International Journals
Permanent URI for this collectionhttps://dspace.psgrkcw.com/handle/123456789/115
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Item PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM(Speak Foundation-International Journal of Management and Social Sciences(IJMSS), 2018-12) M, Rajeswari; S, DeepikaCompetitive advantage is gained by firm through new areas such as data warehousing, data mining and campaign management software have made Customer Relationship Management(CRM). This research aims to develop methodologies for predicting customer churn in advance, while keeping misclassification rates to a minimum.Item DEVELOPMENT OF MODIFIED RIPPER ALGORITHM TO PREDICT CUSTOMER CHURN(International Journal of Advance Research in Engineering Science and Technology, 2018-02) M, RajeswariTechnologies such as data warehousing, data mining, and campaign management software have made Customer Relationship Management (CRM) a new area where firms can gain a competitive advantage. Particularly through data mining a process of extracting hidden predictive information from large databases, organizations can identify their valuable customers, predict future behaviors, and enable firms to make proactive, knowledge-driven decisions. Data Mining along with Customer Relationship Management plays a vital role in today’s business environment. Customer churn, a process of retaining customer is a major issue. Prevention of customer churn is a major problem because acquiring new customer is more expensive than holding existing customers. In order to prevent churn several data mining techniques have been proposed. One among such method is solving class imbalance which has not received much attention in the context of data mining. This paper describes Customer Relationship Management (CRM), customer churn and class imbalance and proposes a methodology for preventing customer churn through class imbalance.Item DESIGN OF MODIFIED RIPPER ALGORITHM TO PREDICT CUSTOMER CHURN(SPC(Science Publishing Corporation), International Journal of Engineering and Technology, 2015) M, Rajeswari; T, DeviTechnologies such as data warehousing, data mining, and campaign management software have made Customer Relationship Management (CRM) a new area where firms can gain a competitive advantage. It is becoming common knowledge in business that retaining existing customers is an important strategy to survive in industry. Once identified, these customers can be targeted with proactive retention campaigns in a bid to retain them. These proactive marketing campaigns usually involve the offering of incentives to attract the customer into carrying on their service with the supplier. These incentives can be costly, so offering them to customers who have no intention to defect results in lost revenue. Also many predictive techniques do not provide significant time to make customer contact. This time restriction does not allow sufficient time for capturing those customers who are intending to leave. This research aims to develop methodologies for predicting customer churn in advance, while keeping misclassification rates to a minimum.