CRM strategies for a small-sized online shopping mall based on association rules and sequential patterns

A Multidimensional CRM Approach for Enhancing Marketing Innovation Capabilities of Construction Companies Using Structural Equation Modeling

“…Consistent with the above, other such as Santouridis and Tsachtani, [20] and Shim et al [26] shed light on information technology in CRM practices, they indicated that customer relationship management relies heavily on gathering and processing customer data in order to extract information that will help to identify ideal customers and customize their offerings s a result of this, information technology plays a pivotal role as an enabler of successful CRM implementation. In this study, we adopted the operational concept that define customer relationship management as a business approach involves a set of methodologies and information and organizational processes to build long term and profitable relationships with customers for creating competitive advantage and achieving marketing innovation capability.…”

An Assessment of Data Mining Based CRM Techniques for Enhancing Profitability

“…Several of them have poor customer relationship management strategies and need to close them. The authors [13] analyze customer transactions data of the online shopping mall and propose sequential patterns and association rules. Firstly, authors [13] define the VIP customers based on recency, frequency and monetary (RFM) values.…”

“…The authors [13] analyze customer transactions data of the online shopping mall and propose sequential patterns and association rules. Firstly, authors [13] define the VIP customers based on recency, frequency and monetary (RFM) values. Formerly, they design a model which categories customers into non-VIP and VIP.…”

“…Shim et al [13] develop CRM approach using association rules and sequential patterns for a small size online shopping mall. In 2002, dot-com bubble burst was established and contained several small-sized online shopping centers.…”

“…Formerly, they design a model which categories customers into non-VIP and VIP. The authors [13] used various data mining techniques such as logistic regression, bagging decision tree, artificial neural network and decision tree with each of these as a base classifier. Lastly, they identify patterns and rules for VIPs customer from the transactional data using association rules and sequential patterns and then design CRM strategies for the online shopping mall.…”