Empirical Study CRM succes

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NRG WORKING PAPER SERIES

A STUDY INTO THE FOUNDATIONS OF CRM SUCCESS

Nyenrode Research Group

Ed Peelen, Kees van Montfort Rob Beltman, Arnoud Klerkx March 2006 no. 06-09


NRG WORKING PAPER SERIES

A Study into the Foundations of CRM Success

Ed Peelen Rob Beltman Kees van Montfort Arnoud Klerkx March 2006 NRG Working Paper no. 06-09

NRG The Nyenrode Research Group (NRG) is a research institute consisting of researchers from Nyenrode Business Universiteit and Hogeschool INHOLLAND, within the domain of Management and Business Administration. Straatweg 25, 3621 BG Breukelen P.O. Box 130, 3620 AC Breukelen The Netherlands Tel: +31 (0) 346 - 291 696 Fax: +31 (0) 346 - 291 250 E-mail: nrg@nyenrode.nl NRG working papers can be downloaded at http://www.nyenrode.nl/research/publications


Abstract Customer Relationship Management has attracted the attention of both marketing practitioners and researchers over the last decade. Despite, or maybe due to, the attention drawn to the subject, a clear agreement on what CRM is and especially how CRM should be developed remains lacking. It is now commonly understood that CRM involves technology, drives Marketing, Sales and Customer Services and is often approached as a business strategy to create value for an organization through the creation of profitable long-term customer relationships. Significant progress has been made in identifying and researching the components of CRM individually. The role of CRM applications, customer knowledge, customer satisfaction and a customer-centric strategy have all been subject of research lately. However, to our knowledge, no comprehensive research has been conducted into the role of these CRM components in achieving CRM success across the line. Also we have yet to find research that shows the relationship between each component. The goal of our research is to determine the impact of each component of CRM on each other and on CRM success. We will strive to do so by using qualitative research into successful CRM practitioners to create research propositions. These propositions will in turn be tested in a quantitative analysis of data collected from 250 Dutch companies. Through building a Structural Equation Model (Sem-model), we determine the role and influence of the key components of CRM on each other and on CRM success. Keywords Customer Relationship Management, Customer Centricity, CRM Components, CRM Success Addresses for correspondence Ed Peelen Professor of Direct Marketing Nyenrode Business Universiteit, Breukelen, The Netherlands Phone: +31 346 291249 E-mail: e.peelen@nyenrode.nl Kees van Montfort Professor Quantitative Corporate Research Techniques Nyenrode Business Universiteit, Breukelen, The Netherlands E-mail: k.van.montfort@nyenrode.nl Arnoud Klerkx Associate director Gartner Consulting E-mail: Arnoud.Klerkx@gartner.com Rob Beltman Partner & Senior Consultant ICSB Marketing en Strategie Phone: +31 10 452 86 02 E-mail: rob.beltman@icsb.nl


A Study into the Foundations of CRM Success Introduction Customer Relationship Management is a topic that has attracted the attention of both marketing practitioners and researchers over the last decade. Despite, or maybe due to, the attention drawn to the subject, a clear agreement on what CRM is and how CRM strategy should be developed remains lacking (Payne and Frow, 2005). Although the principal components of CRM are well described and researched, their interrelations and their contribution to CRM success has yet to be researched (Boulding et al., 2005). The goal of our research is to provide this insight. We will strive to do so by using qualitative research into successful CRM practitioners to create research propositions. These propositions will in turn be tested in a quantitative analysis of 250 Dutch companies. Through building a Structural Equation Model (Sem-model), we determine the role and influence of the key components of CRM on each other and on CRM success.

Defining our CRM perspective

Before we position and investigate the components of CRM, we must first develop our perspective on CRM for the purpose of this research. Although there is proof of convergence towards a common CRM definition, Payne and Frow (2005) still discover different approaches to the topic, ranging from narrow, IT-oriented definitions to broad and customer centric definitions. Whereas the first group focuses on the automation of customer touchpoints (such as Marketing, Sales and Service) and contact processes, the latter focuses on the enabling role of technology in building and sustaining customer loyalty and increased customer revenue. Although the role of technology differs, there seems to be a common understanding that CRM aims at the dual creation of firm and customer value (Rogers, 2005; Vargo and Lusch 2004; Payne and Frow, 2005) and suggests a shift in focus from transactionoriented customer acquisition to retaining and building relationships with them. The objective of CRM is to deliver business value through increases in customer lifetime value instead of in profit on a single transaction (Reinartz and Kumar, 2003). CRM may be presented as a phenomenon of the last decade, but many earlier competitive markets already have been structured as a result of voluntary, long-term, binding commitments among the organizations (and individuals) involved. In such arrangements, transactions are planned and administered instead of being conducted on an ad hoc basis (Arndt, 1979). This illustrates that CRM cannot be viewed as a revolutionary new concept. According to Sheth (2005) and Boulding et al. (2005), it is best described as an evolution of marketing from product- or brand-management to customer management. The recent attention drawn to CRM is the result of the prominent role of customer datawarehouses, sales force automation, interactive communication techniques and statistical decision support tools (Verhoef and Langerak, 2002). These CRM technologies should enable greater customer insight, increased customer access, more effective customer interactions, and integration throughout all customer channels and back-office enterprise functions (Gartner, 2000). This makes it tempting to view CRM purely from

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an IT perspective. We know however that a business perspective is more appropriate, for the integration of these CRM solutions requires organizational adaptation in many ways (Payne and Frow, 2005). There must be a clear strategic orientation towards relationships (Jayachandran et al., 2005; Srinivasan and Moorman, 2005). Processes need to change in a way that the organization can recognize individual customers and extract information on who they are and what they want (Jayachandran et al., 2005). The organization should be in a position to improve the value proposition, for instance by customizing the offering to the individual demands. And finally, channels need to be developed that allow for interaction with the relations. The technology stretches the applicability of customer management to markets where it was economically impossible before. It allows the seller to interact at low cost with large numbers of small buyers, to build their customer profile and to respond to their specific requests and desires. In line with the abovementioned business perspective, we define CRM, based upon an analysis of the definitions of Verhoef and Langerak (2002), Ryals and Payne (2001) and Gartner (2003), as an IT-enabled business strategy focused on the development and maintenance of mutually beneficial relationships between the seller and his buyers. The experience with this IT-enabled business strategy has not been positive so far (Kale, 2004; Reinartz, Kraft and Hoyer, 2004). Although academic research on the impact of CRM on customer satisfaction is scarce (Mythas, Krishnan and Fornell, 2005), consulting agencies have done several studies. Gartner concludes, based upon their 3 year prognosis for the CRM market, that through 2004, 45% of CRM initiatives failed to deliver increases in effectiveness of customer interactions. Through 2006, more than 50% of all CRM initiatives will be viewed as failures from an organization’s point of view due to the inability to link channels, a lack of process redesign or a failure to provide real customer benefits. However, by acting organizations learn. According to Boulding et al. (2005), companies now have developed proven CRM practices that enhance firm performance. The ambition to become a customer centric organization affects every aspect of the organization. The principal components of CRM are by now well described. It requires a vision, a strategy and organizational change. To build customer loyalty, customers should be offered a valuable experience. Processes should be organized around the customer lifecycle and customer information must be available at all customer touchpoints. Information technology should support these touchpoints and enable customer centric interactions. It should help the organization to build customer knowledge and to integrate front- and back-office processes. The interrelations between the components however need further investigation. We still need to find out what characterizes companies that are successful in CRM. In this study we will explore and test the interrelations between these CRM components and thereby discover the contribution of each components to one another and to final CRM success. Firstly, in qualitative explorative research we will analyze the development of CRM components within successful organizations. Their successes and lessons learned are used to formulate propositions as to the effects the different components have on each other. Secondly, a survey was held among 250 Dutch companies to test the hypotheses from the qualitative study.

