Proposed Framework

The theoretical bases for this proposed model are drawn and blended from multiple disciplinary perspectives. Knowledge Discovery in Databases (KDD) and Knowledge Management approaches from MIS and Computer Science, Task-Technology Fit model from Management Information Systems (MIS), and Market Orientation perspectives from Marketing and Business Strategy literatures are adopted and adapted for the purpose of developing this framework.

The Task-Technology Fit (TTF) model from MIS provides a way to explain how CRM systems could lead to increased customer retention and satisfaction. Technologies that fit the tasks lead to salutary performance impacts (Goodhue & Thompson, 1995). MIS methods sometimes imply that technology alone will lead to greater customer satisfaction.

It is not technology in isolation that affects performance - other characteristics also come into play (Goodhue, Klein, & March, 2000). Even though technology is an enabler of CRM practice, it is not easy to satisfy customers without their permissions or without customers' willingness to participate and articulate preferences.

For such preference articulation, permission granting, and co-creating customer participation to occur, organizations have to be sensitive to customers and constantly receive signals from customers. In other words, it is necessary for organizations to be customer centric and market oriented. For, in competitive contexts, customers are likely to migrate away from organizations that ignore customer and market signals, and make a beeline towards organizations that do not ignore such signals.

To invoke the brain-limb-heart analogy again, technological advances have added enormous power to the ' limbs ' in the form of CRM systems, and boosted the IQ of the organizational 'brain' via KDD. The 'heart' of satisfactory service, however, still lies in relationship marketing based on a customer-focused organizational culture. In competitive e-marketing contexts, consumers are wooed by multiple firms - and therefore customer focus has to be leavened with a sharp-eyed competitive focus also. This is why customer focus requires a market orientation: attention to customers and competition.

Elaboration, Illustration, and Rationale

As Figure 12-1 indicates, the proposed model has three dimensions for successful emarketing: Customer Focus (in terms of inculcating a relationship-focused organizational culture with a strong 'Market Orientation'), CRM Technologies ( chosen and deployed so as to enhance 'CRM Fit' within the organization), and KDD Technologies (of the type that improve 'Customer-Knowledge Capability' of the organization).

CRM Fit is a measure of how well the technology employed fits the business goals and tasks of CRM. Its antecedents are the CRM goals and tasks, and the CRM technology itself. The IT aspects of CRM systems are necessary but not sufficient, and also well- developed goals and business processes without help of IT are not enough to achieve the CRM success in dynamic marketplaces . In this framework, CRM Fit is defined as the degree to which CRM systems fit well the tasks of CRM, which are derived from the relationship lifecycle. In some studies, the direct effect of technology on customer retention and customer satisfaction has been found to be not significant (Croteau and Li, 2003; IDC, 2000). Rather, the indirect effect of technological readiness was found significant through the knowledge management capabilities. That is why our model includes an explicitly linked box on 'KDD Technologies': e-marketers cannot win with CRM technologies alone, they need to invest in KDD capabilities as well. KDD capabilities empower organizations to understand customers. KDD helps discover ways to induce customers to participate in co-creation marketing while CRM technologies can be viewed as an enabler of co-creation marketing.

Market Orientation is included in this framework to inject aspects of corporate culture that support strong customer focus. The concept of market orientation has long been examined and extended by many researchers from Narver and Slater (1990) to Nobel, Sinha, and Kumar (2002). Narver and Slater (1990) viewed market orientation as consisting of three behavioral components (customer orientation, competitor orientation, and interfunctional coordination) and two decision criteria (long-term focus and profitability). According to Narver and Slater (1990), customer orientation is defined as 'the sufficient understanding of one's target buyers to be able to create superior value for them continuously' (p. 21). Competitor orientation refers to the situation when 'a seller understands the short-term strengths and weaknesses and long- term capabilities and strategies of both the key current and the key potential competitors ' (Narver and Slater, 1990, p. 22). Finally, interfunctional coordination is viewed as 'the coordinated utilization of company resources in creating superior value for target customers' (Narver and Slater, 1990, p. 22).

Jaworski and Kohli (1993) also investigated the effect of market orientation. They used their own earlier definition (Kohli and Jaworski, 1990), which viewed market orientation as composed of three sets of activities: (1) organization-wide generation of market intelligence pertaining to current and future customer needs, (2) dissemination of the intelligence across departments, and (3) organization-wide responsiveness to it. In their study, they found a strong relationship between market orientation and overall business performance across the environmental contexts (Jaworski and Kohli, 1993).

