Bottleneck Identification And Critical Failure Factors In Data Mining Projects Of CRM
Competition to acquire and maintain valuable customers is significantly increased among companies. Many studies have investigated the maintenance and growth of customers to improve the performance indicators such as retention rate, collection and organization of customers’ data, creating customers’ profiles and modeling the users. With the occurrence of changes in the business environment, markets have saturated and the volume and growth rate of data have increased as well as decisions must be made as quick as possible and with maximum knowledge. Use of data mining methods is increasing. At present, Customer relationship management (CRM) and data mining projects as well as the wrong choice of methods and tools are very costly and many of these projects fail. Aim of this article is investigate concepts of CRM, data mining and the relationship between them as well as the reasons for their success or failure so that we have identified bottlenecks and offered solutions to prevent them.
Keywords- CRM; Data Mining; Bottleneck Identification; Data warehouse; Critical Failure Factors (CFF).