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An analysis of CRM components As stated and illustrated previously, CRM is a very broad concept. We will identify it’s main components, which include information technology, its application throughout the organization in processes and the resulting customer experience, as well as the organization, the strategy and the company vision. In this paragraph, based upon the definition of CRM given and identified CRM practices, we define eight CRM components that comprehend all aspects of CRM.

8. Metrics

1. Vision

2. Strategy

3. Valued Customer Experience

4. Organizational Collaboration

5. CRM Processes 6. CRM Information 7. CRM Technology FIGURE 1 – BUILDING BLOCKS OF CRM, adapted from Gartner

CRM vision Striving for mutually beneficial buyer-seller relations requires a profound synthesis of strategic vision. The organization as a whole needs to articulate or review its vision, related to CRM (Payne and Frow, 2005; Davidson, 2002). The vision reflects a company’s ideal (long-term) future state that it wants to achieve regarding customer relationship management. It focuses on values the organization is committed to and that are translated in appropriate standards of behavior of all employees (Thompson, 1997). We define CRM vision as an organization’s top management commitment to customer centricity as a path to business success. A good example of such a vision is the one adopted by Agrifirm; “Agrifirm’s success is best achieved through helping farmers yield higher returns from their lands”. The vision is not only important in creating a stable environment for CRM. Glazer (1997) also stresses the importance of the CRM vision in aligning information technology and marketing strategy. The CRM vision is crucial to the translation and communication of CRM throughout the organization. It significantly affects the way in which the entire organization accepts and practices CRM (Payne and Frow, 2005). In the model, the CRM vision is the first components since it determines the scope of CRM within the organization and therefore the development of other components.

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CRM strategy The CRM strategy describes the way the organization wants to realize its vision. Without the CRM strategy, the vision will remain without (significant) impact on the other components. The strategy involved in translating a CRM vision to operational results is often referred to as ‘customer centricity’. This means the organization adopts a view of its operations in which the customer is positioned at the heart of its activities. It is attentive to the needs of the customer and its strategy is aimed at making choices that optimize the customer value experience. The strategy ensures that all parts of the organization work together to achieve end results that balance enterprise revenues/profits and customer satisfaction and loyalty. The most important function of the strategy is to map the road from an organization’s starting point to the realization of it’s CRM vision. An excellent example of a CRM strategy is given by KLM’s 10-step approach to CRM, which takes the company from just ‘getting the basics right’ in operational processes to ‘driving cultural change’, while passing through ‘acquisition of customer information’ and ‘responding to customer needs’. CRM and the organization The realization of this business strategy has its implications for the organizational model (Jayachandran et al., 2005). The company has to be built around customer (segment) needs and requires a leading role for customer management, rather than product- or brand-management. Customer management’s success will be evaluated based on intermediate customer results, such as satisfaction and loyalty, but also on the increase in customer profitability. Sales or efficiency are not goals on and by themselves. The customer management function has the responsibility of creating reciprocity in a sense that actions taken by the company are matched by actions from the customers and vice versa. Reciprocity is a key characteristic of CRM (De Wulf et al. 2001). It involves the timely and accurate delivery of goods and services, the creation of empathy towards the customer and the skill to communicate with instead of to customers. A continuous customer-oriented feedback system will help the organization to learn about its customers and to respond to them in a proactive manner. To realize this feedback system, everybody is expected to participate in sharing and interpreting the meaning of data. A customer oriented culture, with its unwritten system of shared values and norms (Payne et al, 1995, Hoekstra et al, 1999), will help employees understand that the customer’s interest always comes first, ahead of those of owners, management or employees (Webster, 1993; Hoekstra et al, 1999). CRM and the customer experience CRM has to result in the delivery of a valued customer experience. Payne and Frow (2005) state that the value creation process should transform the strategy development process into programs that extract and deliver value. Since the scope of the organization is no longer limited to the transaction, but now involves the customer relationship, the entire lifecycle experience of the customer becomes relevant. The product, the services, the communications, the context and the price should match or exceed customer expectations and have a positive impact on loyalty. Effective and efficient communications in face-to-face contacts, by phone, internet or other interactive media will allow the organization to improve its accessibility to customers and its understanding of their needs and wants. The organization will work consciously and in a planned way

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on improving the buyer-seller relation, even if it requires the customization of the offering and the price (Gilmore and Pine II, 1997). A good example of improvements in the customer experience is given by Yorkshire Water, who went from being at the bottom of the UK water industry regulator’s customer service list in 1998 to winning the Gartner EMEA CRM Excellence award in the year 2003. They focused on giving customers complete insight in interactions and work status, providing customers with a single point-of-ownership from first contact to resolution and implementing a closed loop customer survey program. CRM Processes To act as a customer centric organization, processes should be defined to control activities throughout the customer lifecycle. A process can be defined as a logical sequence of activities (Davenport,1993). The components relating to CRM processes therefore comprises the breakdown of the customer value experience into logical sequences of activities. How can the process of complaining be described from the moment the customer expresses his grief? Or which activities form the inquiring, ordering and delivery process? Successful CRM requires the processes to form a closed loop; the end of one sequence of activities signals the beginning of a new one. Secondly, there should be an understanding of the interrelations of these processes during the customer life cycle. What will e.g. be the impact of a complaint process for the continuation of the relation and the response to potential campaigns? CRM Information Information acquisition is key to market success, as was previously established by research into market orientation (Narver and Slater, 1990; Kohli and Jaworski, 1990). This is even more so in CRM, where customer information is the basis of the value creation process (Peppers and Rogers, 1997). Customer knowledge is one of the major assets of the organization. Increased customer knowledge leads to increased cross-sell ratios and a greater ability to forecast demand (Bharadwaj, 2000) and positively impacts customer satisfaction when supported by CRM applications (Mithas, Krishnan and Fornell, 2005). Hogan, Lemon and Rust (2002) argue that customer information can be a key to a sustainable competitive advantage, if acquired, managed and modeled correctly. Here one can see a clear link back to CRM processes. These need to be in place for an organization to effectively identify its customers and prospects and profile them in a way that is relevant to attracting them and to building relations with them. CRM technology For the realization of CRM, organizations rely on information technology. Many CRM applications have been developed that enable service, marketing and sales processes ranging from sales force automation, datawarehouses, campaign management, content management, call management, tele sales, data analysis, etc. The number of integrated solutions is still low. Most organizations still have to work with several vendors and have to integrate their offerings into one, which is supported by their IT architecture. The use of integrated CRM applications to acquire, process and distribute customer knowledge through multiple channels is expected to positively impact an organsiations ability to manage customer encounters (Bitner, Brown and Meuter, 2000) and thereby create customer satisfaction (Mithas, Krishnan and Fornell, 2005)

