits cannot be accessed therefore the Customer Profitability Model cannot be used.
Alternatively revenue model is employed to determine customer value. But because of the
similarity of 3PL business characters, the research results still can be used as a reference of CRM
implementation in 3PL industry.
Due to the time limitation, the thesis cannot cover every issue of CRM implementations, which
may be the topic of some further studies:
1. In CRM theory, companies should segment their customers and take more care of those
valuable customers. But this strategy may incur too much depend on small group of customers
while ignore other large part of customers. This may bring a large variance to the 3PL
companies. In addition, the discrimination between customers may bring some negative
effects on those small customers and further damage the company image. It is a good topic to
study how to keep balance between key customers and non-key customers.
2. After we have studied the relationship between retention rate and profitability, we find that the
retention rate should have some relationship with cost as well. It is a logic sense because
companies may invest more to retain a higher retention rate. Due to the time and data
limitation, we cannot figure out the relationship in detail. It is a good topic for further
research.
Reference
1. McNealy, Roderick M., “making customer satisfaction happen: a strategy for delighting
customers”, Chapman & Hall, 1994
2. Niraj, Rakesh, “Customer profitability in a supply chain”, Marketing Science Institute,1999
3. Goodman, Sam R. “Techniques of profitability analysis”, Wiley-interscience 1970
4. Hooley, Graham J. “Quantitative methods in marketing”, International Thomson Business
Press,1999
5. Wilson, Charles. “Profitable customers: how to identify, develop and retain them” kogan page,
1996
6. Horovitz, Jacques, “The seven secrets of service strategy”, Financial Times/ Prentice Hall,
2000
7. Cartwright, Roger, “In charge of customer satisfaction”, Blackwell Publishers, 1997
8. “Customer satisfaction in the service sector”, Asian Productivity Organization, 2000
9. Chakrapani, Chunk, “How to measure service quality & customer satisfaction: the informal
field-guide for tools and techniques”, American Marketing Assoc, 1997
10. Anderson, Krinstin, “Customer relationship management” Mcgraw-Hill, 2002
11. Ryals, Lynette, “Customer relationship management (CRM): building the business cass”,
Financial Times/Prentice Hall, 2000
12. Wong, Pek San, “Customer service benchmarking in third party logistics industry”, NUS,1996
13. Michale W. Lowenstein, “Customer retention: an integrated process for keeping your best
customer”, ASQC Quality Press , c1995.
14. Roger Cartwright, “In charge of customer satisfaction”, Blackwell Publishers , 1997.
15. “Customer satisfaction in service sector”, Asian Productivity Organization, 2000.
16. Chuck Chakrapani, “How to measure service quality & customer satisfaction”, American
Marketing Assoc., 1997.
17. Jacalyn Sherriton & James L. stern, “Corporate culture, team culture”, American Management
Association , 1997.
18. Joanne Smailes & Angela Mcgrane, “Essential business statistics”, Financial Times Prentice
Hall, 2000.
19. Mark Stwart, “Keep the right customers”, McGraw-Hill Companies , c1996.
20. Katherine N. Lemon, Tiffany Barnett White, & Russell S.Winer, “Dynamic Customer
Relationhip Management”, Journal of Marketing, Vol. 66, January, 2002
21. Dr. Edward H. Frazelle, “Third Party Logistics” seminar notes, 2001
22. Tor Wallin Andreassen, Bodil Lindestad, “Customer Loyalty and complex service”,
internation journal of service industry management, Vol 9, #1, 1998
23. Ian Corner & Matthew Hinton, “Customer relationship management system: implementation
risks and relationship dynamics”, Qualitative Market Research, Vol 5, #4, 2002
24. Rizal Ahmad & Francis Buttle, “Customer retention management: a reflection of theory and
practice”, Marketing Intelligence & Planning, Vol. 20, #3, 2002
25. P.B. Beaumont, L.C. Hunter & D. Sinclair, “Customer-supplier relations and diffusion of
employee relations changes”, Employee relations, Vol. 18, #1, 1996
26. Rhian Silvestro, “Dispelling the modern myth”, International Journal of Operations and
Production Management, Vol. 22, #1, 2002
27. Kaj Storbacka, Tore Strandvik & Christian Grönroos, “Managing customer relationships for
profit: the dynamics of relationship quality”, International Journal of Service Industry
Management, Vol.05, #5, 1994
28. Ko de Ruyter, Martin Wetzels & Josée Bloemer, “On the relationship between perceived
quality, service loyalty and switching costs”, International Journal of Service Industry
Management, Vol.9, #5, 1998
29. G.S. Sureshchandar, Chandrasekharan Rajendran & R.N. Anantharaman, “The relationship
