Restructuring Knowledge Of Organic Customer Profile Within KM-CRM Framework – By: Garnida, N., Tjakraatmadja, J. H., Nasution, R. A. and Purwanegara, M. S.

Nowadays, organic products have become part of green consumerism movement that “focus on renewable resources and protecting soil and water to improve the quality of life for generations to come” (USDA, 2002). Despite of consumers’ growing support to preserve the environment, the consumption and market share of organic food still constitutes a low percentage compare to total food (Aryal 2008; Bonnini and Oppenheim, 2008). The gap between consumers’ attitude and action toward organic products implies that the business is still lack of knowledge about the true potential of organic customers, i.e. those who accept organic products. It is conceivable that there are some influencing factors as such consumers’ attitude cannot be translated into action.

Therefore, it is suggested that the business should learn the features of customers those taking action, and in turn, use that knowledge to direct organic products’ marketing activities in order to be more effective. Customer relationship management (CRM) is a process designed to collect data related to customers, to grasp features of customers, and to apply those qualities in specific marketing activities (Swift, 2001). In the analytical CRM, these data are stored and analyzed through a range of analytical tools in order to generate customer profiles, identify behavior patterns, determine satisfaction level, and support customer segmentation; thus, customers are more effectively segmented and offered products and services are fitted to customer buying profiles (Xu and Walton, 2005). Nevertheless, even though a wide range of CRM systems are being developed and implemented in practice, application of analytical CRM has been low, due to lack of focus on gaining customer knowledge for strategic decision making from CRM systems, and lack of analytical CRM solutions (Xu and Walton, 2005).

Organizations can strategically use analytical CRM to support customer knowledge acquisition (Xu and Walton, 2005). However, effective use of customer knowledge, particularly in the context of marketing decisions, is still inchoate in many organizations (Bose and Sugumaran, 2003). Knowledge Management (KM), in particular, has been defined as the process of capturing the collective expertise and intelligence in an organization and using them to foster innovation through continued organizational learning (Nonaka, 1991). Then, a framework that link KM to CRM is suggested to effectively use customer knowledge. A significant amount of research has applied KM-CRM framework (Xu and Walton, 2005; Bueren et al., 2005). Nevertheless, this framework still needs to be developed and applied in other industry segments or other potential fields (Bueren et al., 2005).

This study applies a KM-analytical CRM framework to create knowledge about organic customer profile and to identify relevant knowledge that is needed to target the potential customers, i.e. the customers who accept organic products. Case study research was conducted to investigate background of companies that will provide detailed Keywords Customer relationship management Knowledge management Organic customer profile Organic products  contextual data so as to better interpret the result of research data (Creswell, 2003). The purpose of this study is to develop a KM-CRM model for organic products acceptance based on: first, investigation toward customer data mining activities within CRM framework; second, restructuring existing customer data in the company to create knowledge about organic customer profile; third, identification of relevant customer knowledge that support company’s need to target organic customers.

As the conclusion, KM-CRM model for organic products acceptance is developed based on the three steps of actions: customer data mining and analysis, creating knowledge about customer, and identification of relevant customer knowledge for targeting organic customers. Individual factors resulted from quantitative study are used as the basis in developing the model. And then, KM is embedded into CRM to determine degree of KM support in each step of action. This model is line with the current concept of knowledge-based system which includes knowledge of consumers’ behaviors from statistical analysis in CRM (Bensoussan et al., 2009); and includes the three antecedents success factors of knowledgebased system, i.e. knowledge codifiability, absorptive capacity, and inter-organizational relationship quality (Argote et al., 2003). Knowledge codifiability relate to how the consumer knowledge can be codified as thoroughly and as accurately as possible. Absorptive capacity is the ability of a firm to recognize the value of new external information, assimilate it, and apply it to commercial ends. Inter-organizational relationship relate to the effective knowledge sharing between knowledge sources and its recipients, which requires their direct and intimate interaction (Hippel, 1998). As managerial implication, first, this study provides basis to the company in restructuring knowledge about organic customer profile within KM – analytical CRM framework, which is useful in targeting organic customers to be more effective; second, the research proposed different contextual applicability of KM-CRM integration in environmentally friendly products domain. As its limitation, CRM implementation in the companies is still in the early stage; and majority of them only focusing at the operational level, e.g. customer transaction. Thus, the implementation of KM-CRM in the organizations is beyond the scope of this study.

 

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