Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study
Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study
Author(s): Damla Aslan, Metehan TolonSubject(s): Business Economy / Management, Marketing / Advertising, ICT Information and Communications Technologies
Published by: İşletme Araştırmaları Dergisi
Keywords: B2B Marketing; Customer Segmentation; Customer Lifetime Value; CLV; k-means;
Summary/Abstract: Customer segmentation is an essential activity for marketing executives. To penetrate to target market, they should analyze their clients very well. Undoubtfully customer lifetime value (CLV) is a compact calculation method to understand customer behaviors and their values. Various models are presented for CLV interpretation in literature. Two of them are statistical hypothesis tests and k-means. This case study provides the comparison these methods for a B2B IT company. The methodology can easily be used for similar purposes in other organizations. The successful clusters are obtained by k-means application.
Journal: İşletme Araştırmaları Dergisi
- Issue Year: 10/2018
- Issue No: 4
- Page Range: 887-900
- Page Count: 14
- Language: English