between service quality and customer satisfaction: a factor specific approach”, Journal of
Service Marketing, Vol. 16, #4, 2002
30. Tor Wallin Andreassen, “Satisfaction, Loytalty and Reputation as indicators of customer
orientation in the public sector”, International Journal of Public Sector Management, Vol. 7,
#2, 1994
31. Bernd Stauss & Patricia Neuhaus, “The qualitative satisfaction model”, International Journal
of Service Industry Management, Vol.8, #3, 1997
32. Paul H. Zinszer, “Segmenting logistical service offerings using the extended buygrid model”,
International Journal of Physical Distribution and Logistics Management, Vol. 27, #9, #10,
1997
33. Nicholas Alexander, “The evolution of retailer, banker and customer relationships: a
conceptual framework”, International Journal of Retail & Distribution Management Vol. 26
Number 6 1998
34. Dana Yagil, “The relationship of customer satisfaction and service workers' perceived control”,
International Journal of Service Industry Management Volume 13 Number 4 2002
35. Roger Hallowell, “The relationships of customer satisfaction, customer loyalty, and
profitability: an empirical study”, International Journal of Service Industry Management
Volume 7 Number 4 1996
36.
Appendix A
Internal survey questionnaire
Direction:
The survey is conducted by the student of National University of Singapore for the research use.
The purpose of this survey is to measure the impact of CRM implementation on employees’
attitudes change towards customer needs. The respondents for the survey are the supervisors of
every major department in YCH. The data collected from this survey will be kept confidential and
all the respondent name will be omitted in the report. For those multiple choice questions, please
circle the letter of the answer you choose. Only one answer can be chosen in each question.
Questions
1. Do you know who are your top 5 customers?
Yes Partial Not sure Totally lost
2. Do you know what are their needs?
Yes Partial Not sure Totally lost
3. Are they currently receiving from you in term of service quality and customer support, etc?
Yes Partial Not sure Totally lost
4. Do you know the gap between their expectations and what they are getting?
Yes Partial Not sure Totally lost
5. Do you know what are the processes that contribute to the gap?
Yes Partial Not sure Totally lost
6. Are your operation or service being measured?
Yes Partial Not sure Totally lost
7. Do you review and identify the pitfall
Yes Partial Not sure Totally lost
8. Are you receiving feedback from your customer?
Yes Partial Not sure Totally lost
9. Do you develop improvement plans after receiving the feedback?
Yes Partial Not sure Totally lost
10. Do you share the feedback across the department?
Yes Partial Not sure Totally lost
11. Do you receive preventive initiation from the department?
Yes Partial Not sure Totally lost
12. Are you ready to implement CRM within your department?
Yes Partial Not sure Totally lost
******************************************************************************
You may end here.
Thanks for your cooperation!
Appendix B
A Survey on the Customer Relationship Management (CRM)
implementation in YCH
Direction:
The survey is conducted by the student of National University of Singapore for the research use.
The purpose of this survey is to measure the customer satisfaction of YCH’s customer and the
effect of Y-service program. The respondents for the survey are the key customers of YCH. The
data collected from this survey will be keep confidential and all the company’s real name will be
omitted in the report. The survey is divided into two sections, Section A and Section B, respectively.
Section A is about the company profile information. Section B is the question part of the survey.
For those multiple choice questions, please circle the letter of the answer you choose. Only one
answer can be chosen in each question.
Section A
Name_________________________ Company_________________________________________
Title__________________________ Address of the company_____________________________
Tel_____________________Fax____________________E-mail___________________________
Age of the company______________________ Business Category____________________
The approximate number employees__________________
Section B
1. How long have your company outsourced the logistics work to YCH?
a. 5 years
2. Which logistics work of the following is needed to support your core business?
a. Intribution b. Intrabution c. Retrogistics
3. How many logistics work have your company outsourced to YCH?
a. Intribution b. Intrabution c. Retrogistics
4. Please give marks to the logistics service that YCH is providing you. If the following
service is not the one you are using, then just leave it blank.