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CRM Metrics The final components of this conceptual model is concerned with the results of the CRM initiative. It is quite clear that the adoption of a CRM vision will cause an organization to redefine it’s metrics. The shift from value creation on a transactional basis to value creation during the entire buyer-seller relationship implies a focus on softer variables, such as customer satisfaction and customer loyalty, but also employee satisfaction and loyalty (Heskett et al. 1994, Loveman, 1998). These are intermediate metrics that allow the organization to evaluate the degree in which it is capable of delivering value to the customer and retrieve value from the customer. Ambler(2002) found that the most important customer metrics (satisfaction and loyalty) hardly reach the board (36 and 51% of the companies respectively). If they do, it is unclear if they are understood and how much time is spent on them. This is disturbing in a sense that in the end, positive trends in both intermediate variables should lead to better top-line and bottom-line economic performance of the organization. Payne and Frow (2005) argue that traditional performance measurement systems, which are functionally driven, may not be appropriate for cross-functional CRM).

Qualitative research design The conceptual model of CRM components that we described has been used to perform explorative research into the development of CRM within different organizations. To this extent a number of cases originating from the Dutch CRM award and from international Gartner CRM Excellence Awards were used. The goal of this explorative effort is to discover how the CRM components are effectively developed in organizations that have achieved CRM success either across the organization or in a particular field. We are particularly interested in discovering which components typically coincide in cases where CRM success was achieved. We furthermore strive to deduct from this study a set of propositions as to the influence of components on each other. The organizations that won the Dutch CRM award or the Gartner CRM award are considered references in terms of CRM excellence. Both awards use the conceptual model proposed above in the application forms they use to evaluate their candidates, ensuring the comparability of the cases with the data collected through our quantitative research. The use of this common perspective on CRM and common definition of CRM components of course increases our confidence in comparing and contrasting the cases. We follow Yin’s (1994) methodology of using expert judgments to compare the individual case studies. The cases were evaluated by professional juries composed of independent experts. These experts have gained significant insight into each of the award-winning cases through a combination of submitted documentation and in-depth interviews. In the jury reports of the CRM Award winners, the juries have addressed and discussed separate components that were particularly well developed. We rely on their expert judgment in this case analysis.

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About the Gartner CRM Excellence award The selection of candidates is designed around the eight building blocks of CRM Excellence. The criteria used in evaluating CRM Excellence Award candidates includes CRM vision, CRM Strategies, Valued customer experience, Organizational collaboration, Processes, Information, Technology, and Metrics. Finalists are selected based on how well the project demonstrates CRM excellence. The entries are evaluated on: > The ability to demonstrate excellence and innovation in implementation. > Execution and support for using CRM applications and strategies to deliver a dramatically improved customer experience, while powering growth in both revenue and the customer base. Special attention is paid to the business value that the CRM initiative has yielded.

About the Dutch CRM awards The goal of the Dutch CRM award is to positively impact the development of customer centric entrepreneurship in general and CRM in particular. The Dutch CRM award jury uses the eight building blocks of CRM Excellence in a survey that assesses the performance of potential candidates. Retained candidates are asked to share deeper insight in their organization, processes and results and are interviewed by members of the jury. The award or awards are granted to those companies that: > Serve as an example to others that are pursuing a CRM implementation in both profit as well as non-profit organizations. > Have implemented a completely customer-centric method of working or have implemented partial methods in a particularly innovative or promising manner. Special attention is paid to the improvements in the customer experience that the CRM initiative has yielded. The development of each components and the order in which the award winner has built the CRM initiative are suspected to indicate the interrelations and the impact different components have on the final result. Did the award winner start with Information and Technology, or was Vision the starting point of the initiative? Does the Vision help in the creation of a Valued customer experience, or was success achieved otherwise? The jury reports of the award winners were used to develop a series of hypotheses as to the role and impact of the eight components in a complete and successful CRM initiative. The cases that received CRM awards and of which jury reports were analyzed, were; > British Columbia Automobile Association – winner of the North-American Gartner CRM Excellence Award 2002 (Small to Medium Businesses) > Canada Post – winner of the North-American Gartner CRM Excellence Award 2002 > Telecom Italia Mobile – winner of the EMEA Gartner CRM Excellence Award 2002 NRG 06-09 A Study into the Foundations of CRM Success - Beltman, Klerkx, Van Montfort and Peelen - 9 of 27


> > > > > >

Yorkshire Water – winner of the EMEA Gartner CRM Excellence Award 2003 Robeco Direct – winner of the Dutch CRM Award 2003 KLM – winner of the EMEA Gartner CRM Excellence Award 2004 Orange Nederland N.V. – winner of the Dutch CRM Award 2004 Fokker Services – winner of the Dutch CRM Award 2004 Agrifirm – winner of the Dutch CRM Award 2005

The selection of the cases is based upon two criteria. First of all, it was our goal to achieve at least one case study per year of each award. At the time of analysis, the 2005 Gartner CRM Excellence award had not yet been discerned. Secondly, we strived for representation of different geographical areas around the globe and different sector (business-to-business, consumer markets, profit- and not-for-profit). The cases have offered a basis for the formulation of several clear propositions, which we will subsequently test through quantitative analysis. We will develop the propositions through the illustration of the cases in this part. In order to compare the cases, an expression of the jury assessments is included in appendix I. Proposition 1 Successful CRM initiatives require developed ‘CRM Vision‘ and ‘CRM Strategy’. Jury reports of the past 4 years all speak highly of top management’s vision regarding CRM. In the case of the British Columbia Automobile Association, the vison was based upon a commitment to confront a difficult market environment by building strong customer relationships. In BCAA’s vision, this meant catering to the individual needs of customers. To that extent, top management stimulated the translation of vision into strategy by annually refocusing on building, integrating and distributing customer knowledge and redeveloping ideas to improve the customer experience. Also illustrative of this point is Telecom Italia Mobile’s Vision. They aim to “turn every customer contact into a commercial opportunity through building customer satisfaction with services tailored to the customer’s needs”. This vision also includes a clear indication of how Telecom Italia Mobile wishes to achieve it. Throughout the analysis of the various award-winning cases, we found a simultaneous development of vision and strategy and conclude that both components are reflective of top management’s awareness of and commitment to CRM. But top management commitment alone is not enough. Showing strong and lasting support should be complemented by showing direction, inspiring people and supporting initiatives from employees. Although in theory we distinguish between having a vision on customer centricity and adopting a clear strategy towards it, the award-winners do not seem to make that distinction. We note that whilst this relation is clear from the analysis of award-winning cases, less successful CRM initiatives may not share this relationship. Proposition 2 The components ‘CRM Information’, ‘CRM Technology’ and ‘CRM Processes’ are related. One of the CRM key areas are the processes, being enabled by technology and information. Fokker, Canada Post, and Orange started by making one or more clear improvements in the area of Technology, Processes or Information. In most cases, CRM processes were

