scholarly journals Data mining framework for customer lifetime value-based segmentation

2012 ◽  
Vol 19 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Harsha Aeron ◽  
Ashwani Kumar ◽  
Janakiraman Moorthy
Keyword(s):  
Data Mining ◽  
Customer Lifetime Value ◽  
Customer Lifetime ◽  
Lifetime Value

Data Mining Techniques to Enhance Customer Lifetime Value

2011 ◽  
Vol 225-226 ◽  
pp. 3-7
Author(s):  
Chia Chia Lin ◽  
Dong Her Shih
Keyword(s):  
Data Mining ◽  
Clustering Analysis ◽  
Critical Factor ◽  
Department Store ◽  
Customer Lifetime Value ◽  
Data Mining Techniques ◽  
Customer Lifetime ◽  
Rfm Model ◽  
Lifetime Value

It is proved by many studies that it is more costly to acquire than to retain customers. Consequently, evaluating current customers to keep high value customers and enhance their lifetime value becomes a critical factor to decide the success or failure of a business. This study applies data from customer and transaction databases of a department store, based on RFM model to do clustering analysis to recognize high value customer groups for cross-selling promotions.

scholarly journals An Empirical Assessment of Customer Lifetime Value Models within Data Mining

2018 ◽  
Vol 6 (4) ◽  
Author(s):  
Abdulkadir Hiziroglu ◽  
Merve Sisci ◽  
Halil Ibrahim Cebeci ◽  
Omer Faruk Seymen
Keyword(s):  
Data Mining ◽  
Customer Lifetime Value ◽  
Empirical Assessment ◽  
Customer Lifetime ◽  
Lifetime Value
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