Warehouse and distribution management
a. Excellent b. Good c. Average d. Poor e. Unbearable
Inventory management
a. Excellent b. Good c. Average d. Poor e. Unbearable
International Freight Forwarding
a. Excellent b. Good c. Average d. Poor e. Unbearable
LTL or TL trucking service
a. Excellent b. Good c. Average d. Poor e. Unbearable
Repair products collection (Reverse logistics)
a. Excellent b. Good c. Average d. Poor e. Unbearable
Insurance brokerage
a. Excellent b. Good c. Average d. Poor e. Unbearable
Bulk-breaking/Re-package
a. Excellent b. Good c. Average d. Poor e. Unbearable
Cross-docking
a. Excellent b. Good c. Average d. Poor e. Unbearable
Consultancy and supply chain design
a. Excellent b. Good c. Average d. Poor e. Unbearable
5. What do you think of the price of the logistics service provided by YCH?
a. Worthwhile for the service provided b. Acceptable
c. Too high to accept
6. How many third party logistics companies are you currently using to outsource your
logistics work?
a. 1 b. 2 c. >=3
7. Before implementing Y-service program, what channel did you use most frequently for
complain?
a. e-mail b. telephone c. monthly meeting
8. Before implementing Y-service program, what is the average response (means a solution
or explain is given by YCH) time?
a. Within 3 days b. Within 7 days c. Within 2 weeks d. Within a month
9. How long have your company implemented Y-service program?
a. 3 months b. half a year c. a year
10. After implementing Y-service program, what is the average response (means a solution
or an explain is given by YCH) time?
a. Within 3 days b. Within 5 days c. Within 7 days
d. Within a month
11. Do you think the solution given by Y-service system is efficient?
a. Most are efficient b. Only a few are efficient c. Not efficient at all
*******************************************************************************
You may end here
Thank you for your cooperations!
Appendix C
Introduction of YCH
YCH were established in 1955 as a small local passenger transportation business under the name
of Yap Chwee Hock Transport and General Contractors ("YCH Transport"). In 1973, YCH
Transport was converted from a sole proprietorship to a private limited enterprise and was
renamed Yap Chwee Hock Transport Pte Ltd, which is today known as YCH Global Logistics Pte
Ltd
In 1977, YCH undertook a strategic decision to redirect our passenger transportation business to
cargo transportation and in the following year, became one of the major cargo transport
contractors for the then Port of Singapore Authority. In the early 1980s, YCH diversified into the
business of warehouse leasing and the provision of freight forwarding services via the acquisitions
of Freight Connections Worldwide Pte Ltd and Regional Forwarding & Warehousing Management
Pte Ltd ("RFWM") in 1982 and 1983 respectively. RFWM was incorporated in Singapore on 6
October 1980 as a private exempt limited company and was renamed YCH Logistics Pte Ltd on
17 March 1989. In 1999, YCH Logistics Pte Ltd was renamed YCH Group Pte Ltd and presently
serves as our holding company.
In the mid-1980s,YCH grew from a warehousing and cargo transportation provider to an
integrated third party logistics company providing services such as warehousing, distribution
inventory management and freight management. In line with the growth of our business, YCH
established a number of distribution centers to manage the warehousing and regional distribution
for MNC clients in 1991. YCH developed and completed our present headquarters, known as
YCH DistriPark, in 1992. The establishment of YCH Malaysia in 1991 marked YCH’s first foray
overseas. In 1993, YCH set up PDC-YCH DistriPark Sdn Bhd, a 51% owned joint venture with
Penang Development Corporation, to operate a distribution hub in Penang. This joint venture in
Penang is fully operated and managed by YCH. In 1993, YCH also opened the Roche Distribution
Center in Singapore to manage the logistics needs of Roche. In 1994, YCH expanded into China
and set up operations in Shanghai to operate a distribution hub by way of a 51% owned joint
venture with Shanghai Wai Gao Qiao Free Trade Zone United Development Co and China Ocean
Shipping Agency Shanghai. This joint venture in Shanghai is fully operated and managed by
YCH.
In 1995, YCH made an investment to build an automated storage and retrieval system warehouse
in Singapore. In 1997, YCH commenced operations in Hong Kong through the establishment of
YCH Hong Kong.
With the growing trend of logistics outsourcing and the increasingly complex requirements of
YCH’s clients, YCH further expanded our services to include the provision of supply chain
management services through a suite of supply chain solutions, namely Intribution™ (raw
materials management to support manufacturing) in 1996, Retrogistics™ (service and returns
management) in 1998 and Intrabution™ (consumer goods distribution) in 2000.