Many researchers have studied the effect of market orientation on performance and profitability. Quite a few studies have found support for the fundamental market orientation and performance relationship (Pelham, 2000; Narver, Jacobson, and Slater, 1999) while several issues have been raised about the positive effect of market orientation on performance. Some of the issues are about the fact that market orientation is not the only strategic orientation and there may be other critical factors and strategic orientations that affect the business performance (Noble, Sinha, and Kumar, 2002).

It is, however, broadly recognized that successful organizations need to have a customer-oriented business culture (Athanassopoulos, 2000; Deshpande, Farley and Webster, 1993).

In view of the above discussion, since CRM Fit is based on both CRM tasks/goals and the CRM technologies, companies with strong market-oriented culture will interpret CRM tasks in customer-focused ways and therefore adopt better technologies to serve customers in more effective ways. This is the rationale for the major linkage from 'Customer Focus' to 'CRM Technologies' in Figure 12-1. In the My Twin case, for example, the CRM technologies were chosen specifically to boost the customer-knowledge and empathy levels of the call center staff, to serve the high-involvement doll buyers.

Managing customer relationships is not a single project but a continuing process of improving the customer- facing interfaces of the organization. This requires a learning organization that constantly improves its 'Customer-Knowledge Capability,' as shown in the link from 'Customer Focus' to 'KDD Technologies' in Figure 12-1. For e-marketers, KDD is the ongoing process of gathering customer information and knowledge, integrating that into existing organizational knowledge, sharing and leveraging it, and applying it to create value for customers (Dawson, 2000). American Airlines was doing this, in small experimental ways, in terms of test offers to prime prospects chosen through KDD processes. Of course, continuous updating of the customer-knowledge base via CRM is critical - shown by the vertical arrow from CRM Technologies to KDD Technologies in Figure 12-1. Furthermore, good customer-knowledge processes enhance new product or service advantage because such processes enable a firm to detect and explore innovation opportunities in the market as well as to reduce potential risks of mis-fitting buyer needs (Cooper, 1992; Day and Wensley, 1988; Li and Calantone, 1998)

In the Internet era, customer-knowledge capability is critical. Rust and Lemon (2001) noted that the Internet promotes an environment of 'interactive information service,' with consumer wants and needs going in one direction, and highly customized information going in the other direction. They pointed out that if the Internet is used merely as a catalog or new advertising medium, then the organization is failing to take full advantage of the Web-based e-marketing capabilities.

Also, if companies have a good fit with CRM technology and CRM goals, such 'CRM Fit' will boost KDD and customer-knowledge capabilities. Good 'CRM Fit' means that CRM technologies support the CRM tasks well, one of which is analysis of customer data. This is an obvious-sounding requirement of CRM systems, but one that is easily flouted in the cutthroat competitive milieu of CRM vendors. To impress potential CRM adopters, CRM vendors pay lavish attention to those features of CRM that make life easy for the organization, especially the customer-facing sales employees . In such aggressive , competitive positioning, the 'C' for 'Customer' in CRM gets shortchanged. It is up to the adopting organization to mold the CRM system so that it 'fits' the specific task of customer service for that organization - this is the rationale for having 'CRM Fit' as a major component of our proposed model.

In e-marketing contexts, since the interactions with customers are by virtual cyberspace methods , privacy and security concerns pervade all aspects of the framework of Figure 12-1. We have not listed privacy and security as explicit factors because every aspect of e-marketing has to be sensitive to these concerns. CRM systems and KDD systems require adequate safeguards to ensure that personalization and customer intimacy do not turn into personal invasion and customer intimidation .

Are organizations ready to deal with the new waves of privacy and security concerns triggered by new, powerful CRM and KDD technologies? The simple answer at this stage is: Not quite. In the case of American Airlines, the prospects of offending some of the high- tier members , through offers that are perceived as falsely targeted , cannot be ignored. Similar dangers exist in the My Twin and Wells Fargo cases. The leading e-marketer of our times, Amazon.com, tries to mitigate this problem by opening part of its data mining heuristic to the customer. Amazon customers are given the opportunity to manipulate the tweak the 'recommendation engine' that the company uses by strengthening, weakening, or ignoring altogether the bases for particular recommendations.

In the future, organizations would have to move considerably beyond Amazon's current methods. In effect, 'feedback loops ' would be needed from the end-customer side to the CRM and KDD sides in Figure 12-1. The current state of technology and organizational practice is not there yet, and therefore for the time being we leave Figure 12-1 as is.