The main challenge for companies is to identify accurate models and methods to predict winning competitive strategies. Data mining is becoming an astonishing approach for data analysis because the meaningful knowledge is often hidden in enormous databases, and most traditional statistical methods could fail to uncover such knowledge. An efficient development of the customer relationship management and the data mining is the vital resource to collect and to manage this knowledge. The purpose of this chapter is to demonstrate the strong relationship between data mining and customer relationship management in order to forecast customer-centric marketing strategies. The last part of this chapter shows the results of an empirical study related to the identification of the main marketing and financial activities that could be leading customers in a credit-risk state. This study focuses the attention on the logistic regression model and on the criteria based on the loss function
Veglio, V. (2013). The Strategic Importance of Data Mining Analysis for Customer-Centric Marketing Strategies. In Customer-Centric Marketing Strategies. Tools for Building Organizational Performance (pp. 126-148). IGI Global Book [10.4018/978-1-4666-2524-2.ch007].
The Strategic Importance of Data Mining Analysis for Customer-Centric Marketing Strategies
VEGLIO, VALERIO
2013
Abstract
The main challenge for companies is to identify accurate models and methods to predict winning competitive strategies. Data mining is becoming an astonishing approach for data analysis because the meaningful knowledge is often hidden in enormous databases, and most traditional statistical methods could fail to uncover such knowledge. An efficient development of the customer relationship management and the data mining is the vital resource to collect and to manage this knowledge. The purpose of this chapter is to demonstrate the strong relationship between data mining and customer relationship management in order to forecast customer-centric marketing strategies. The last part of this chapter shows the results of an empirical study related to the identification of the main marketing and financial activities that could be leading customers in a credit-risk state. This study focuses the attention on the logistic regression model and on the criteria based on the loss functionFile | Dimensione | Formato | |
---|---|---|---|
Chapter Contribution Veglio.pdf
accesso aperto
Dimensione
443.68 kB
Formato
Adobe PDF
|
443.68 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.