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specifically put into practice to support the organization’s ability to use customer information (e.g. BCAA, Yorkshire Water, Orange) in interaction with relations and to deliver of customer value. Technology always plays an important role in collecting, storing and disseminating this information and by enabling the processes. Appraisal for the three components was given in very different ways by the juries of the CRM Awards, depending on the specific challenges of the award winners. Some of the winners clearly were challenged to review processes extensively (e.g. Yorkshire Water, Canada Post), whereas others had a technological challenge of integrating multiple legacy systems (e.g. KLM) or build better cusistomer information (e.g. Robeco Direct). The interdependence of the three factors is clear, as absence of CRM processes reduces the ability to capture customer information and process it. Likewise, the lack of CRM information reduces the need for CRM processes and technology to distribute it. We therefore propose that CRM Processes, CRM Technology and CRM Information develop in close collaboration. Proposition 3 The component ‘CRM Strategy’ has a positive impact on ‘CRM Processes’, ‘CRM Technology’ and ‘CRM Information’. The direction in which Processes, Technology and Information are developed is influenced by the strategy. Throughout the analysis of all cases, we find that customer centricity forces organizations to rethink their processes, especially in the area of capturing customer information, processing and analyzing it and defining how it can be put to use. Looking at several of the award winning cases, the strategy clearly includes directions for improving customer knowledge (CRM Information), adopting different processes and developing enabling technology. KLM is a good example of a strategy that sets the direction in which technology, processes and information need to be developed. The jury report states “KLM’s Strategy has transformed existing processes in all customer facing area’s of the business. The aim is to give staff the insight to make every customer interaction an opportunity for delivering better service and improve the traveler’s experience.” Proposition 4 The components ‘CRM Vision’ and ‘CRM Strategy’ have a positive impact on ‘Organizational Collaboration’. A well developed CRM Vision and CRM Strategy helps to transform the organization and to improve cross function/business/division interfaces in order to timely meet individual customer needs and wants. One of the convincing cases for this proposition is Telecom Italia Mobile. A sound vision and strategy stood at the basis of a organizational change program. Organizational collaboration was not achieved through restructuring processes alone, but also by stimulating a more customer centric culture. In some cases organizational collaboration required apart from changes in culture adaptations of the structure. It is not just Telecom Italia Mobile, though. Yorkshire Water, KLM, Orange an BCAA all share this same characteristic. We appear to find support for Payne and Frow’s (2005) findings that the commitment of top management to CRM clearly influences the organization’s adoption of customer centricity. Gartner (2003) also finds top

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management can boost employee buy-in and collaboration among employees, business units and divisions by setting sensible expectations for their CRM program and ensuring enterprise communication about the reasons to undertake CRM. Proposition 5 The components ‘CRM Processes’, ‘CRM Technology’ and ‘CRM Information’ have a positive impact on ‘Organizational Collaboration. Organizational collaboration is not an isolate CRM building block. By definition processes, enabled by technology and information actually facilitate initiatives to collaborate between functions, areas, products and levels. Whether it is the creation of a single customer database, the restructuring of a crucial customer process or the adoption of a state-of-the-art CRM software tool, the jury always praises the increased customer centricity of the organization. Proposition 6 The components ‘CRM Processes’, ‘CRM Technology’ and ‘CRM Information’ have a positive impact on ‘Valued Customer Experience’. Illustrative of this proposition is Yorkshire Water. Their improvement in the Valued Customer Experience, from being last-in-class to significant customer satisfaction, was mainly driven by improvements in processes, information and technology. Their processes were reviewed from the customer’s point of view and were improved by focusing on; - First Call Resolution - Appointment Scheduling - Proactive management of customer expectations - Closed-loop Satisfaction Calls - Field Service Optimization These processes were all supported by a new technology infrastructure which enabled Yorkshire to use customer information to its advantage in creating a better customer experience. BCAA’s jury report also refers to the link between processes, technology and information on one hand and the customer experience on the other. The report states “BCAA developed processes for capturing input about customers’ future insurance and travel needs, as well as customer feedback. BCAA analyzed this customer information internally to improve customer experiences.” Proposition 7 The components ‘Valued customer experience’ and ‘Organizational collaboration’ are related. In 7 out of 8 cases, there is a clear appraisal from the CRM Award jury for both elements. Only in the case of BCAA there is a discrepancy between these two components. This may be explained by the fact that BCAA not only focused on customer centricity, but also clearly stated increased efficiency as a major goal. This may mean that while organizational collaboration was improved, this did not result in a higher quality of response to customer needs (effectiveness), but rather in speedier service at less costs.

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In the other cases the jury sees clear effect of the organization’s efforts to become more customer centric internally in terms of a better value experience for customers externally. These components are already assumed to be interdependent in our conceptual model proposed earlier. Without organizational collaboration, the customers experience cannot be optimal, according to the model. We find support for this proposition in several cases. Proposition 8 The components ‘Valued Customer Experience’ and ‘Organizational Collaboration’ have a positive impact on ‘CRM Metrics’. One of the organizations that showed significant improvement in CRM Metrics was Yorkshire Water. The intermediary measures related to customer satisfaction and company image have seen a significant increase. The better Customer Experience, enabled through Organizational Collaboration has made these increases possible. The Orange case also illustrates this point; “The jury is impressed by both the internal results, in terms of the turnaround of the whole organization, as well as the external results, in terms of the many new customers, increases in customer loyalty and increased customer satisfaction.” Agrifirm is the only case in which improvements in metrics are still hard to find. This might be explained by the fact that this is the most recent of all cases. The jury, however, mentions that these results cannot be far away and refutes Agrifirm’s admission that CRM Metrics are not yet proven. The jury report states that “…customers will disagree; they experience that Agrifirm is a partner who helps optimize their business. Agrifirm is one of the fine examples where CRM is woven into the fabric of the organization and has become natural”. This motivation also hints at the positive impact of the customer experience and organizational collaboration on CRM metrics. Proposition 9 Organizations that started to adopt CRM later are able to learn faster and achieve high scores in CRM Metrics quicker. Because of lessons learned over the years, the award-winners of recent years seem to follow a quicker path to CRM success. They are increasingly able to avoid the pitfalls of CRM implementation and therefore seem to achieve results quicker. The jury mentions failed CRM implementations in several cases, notably KLM and Agrifirm. These organizations were not able to successfully adopt CRM earlier, but now became best-inclass rather quickly. Although we do not expect the 2004 and 2005 initiatives to have developed higher scores on all CRM components, we do see that results are achieved quicker. Proposition 10 Organizations that operate in a monopolistic or oligopolistic market will not achieve the same level of customer centricity throughout the eight components as organizations that are in highly competitive markets. Due to the nature of the marketplace, we suspect that organizations in competitive markets will be forced to become more customer centric and therefore develop their CRM initiative further.

