For companies to gain competitive advantage, an effective customer relationship management (CRM) approach is necessary. Based on customer purchase behaviour and ordering patterns, companies can be classified into different categories in terms of providing customised sales and promotions for customers. However, companies that lack an effective CRM strategy can only offer the same sales and marketing strategies to all customers. Furthermore, the traditional approach to managing customers is control via a centralised method, in which the information regarding customer segmentation is not shared among the customer network. Consequently, valuable customers may be neglected, resulting in the loss of customer loyalty and sales orders, and the weakening of trust in the customer–company relationship. This paper designs an integrated data analytic model (IDAM) in a peer-to-peer cloud, integrating RFM-based k-means clustering algorithm, analytical hierarchy processing and fuzzy logic to divide customers into different segments and hence formulate a customised sales strategy. A pilot study of IDAM is conducted in a trading company specialised in providing advanced manufacturing technology to demonstrate how IDAM can be applied to formulate an effective sales strategy to attract customers. Overall, this study explores the effective deployment of CRM into the peer-to-peer cloud so as to facilitate sales strategy formulation and trust between customers and companies in the network.
- Customer behaviour
- Customer relationship management
- Data analytic
- Peer-to-peer cloud
- Sales strategy formulation
ASJC Scopus subject areas
- Computer Networks and Communications