In 1996, YCH were awarded an Innovation Development Award under EDB's Innovation
Development Scheme, for the development of the Intribution™ solution. YCH were appointed by
Compaq Asia to implement our Intribution™ solution to service its Asia-Pacific manufacturing
operations in the same year. Today, YCH have implemented the Intribution™ solution for our
various clients, such as Natsteel Electronics in Singapore and Mexico, Motorola in Singapore and
China, Gateway in Malaysia, MiTac in Taiwan and Solectron in Mexico.
In 1999, YCH Logistics Pte Ltd was renamed YCH Group Pte Ltd and presently serves as its
holding company.
Currently, YCH can provides both an individual logistics service and an integrated supply chain
service, as described as follows:
LOVA™ (Logistics Value-Added) Solutions
Warehouse Management
Inventory Management
International Freight Forwarding (Air & Sea)
Bonded Trucking
Third Party Repair / Materials Recovery Operations
Insurance Brokerage
Bulk-Breaking/Re-Packaging
Cross Docking
Supply Chain Consultancy, Design, Implementation and Operations
Appendix D
Proof of NAV n (n>=1) by mathematic induction
When n=1,
A(1 x)(r (1) c1 (1) c2 ) A(1 x) x(r (2) c1 (2)) A(1 x) x 2 (r c1 (3))
NAV1 = ….
1 i (1 i) 2 (1 i) 3
A(1 x)[r (1) c1 (1) c2 ] A(1 x) x[r (2) c1 (2)] x2
= A(r c1 )(1 x)
1 i (1 i) 2 (1 i) 2 (1 i x)
Assume that when n=k
NAV k =
A(1 x)[r (1) c1 (1) c2 ] A(1 x) x[r (2) c1 (2)] x2
A(r c1 )(1 x)
(1 i) k (1 i) k 1 (1 i) k 1 (1 i x)
Then the revenue and cost for the customers who entered the company in year k+1 is described as
follows:
Year k Year k+1 Year k+2
Revenue A(1 x)r (1) A(1 x) xr (2) A(1 x) x 2 r (3)
Cost A(1 x)[ c1 (1) c2 ] A(1 x) xc1 (2) A(1 x) x 2 c1 (3)
A(1 x)(r (1) c1 (1) c2 ) A(1 x) x(r (2) c1 (2)) A(1 x) x 2 (r c1 (3))
NAVk 1
(1 i) k 1 (1 i) k 2 (1 i) k 3
………..
A(1 x)[r (1) c1 (1) c2 ] A(1 x) x[r (2) c1 (2)] x2
= A(r c1 )(1 x)
(1 i) k 1 (1 i) k 2 (1 i) k 2 (1 i x)
Proof finished.
Appendix E
Data table of retention-NAV model
Formula
NAV NAV n
n 0
1 i i 1 A(1 x)[ r (1) c1 (1) c 2 ] A(1 x) x[r (2) c1 (2)]
A(r c1 ) + {
1 i x i 1 i (1 i ) 2
x2
A(r c1 )(1 x) }
(1 i) 2 (1 i x)
Parameter variables
Constant
variable A r r(1) r(2) c1(1) c1(2) c1 c2 I
value 25 2800000 840000 1960000 756000 1764000 2520000 60000 0.0125
Data table
x 1 0.998 0.996 0.994 0.992
NAV 567000000 565644811.9 564290951.1 562938417.8 561587211.9
x 0.99 0.988 0.986 0.984 0.982
NAV 560237333.3 558888782.2 557541558.5 556195662.2 554851093.3
x 0.98 0.978 0.976 0.974 0.972
NAV 553507851.9 552165937.8 550825351.1 549486091.9 548148160
x 0.97 0.968 0.966 0.964 0.962
NAV 546811555.6 545476278.5 544142328.9 542809706.7 541478411.9
x 0.96 0.958 0.956 0.954 0.952
NAV 540148444.4 538819804.4 537492491.9 536166506.7 534841848.9
x 0.95 0.948 0.946 0.944 0.942
NAV 533518518.5 532196515.6 530875840 529556491.9 528238471.1
x 0.94 0.938 0.936 0.934 0.932
NAV 526921777.8 525606411.9 524292373.3 522979662.2 521668278.5
x 0.93 0.928 0.926 0.924 0.922
NAV 520358222.2 519049493.3 517742091.9 516436017.8 515131271.1
x 0.92 0.918 0.916 0.914 0.912
NAV 513827851.9 512525760 511224995.6 509925558.5 508627448.9
x 0.91 0.9 0.89 0.88 0.87
NAV 507330666.7 500866666.7 494435851.9 488038222.2 481673777.8