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The Canada Post case, for instance, mentions the emergence of new brick-and-mortar and internet competitors as a reason from increased customer expectations. These expectations could only be met by Canada Post if it became more customer centric. The same holds true for Agrifirm, KLM, BCAA and especially Yorkshire Water. The influence of market trends towards more competitive pressure seems to be a great stimulator. All these best practices started defining their CRM Vision at a time the marketplace was changing for the worst. In most cases cost pressure was rising and new entrants threatened to lure customers away. These cases all illustrate that the CRM vision and organizational change were adopted quicker due to market pressure. Yorkshire water, for instance, had been performing critically poor before the UK government started encouraging competition and the regulator forced it to lower its prices.

Quantitative research design The objective of the empirical research was to test the relationships between the CRM components in organizations that have deployed CRM initiatives. After defining the CRM components and using the CRM Award winning cases to formulate several clear propositions, a questionnaire has been designed to collect data from Dutch organizations who have adopted CRM. The target population of this survey consisted of all Dutch organizations having adopted CRM. Because of the broad definition of CRM and its increasingly wide applicability in business practice, we chose self-selection sampling. The questionnaire for this research was published online and brought to the attention of potential respondents through CRM related websites. Respondents were offered an individual assessment of their CRM performance on each of the components to stimulate response and ensure high quality data by giving the respondent a stake in entering the right data. This yielded a total of 250 respondents between March 2004 and March 2005. The questionnaire has been built up with input from literature and qualitative research according to the conceptual model of the ‘eight building blocks of CRM, as these were described earlier in this paper. In order to analyze the data, background characteristics referring to the respondent’s organization, market and products or services were asked. The questionnaire included the following sections: - Background information of the organization - Market and product characteristics - CRM Vision - CRM Strategy - Organization - Valued Customer Experience - CRM Processes - CRM Information - CRM Technology - CRM Metrics For the purpose of assessment of each of the components, a set of statements was used that the respondent was asked to score on a Likert scale anchored by strongly agree (value 7) and strongly disagree (value 1). In almost all cases the statements were proposed in a way so that 1 was the lowest score on the component and 7 the highest.

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Results: sem-model As our conceptual model dictates, we will consider 8 components of CRM in our analysis. To operationalize these components into an integrated model, we will develop a Structural Equations Model (sem). A structural equations model is a statistical model which combines two techniques: confirmatory factor analysis (the measurement model) and path analysis (the structural model) (Kline, 1998). The confirmatory factor analysis enables us to represent unobserved concepts by creating latent variables. The path analysis is represented by a series of structural (i.e. regression) equations. The expected sem-model, based upon our eight components would be represented as follows:

FIGURE 2 – The proposed structural equations model

The components are expected to each form a latent constructs (latent variable). Based upon our research, we expect: TOPMANAGEMENT:

This latent variable would relate to statements concerning CRM Vision

STRATEGY:

This latent variable would involve CRM Strategy

TECHNOLOGY:

This latent variable would translate to the CRM component Technology

INFORMATION:

This latent variable would indicate the availability and use of Customer Information

PROCESSES:

This latent variable would refer to the development of specific CRM Processes

CLIENT ORIENTED:

This latent variable would indicate the customer centricity of Organizational Collaboration

CUSTOMER MGNT:

This latent variable (customer management) would refer to the component Valued Customer Experience

METRICS:

This latent variable would indicate improvements in CRM metrics that were achieved over the past three years

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The objective of the first step in our analysis is to confirm our model. We therefore will perform a confirmatory factor analysis, which we expect to yield the eight latent variables stated above. The measurement model: confirmatory factor analysis Economists are often interested in exploring theoretical constructs that cannot be observed directly and can only be approximated by observable or measurable variables. These abstract phenomena are termed "latent variables" (Byme, 1998). The creation of latent variables is done with a confirmatory factor analysis, where we have to specify which variables define each factor (i.e. latent variable). The observed variables are also coined "indicators" in the measurement model, since they indicate the latent constructs (Hair et al., 1998). The measurement model for the vector X of observed exogenous variables is described as follows: X = Λ xξ + δ where ξ is the latent endogenous variable, δ is the measurement error in x, and Λ x is a q*n matrix that relates n factors to each of the q observed variables designed to measure them. In confirmatory factor analysis, the purpose is to test whether the hypothesized construct is indeed confirmed by the data. There are several statistical tests that can indicate whether the observed indicators do, indeed, correctly represent the hypothesized latent construct. Other statistical tests aim at measuring the reliability and validity of the indicators as representing a common factor (e.g. Cronbach's alpha, which is recommended to have a value of at least .7 and the variance-extracted measure, that should exceed .5 for a construct). As mentioned earlier, TOPMANAGEMENT, STRATEGY, TECHNOLOGY, CLIENT ORIENTED, CUSTOMER INFORMATION, PROCESSES, MANAGEMENT and METRICS, are latent concepts that cannot be measured directly. With the help of 6, 6, 6, 7, 6, 12, 8 and 5 observed variables respectively, we have created seven latent variables that represent the latent concepts. Each of the eight factor analyses models generates one latent factor, except the factor analyses model corresponding to CLIENT ORIENTED. This factor analyses model generates two latent factors. Therefore we split the corresponding observed variables into two groups. The first group corresponds to the statements that depict the current client orientation of the organization (CLIENT ORIENTED 1), while the other group of variables indicates the intentions and activities to improve upon the client orientation (CLIENT ORIENTED 2). Now we have 9 instead of eight factor analysis model. In our models, the variances extracted by the latent variables is between .55 and .67. Thus, between 55% and 67% of the common variance of the model's observed indicators is explained by their latent constructs. This is a reasonable approximation for the latent concepts, which is recommended to exceed 50% (Hair et al., 1998). As for the reliability measure for each latent variable, all variables appeared to exceed the recommended Cronbach's alpha value of .7. We checked the correlation between the nine latent variables. It turned out, that TOPMANAGEMENT and STRATEGY are extremely strongly correlated. While proposition 1 was aimed directly at this correlation in successful cases of CRM, we now find that the correlation holds true in almost any CRM initiative. Our distinction between NRG 06-09 A Study into the Foundations of CRM Success - Beltman, Klerkx, Van Montfort and Peelen - 16 of 27


