Restructuring the Marketing Information System for eCRM: An Application of the Eriksson-Penker Method

Restructuring the Marketing Information System for eCRM: An Application of the Eriksson-Penker Method

Calin Gurau
Copyright: © 2009 |Pages: 12
DOI: 10.4018/978-1-59904-859-8.ch019
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Abstract

This chapter considers the importance of business modelling for implementing e-CRM systems. The introduction of e-business models requires the adaptation of the Marketing Information System the specific characteristics of the online environment. The representation of various components of the Marketing Information System, and of the flows of information among various organizational departments, represents an essential step for the successful implementation of e-CRM systems. Considering the specific requirements of this restructuring process, chapter presents the advantages of the Eriksson-Penker Business Extensions of the Unifying Modeling Language (UML), and exemplifies their use for modeling the Marketing Information System during the implementation of an interactive e-CRM approach.
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Background

The opportunities provided by the rapidly evolving online markets have determined many firms to initiate e-business operations. However, the success of these initiatives is determined by capacity of enterprises to properly understand the specificity of the Internet, and to restructure their Marketing Information Systems in order to develop a competitive advantage. In this context, the eCRM systems represent interesting solutions for adopting a customer-centric approach and for increasing the online value propositions (Jayachandran, Sharma, Kaufman, & Raman 2005; Payne, & Frow 2005; Srinivasan, & Moorman 2005). Value maximisation happens when firms and customers engage in long-term relationships (Vargo, & Lusch 2004), co-creating personalised value (Prahalad, & Ramaswamy 2004), based on information exchange and close collaboration in all the stages of product R&D, manufacturing and commercialisation.

The eCRM system comprises a number of business processes, inter-linked in a logical succession:

  • Market segmentation: the collection of historical data, complemented with information provided by third parties (such as marketing research agencies), is segmented on the basis of customer life-time value (CLV) criteria, using data mining applications.

  • Capturing the customer: the potential customer is attracted to the web site of the firm through targeted promotional messages, diffused through various communication channels.

  • Customer information retrieval: The information retrieval process can be either implicit or explicit. When implicit, the information retrieval process registers the web behaviour of customers, using specialized software applications, such as ‘cookies’. On the other hand, explicit information can be gathered through direct input of demographic data by the customer (using online registration forms or questionnaires). Often, these two categories of information are connected at database level.

  • Customer Profile definition: the customer information collected is analyzed in relation with the target market segments identified through data mining, and a particular customer profile is defined. The profile can be enriched with additional data, e.g. external information from marketing information providers. This combination creates a holistic view of the customer, its needs, wants, interests and behaviors (Pan, & Lee, 2003).

  • Personalization of firm-customer interaction: the customer profile is used to identify the best customer management campaign (CMC), which is applied to personalize the company-customer online interaction.

  • Resource management: the company-customer transaction require complex resource management operations, which are partially managed automatically, through specialized IT-applications such as Enterprise Resource Planning (ERP) or Supply Chain Management (SCM), and partly through the direct involvement and co-ordination of operational managers.

Key Terms in this Chapter

Enterprise Resource Planning (ERP): A business management system based on specialised software systems that manage various information flows, integrating all business facets, including planning, manufacturing, sales, and marketing.

UML Stereotypes: Extensions to the UML vocabulary, allowing additional text descriptions to be applied to the notation. The stereotype is shown between chevron brackets <<>>.

Supply Chain Management (SCM): A management system that coordinates, integrates and controls the move of materials, information, and finances from supplier to manufacturer to wholesaler to retailer to consumer, in order to reduce inventory and increase the efficiency of the supply process.

UML Constraints: Extensions to the semantics of an UML element. These allow the inclusion of rules that indicate permitted ranges or conditions on an element.

Customer Lifetime Value (CLV): Consists in taking into account the total financial contribution - i.e. revenues minus costs - of a customer over his or her entire life of a business relationship with the company.

UML Tagged Value: Extensions to the properties of an UML element.

Electronic Customer Relationship Management (eCRM): CRM comprises the methods, systems and procedures that facilitate the interaction between the firm and its customers. The development of new technologies, especially the proliferation of self-service channels like the web and wap phones, has changed consumer buying behaviour and forced the companies to manage electronically the relationships with customers. The new CRM systems are using electronic devices and software applications that attempt to personalize and add value to customer-company interactions.

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