Integrating AHP and data mining for product recommendation based on customer lifetime value

2005 ◽  
Vol 42 (3) ◽  
pp. 387-400 ◽  
Author(s):  
Duen-Ren Liu ◽  
Ya-Yueh Shih
Keyword(s):  
Data Mining ◽  
Customer Lifetime Value ◽  
Product Recommendation ◽  
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.

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