top management’s Vision and the Strategy seems merely theoretical. Therefore we joined the factor model of TOPMANAGEMENT and the factor model of STRATEGY. The new factor model with 12 observed variables has only one common latent factor (about 60 percent of the variances of the observed variables is explained by the common factor). It also turned out, that TECHNOLOGY is strongly correlated with INFORMATION and PROCESSES. We may explain this from our qualitative research, where proposition 4 suggests a link between these three components, positioning them on a same level in influencing Organizational Collaboration. It now seems that the correlation between technology on one hand and Information and Processes on the other is due to a supporting or enabling role of technology. To avoid statistical problems with the second part of the model, i.e. the structural part, we skipped the factor analysis model of TECHNOLOGY. We do not include TECHNOLOGY in our model, but retain that it is an enabling factor for INFORMATION and PROCESSES. We accept proposition 4, which suggests a reinforcing relationship between ‘Information’, ’Processes’ and ’Technology’. In the end we had 7 factor analysis models. The structural model After building the latent constructs that represent the aspects of CRM, we will now present the structural model. The structural segment of the sem-model estimates a series of separate, but interdependent, multiple regression equations simultaneously. Figure 3 shows a schematic representation of the overall sem-model (i.e. the structural components). There are 47 observed variables that serve as indicators of the latent constructs. So, the 7 latent constructs were estimated through the observed indicators.

FIGURE 3 – The structural part of the structural equations model Model estimates

The complete sem-model can be estimated by using the statistical software LISREL (see Joreskog and Sorbom, 1996). The fit values of the complete sem-model are satisfactory. The Goodness of Fit Index (GFI) and the Augmented Goodness of Fit Index are 0.8759 and 0.8416, which is near to 0.9. Among others. in the model we have estimated the relationships between the 7 latent variables. Table 2 (Appendix II) presents these estimates of the structural part of the sem-model. The standard deviations of the estimates are given between brackets. In Table 2 the significant relations (on a 5-percent level) are printed in bold. We conclude that TOPMANAGEMENT and STRATEGY influence INFORMATION and

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PROCESSES positively. Next, INFORMATION and PROCESSES are significantly positively related to CLIENT ORIENTED 1, CLIENT ORIENTED 2 and CUSTOMER MANAGEMENT. Finally, CLIENT ORIENTED 1, CLIENT ORIENTED 2 and CLIENT MANAGEMANT have a positive influence on METRICS. From Table 2 it also follows that there is no significant direct relation between TOPMANAGEMENT and STRATEGY on one hand and CLIENT ORIENTED 1, CLIENT ORIENTED 2 and CLIENT MANGEMENT on the other hand. However, these relations are indirect and channeled through INFORMATION and PROCESSES. Consequences for propositions As mentioned above, the confirmatory factor analysis already lead to the acceptation of proposition 1 and 2. Research proposition 3, stated that “The component ‘CRM Strategy’ has a positive impact on ‘CRM Processes’, ‘CRM Technology’ and ‘CRM Information’. Because we find a positive and significant impact of the latent factor ‘Top management and Strategy’ on both ‘Information’ and ‘Processes’, we support this proposition. Due to problems arising from the latent factor of ‘Technology’, we were not able to determine the impact of Strategy on that level. Considering the results of the structural part of our sem-model, we do not find support for the proposition 4, claiming a positive impact of Strategy (now the latent variable ‘Top management & Strategy’) on the Organizational Collaboration (latent variable ‘Customer Management’). This relationship has been found, but is not significant and exists indirectly. Research propositions 5 and 6, concerned with the positive impact of processes and information on the Valued Customer Experience (now latent variables ‘Client Oriented 1’ and ‘Client Oriented 2’) and Organizational Collaboration (now latent variable ‘Customer Management’), are confirmed by the analysis. Because the latent variables related to the Valued Customer Experience and Organizational Collaboration are positioned on the same level in the sem-model, proposition 7 can be accepted. Since the related latent variables all have a positive impact on CRM Metrics, proposition 8 is also accepted. With regard to proposition 9, a new analysis is proposed below. The estimates of the Sem-model with CRM maturity We used the sem- model to test proposition 9, which states that organizations that adopted CRM later will achieve success in METRICS earlier. To this extent we used our MATURITY variable, which is based upon the question when the organization first started to adopt CRM. • Started CRM before 1990 (value=1); • Started CRM between 1990 and 1995 (value=2); • Started CRM between 1995 and 2000 (value=3); • Started CRM after 2000 (value=4).

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We ran the sem-model and evaluated the average scores for the 7 latent constructs within the 4 groups. This is called a multi-sample sem-model with a categorization variable. The categorization variable in our case is MATURITY. Table 3 (Appendix III) shows the difference in scores between the crm maturity groups. Between brackets the t-values have been given for those differences that proved significant. The table only shows the differences between group 1 and group 4, because groups where the categorization variable was 2 or 3 do not significantly deviate from group 1 and group 4. The results show that group 1 organizations (i.e. working with CRM for a long time) score relatively high on the latent variable ‘Top management & Strategy’ and relatively low on ‘CRM Metrics’, compared to group 4 organizations (i.e. working with CRM for a short time). We sought to explain the difference in the scores on CRM Metrics and found that the statements relating to this latent variable are oriented towards progress over the past 3 years. This progress may indeed be expected to be more dramatic for organizations who are relatively new to CRM. We find no support for proposition 9. Testing for market- and product characteristics In order to test proposition 10, which states that organizations in an oligopolistic or monopolistic market will achieve lower scores on CRM components, we ran a new factor analysis on the section of the questionnaire concerning market- and product characteristics. This has led to the construction of a latent factor number eight, that represents the market-product situation. This latent factor has low values for businesses that indicated their market- and product situation is price-dominated. The new latent factor has high values for businesses that indicate they operate in market- and product situations where price is less dominant and the product or relationship between businesses are differentiators. The cluster analysis based on eight latent factors produces the results shown in table 6 (appendix III). The table indicates two groups of businesses are to be distinguished. The first group is related to businesses with a relatively low value for the new latent variable ‘MARKET-PRODUCT SITUATION’. On average, this group has a relatively low score to all latent factors, with the exception of METRICS. The second group has on average a relatively high score to the variable ‘MARKET-PRODUCT SITUATION’. The businesses from this group have a relatively high score on all latent variables. We may conclude that no support has been found that organizations in competitive markets outperform organizations in less competitive (oligopolistic or monopolistic) markets. The opposite seems true, judging from the outcome of this analysis. This may be due to the short-term orientation of organization’s in competitive industries. The competitive nature of the market may introduce a ‘hit-and-run’ or transaction-oriented mentality, hindering CRM development. This may also explain why CRM Metrics are alone in achieving high scores: there is a continuous drive to perform. Organizations in less competitive markets may be more prone to building long-term relationships with their customers as they are less threatened by short-term competitive offers.

