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Abstract
Purpose – The main purpose of this paper is to review the related literature and propose a new decision-support-system (DSS) framework for
marketing in the business-to-business (B2B) arena based on customer-relationship management (CRM) and knowledge-driven marketing to help
related-field graduate students and marketing managers.
Design/methodology/approach – Reviews a range of the most important works published between 1966 and 2004 in order to demonstrate both
practical and theoretical aspects. The main method of this research is analytical and conceptual and the approach to this subject was to investigate the
gap between marketing DSSs and analytical CRM.
Findings – Provides information about a customized marketing DSS in a B2B context, indicates related literature and frameworks and, finally, tests the
ideas with a case study.
Practical implications – Outcomes and applications are identified for developing new activities in improving marketing decision making and
marketing planning based on customer orientation and customer satisfaction.
Originality/value – Despite such interdependencies, the research in the fields of DSSs and CRM solutions has not adequately considered the
integration of such systems. The novel contribution of this paper lies in integrating marketing DSSs and CRM with regard to knowledge-driven
marketing in B2B marketing, in both theoretical and practical aspects.
Introduction
Intense competition is forcing companies to develop
innovative marketing activities to capture customer needs
and improve customer satisfaction and retention. Businesses
can benefit significantly from analyzing customer data to
determine their preferences and thus improve marketing
decision support (Liu and Shih, 2005; Liang and Lai, 2002).
More and more managers are faced with a rapidly changing
and highly competitive marketing environment. Marketing
managers are forced to become more competitive through
better decision making. A decision can be considered as the
output of a productive activity whose inputs include
intellectual efforts of an individual or a group of individuals,
computing hardware and software, data, etc.
The advances in computer technology and the computerbased
techniques for handling information allow the
development of decision-support systems (DSSs), than can
play a crucial role in the progress of a firm (Alexouda, 2005)
There is an obvious need for tools, which can improve
marketing decision making. Many efforts have been made to
develop suitable software tools, that can act as consultants for
marketing managers. There are many opportunities for
applications of information systems in the marketing area.
The modern information technology and information systems
can assist a company to manage the increasing information
flow and improve its quality. There is a growing interest in the
use of marketing-decision-support systems (MDSSs)
designed to be used in complicated marketing decision
making problems (Talvinen, 1995). An MDSS is defined as
“a coordinated collection of data, models, analytic tools and
computing power by which an organization gathers
information from the environment and turns it into a basis
for action” (Little, 1979).
The concepts of mass production and mass marketing, first
created during the Industrial revolution, are being supplanted
by new ideas in which customer relationships are the central
business issue. Firms today are concerned with increasing
customer value through analysis of the customer lifecycle.
The old model of “design-build-sell” (a product-oriented
view) is being replaced by “sell-build-redesign” (a customeroriented
view). The traditional process of mass marketing is
being challenged by the new approach of one-to-one
marketing.
In the traditional process, the marketing goal is to reach
more customers and expand the customer base. But given the high cost of acquiring new customers, it makes better sense to
conduct business with current customers.
In business-to-business (B2B) environments, a tremendous
amount of information is exchanged on a regular basis. B2B is
one of the most broadly used marketing terms in the
information technology (IT) world. In its simplest definition a
B2B process is any business process between two companies
that uses digital technology. The term can represent functions
that provide information, or facilitate transactions, or execute
transactions or completely integrate shared business processes
into separate, existing enterprise resource planning (ERP)
systems. B2B markets have been considered an attractive ebusiness
venue for the realization of cost reduction and
exchange creation utilities (Hunter et al., 2004).
As any perusal of the appropriate journals indicates, the use
of quantitative methodologies in business-to-customer (B2C)
marketing has been widespread for decades, while B2B
marketing has not embraced these techniques to the same
extent (Nairn et al., 2004). An increase in the B2B market is
potentially of much greater significance than one in the B2C
market (Berthon et al., 2003).
The explosion in internet-based B2B is driven by
economics – the internet offers the potential for reduced
prices for goods and reduced transaction costs, but this is not
simply derived from the internet as a communications
infrastructure (Kuechler et al., 2001). Furthermore, with the
advances in computers, databases, communications and the
internet technologies, modern organizations nowadays collect
massive amounts of data on about everything like, payment
records, financial transactions, loan applications and others.
Analyzing data on this scale and converting it into knowledge
to help decision making, presents exciting new challenges.
Customer-relationship management (CRM) has become
one of the leading business strategies in the new millennium.
It is difficult to find out a totally approved definition of CRM.
We, however, can describe it as “managerial efforts to manage
business interactions with customers by combining business
processes and technologies that seek to understand a
company’s customers”, i.e. structuring and managing the
relationships with customers. CRM covers all the processes
related to customer acquisition, customer cultivation, and
customer retention (Hwang et al., 2004). Data mining is a
new generation of computerized technologies for discovering
knowledge hidden in large amounts of data. Support of
domain expertise to make better decisions and new IT
techniques to promote B2B marketing are essential
(Changchien and Lu, 2001). Data mining techniques are
useful for extracting marketing knowledge and further
supporting marketing decisions (Bose and Mahapatra, 2001;
Shaw et al., 2001).
In this paper, we focus on a very specific DSS on behalf of
market managers who want to develop and implement
efficient B2B marketing programs by fully utilizing a customer
database. This is important because, due to the growing
interest in marketing, many firms devote considerable
resources to identifying households that may be open to
targeted marketing messages. This becomes more critical
through the easy availability of data warehouses combining
demographic, psychographic and behavioral information
(Kim and Street, 2004). In this paper we will focus on
DSSs for the B2B market that are driven by data mining
modeling and analysis. The buying patterns of individual
customers and groups can be identified via analyzing customer data (Wells et al., 1999), but also allows a
company to develop one-to-one marketing strategies that
provide individual marketing decisions for each customer
(Peppers and Rogers, 1997).
The ultimate goal of DSSs is to provide managers with
information that is useful for understanding various
managerial aspects of a problem and to choose a best
solution among many alternatives.
The paper is organized as follows. Section 2 deals with the
presentation of DSS and CRM. Literature review of MDSS
studies are provided in section 3. In section 4 the proposed
MDSS is presented and in section 5 related case study and
implications is discussed. Finally, in section 6, the conclusions
of the paper are summarized