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Discussion The components of CRM have been clearly identified and tested in this study into the foundations of CRM Success. We discovered 7 latent constructs that together explain how CRM success is achieved. The sem-model clearly shows a division in 4 levels of CRM components, where the higher level each time has a positive impact on the lower level. There are no significant relationships between a higher level and any other level than that directly below. We therefore state that in order to achieve CRM success, organizations first need to focus on creating a clear vision among top management and translating that vision into strategy. The vision should encompass how customer centricity will help the organization face the challenges in its (future) market place and how CRM can be used to develop lasting interactions with customers from which both parties derive value. The strategy should be a detailed roadmap to take the organization from A to B. Top management and Strategy are the starting points of successful CRM initiatives in our model. The strategic roadmap and the commitment and leadership from top management nurture the organization’s ability to adopt new processes, review old product centric processes and develop a culture where customer information is collected, analyzed and translated into better value propositions to the customer. Our model proved this reinforcing relationship between Top Management & Strategy on one hand and Information and Processes on the other. On the third level of our model, one can see that through better customer information management the organization will be capable of improving internal communication and coordination. Departments share the same view of the customer and better right hand/left hand coordination will be achieved. Improvements in processes, where the focus is now on end results for customers instead of sub optimized processes per internal department, also further the organizational collaboration. The customer notices this in terms of a better customer experience. Products are more tailored to the customer’s needs, the organization is able to put customer information to effective use and optimizes customer contact processes. This leads to increased customer orientation and better customer management. The fourth level is composed of metrics, which represent improvements in both customer satisfaction and loyalty as well as cost reduction and revenue increase. Our model shows a clear positive impact of both client orientation and customer management on the final results, proving that the growth path that has been described is yielding results for the organizations that we researched. We have not been able to include the impact of technology on CRM success in our final model. The results generated when using the latent construct were yielding problems in model analysis. We argue that, since CRM has been defined as an IT enabled business strategy, the factor technology is supporting several components and therefore outweighs all other latent variables in the sem-model. We come back to this in our recommendations for further research. The model shows a clear difference between early starters (adopted CRM before 1990) and late starters (adopted CRM after 2000) on two of the principle components. Whereas ‘Top management & Strategy’ are highly developed in the first group, ‘Metrics’ are scoring higher in the second. The CRM Metrics are explained by the focus in the

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questionnaire, where the statements focus on improvements in CRM Metrics over the past three years. These are likely to be more impressive in relatively new initiatives. The higher score of ‘Top management & strategy’ hints that continued support of both vision and strategy are required. Organizations that have recently adopted CRM might still have some gaps in their CRM Vision and Strategy and not be able to oversee all operational consequences. The model does not offer support for our proposition that the CRM components are developed better in markets where market- and product characteristics suggest that competitive pressure is high. The relationship seems to be opposite and thereby, in our opinion, suggests that the market- and product characteristics do form one of the foundations of CRM success. Organizations in less competitive (monopolistic or oligopolistic) markets are less threatened by short-term price competition. Competitive pressure reduces the likeliness that an organization successfully adopts a clear CRM Vision, develops a CRM Strategy and produces the changes in Processes and Information required to develop Organizational Collaboration and a better Customer Experience. We have adopted increases in CRM Metrics as our measure of CRM Success. In the CRM Award winning cases the results are defined in terms of customer satisfaction, customer loyalty, increased cross-sell ratios, Return on Investment (ROI). Following the case of Agrifirm, one may argue that the Customer Experience is a result in and by itself, just as from BCAA’s case study one might conclude that Organizational Collaboration is an end-result. Since we defined the purpose of CRM as creating mutually beneficial relationships with customers, we find the results yielded in both the Customer Experience and Organizational Collaboration should be objectively measured in CRM Metrics. CRM Success is not achieved, in our opinion, if the results are only external or internal. We conclude by stating that the starting point of CRM initiatives should be the top management level, where vision and strategy must be defined, supported and translated into a desire to take action. Although the efforts on this level only significantly impact the level below (Information and Processes), one can understand that, through the links between each level, the performance in this area influences the final results as if it where the first waterfall in a series. Although there is no direct impact, a greater stream of water upstream will, ceteris paribus, lead to a greater stream of water downstream. This holds true for each consecutive level.

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Conclusion and recommendations for further research Although much research on individual components of CRM has been done over the past years, no comprehensive research has been conducted into the role of these CRM components in achieving CRM success across the line. This study suggests that CRM success is achieved by focusing sequentially on 4 levels of CRM components. Top Management and strategy have a positive impact on CRM Information and CRM Processes. These in turn have a positive impact on the Customer Experience (Client oriented 1 & 2) and Organizational Collaboration (Customer management). This results in improvements in CRM Metrics. This study also suggests that market- and product characteristics are of influence on CRM success. CRM components are better developed in organizations operating in markets that are less competitive by nature and where products are less ‘commoditized’. The sense of pressure seems to reduce performance in all levels of CRM adoption except CRM Metrics. This means that, even though many components are not as welldeveloped as organizations operating in less competitive markets, short term results must be and are generally achieved. We will concentrate further research on the role of CRM Technology as a foundation of CRM success. Our sem-model was not able to include the latent variable at this stage. Since the role of technology is much debated in relation to CRM, we will perform further research to quantify the impact of this component on CRM success as a whole.

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Kohli, Ajay and Bernard Jaworski (1990), “Marketr Orientation: The Construct, Research Propositions, and Managerial Implications”, Journal of Marketing, 5 (April), p. 1-18 Loveman, Gary W. (1998), “Employee Satisfaction, Customer Loyalty, and Financial Performance”, Journal of Service Research, Vol. 1, No. 1, p. 18-31 Mithas, Sunil, M. S. Krishnan and Claes Fornell (2005), “Why do Customer Relationship Management Applications affect Customer Satisfaction?”, Journal of Marketing, 69 (October), p. 201-209 Narver, John C. and Stanley F. Slater (1990), “The Effect of a Market Orientation on Business Profitability”, Journal of Marketing, 20 (Octobre), p. 20-35 Payne, Adrian (ed.) (1995), Advances in Relationship Marketing, Kogan Page, London. Payne, Adrian and Pennie Frow (2005), “A Strategic Framework for Customer Relationship Management”, Journal of Marketing, 69 (October), p. 167-176 Peppers, Don and Martha Rogers (1997), One to One marketing, tools for competing in the interactive age, Doubleday, New York Radcliffe, John (2001), “Eight Building Blocks of CRM: A Framework for Success”, Gartner research note, DF-14-2111, 13-12-2001, Stamford, CT Radcliffe, John and Brian Wood (2003), “Telecom Italia Mobile Cuts Churn and Increases Value”, Gartner CRM Award Case, CS-17-6919, 22-04-2003, Stamford, CT Reinartz, Werner and V. Kumar (2003), “The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration”, Journal of Marketing, 67 (Octobre),p. 77-99 Reinartz, Werner, Manfred Krafft and Wayne D. Hoyer (2004), “The Customer Relationhip Management Process: Its Measurement and Impact on Performance”, Journal of Marketing Research, 41 (August), p. 293 - 305 Riseley, Mark J. (2004), “KLM Demoonstrates the Power of Persuasion to Drive CRM Success”, Gartner CRM Award Case, CAS-1004-0005, 05-10-2004, Stamford, CT Rogers, Martha (2005), “Customer Strategy: Observations from the Trenches”, Journal of Marketing, 69 (October), p. 262-263 Ryals, Lynette (2005), “Making Customer Relationship Management Work: The Measurement and Profitable Managament of Customer Relationships”, Journal of Marketing, 69 (October), p. 252-261 Ryals, Lynette and Adrian Payne (2001). Customer relationship management in financial services: towards information enabled relationship marketing. Journal of Strategic Marketing, 9, p. 3-27 Sarner, Adam (2002), “CRM Excellence Award Winner: BCAA”, Gartner CRM Award Case, CS-18-6777, 5-12-2002 Singh, Deepali and D. Agrawal (2003), “CRM Practices in Indian Industries”, International Journal of Customer Relationship Management, 5 (December-January), 241-257 Srinivasan, Raji and Christine Moorman (2005), “Strategic Firm Commitments and Rewards for Customer Relationship Management in Online Retailing”, Journal of Marketing, 69 (October), p. 193-200 Thomas, Jacqueline S., Werner Reinartz and V. Kumar (2004), “Getting the Most out of All Your Customers”, Harvard Business Review, July-August 2004, p. 117 - 123 Vargo, Stephen L. and Robert Lusch (2004), ‘Evolving to a New Dominant Logic for Marketing’, Journal of Marketing, 68 (January), p. 1-17 Verhoef, Peter (2003), “Understanding the Effects of Customer Relationship Management Efforst on Customer Retention and Customer Share Development”, Journal of Marketing, 67 (October), p. 30-45

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Verhoef, Peter and Fred Langerak (2002), “Eleven Misconceptions about Customer Relationship Management”, Business Strategy Review , 13, p. 70-76 Webster, Frederick E. Jr (1992), “The Changing Role of Marketing in the Corporation”, Journal of Marketing, 56 (October), p. 1-17 Yin, R. K. (1994). Case study research: Design and methods (2nd ed.). Thousand Oaks, CA:Sage.

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Appendix I Case analysis synopsis The cases were analyzed using the conceptual models and the findings are summarized by table 1 below. To transfer the findings to comparable statements, the following assessment criteria have been used: ++ + 0 --

The jury report has elaborately lauded this component The jury report specifically applauds this component The jury report mentions the component without further comments The jury report specifically criticizes this component The jury report has elaborately criticized this component

BCAA

Canada Post

Telecom Italia Mobile

Yorkshire Water

Robeco Direct

KLM

Orange NL

Agrifirm

Vision

+

++

++

++

++

++

+

++

Strategy

++

++

++

+

++

++

++

++

0

+

+

+

0

+

+

++

++

++

++

++

0

++

++

0

Processes

+

0

0

++

+

++

++

+

Information

+

0

+

0

++

+

+

++

Technology

0

++

0

++

0

0

+

0

Metrics

+

+

++

++

++

+

++

0

Valued Customer Experience Organizational Collaboration

TABLE 1 – COMPARISON OF CRM AWARD-WINNING CASES

Appendix II

Coefficient estimates of the sem-model

\ To From \

INFORMATION

PROCESSES

TOPMANAGEMENT STRATEGY INFORMATION

1.1613 (0.1275)

1.1196 (0.1255)

PROCESSES

CLIENT ORIENTED 1 -0.3972 (0.2651)

CLIENT ORIENTED 2 0.1949 (0.1498)

CLIENT MANAGEMENT -0.2133 (0.1783)

0.2518 (0.0885) 0.9827 (0.2081)

0.1291 (0.0561) 0.5074 (0.1183)

0.3192 (0.0696) 0.5346 (0.1339)

METRICS

0.2406 CLIENT ORIENTED 1 (0.1023) 0.2607 CLIENT ORIENTED 2 (0.1528) CUSTOMER 0.1762 MANAGEMENT (0.1035) TABLE 2 - COEFFICENTS ESTIMATES OF THE STRUCTURAL PART OF THE SEM-MODEL

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Appendix III

multi sample sem-model and clustering

Value maturitygroup 1 minus Value maturitygroup 4 Topmanagement/Strategy 0.5243 (t=2.03) Information -0.0496 Processes 0.0155 Client orientated 1 -0.5342 (t=1.90) Client orientated 2 0.0871 Customer management -0.1163 Metrics -0.4741 (t=2.09) TABLE 3 – AVERAGE SCORES FOR LATENT FACTORS IN A MULTIPLE-SAMPLE SEMMODEL (subdivided into four age groups; between brackets are the t-values for significant differences) Cluster 1 (n=12) 0.99

Cluster 2 (n=90) 2.17

Cluster 3 (n=47) 3.26

Cluster 4 (n=67) 4.38

TOPMANAGEMENT/ STRATEGY INFORMATION 1.38 2.94 4.58 6.13 PROCESSES 1.46 3.36 4.55 5.80 CLIENT ORIENTATED 1 1.60 3.67 4.74 5.99 CLIENT ORIENTATED 2 1.14 2.60 3.66 4.76 CUSTOMER 1.39 2.95 3.59 4.41 MANAGEMENT METRICS 1.73 3.46 4.20 5.12 TABLE 4 – AVERAGE SCORES ON SEVEN LATENT FACTORS FOR FOUR CLUSTERS Cluster 1 (n=109) 2.26

Cluster 2 (n=107) 3.80

Difference

TOPMANAGEMENT/ 1.54 STRATEGY INFORMATION 3.15 5.40 2.25 PROCESSES 4.30 4.57 0.27 CLIENT ORIENTATED 1 3.67 5.35 1.68 CLIENT ORIENTATED 2 2.63 4.25 1.62 CUSTOMER 2.90 4.01 1.21 MANAGEMENT METRICS 3.70 4.37 0.67 TABLE 5- AVERAGE SCORES ON SEVEN LATENT FACTORS FOR TWO CLUSTERS Cluster 1 (n=108) 2.19

Cluster 2 (n=108) 3.89

Difference

TOPMANAGEMENT/ 1.70 STRATEGY INFORMATION 3.05 5.41 2.36 PROCESSES 3.37 5.19 1.82 CLIENT ORIENTATED 1 3.66 5.35 1.69 CLIENT ORIENTATED 2 2.62 4.24 1.62 CUSTOMER 2.91 3.98 1.07 MANAGEMENT METRICS 3.89 4.17 0.28 MARKET-PRODUCT 3.54 4.16 0.62 SITUATION TABLE 6 – AVERAGE SCORES TO EIGHT LATENT FACTORS FOR TWO CLUSTERS

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Nyenrode Research Group

Nyenrode Business Universiteit Nyenrode Research Group Straatweg 25 Postbus 130, 3620 AC BREUKELEN T +31 346 291 696 F +31 346 291 250 E nrg@nyenrode.nl www.nyenrode.nl/nrg


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