In the global market of today, Customer Relationship Management (CRM) plays a fundamental role in market-oriented companies to understand customer behaviors, achieve and maintain a long-term relationship with them, and maximize the customer value. Moreover, the digital revolution has made information easy and fairly inexpensive to capture. Thus, companies have stored a large amount of data about their current and potential customers. However, this data is often raw and meaningless. Within the CRM framework, Data Mining (DM) is a very popular tool for extracting useful information from this data and for predicting customer behaviors in order to make profitable marketing decisions. This research aims to demonstrate the classification decision tree as one of the main computational data mining models able to forecast accurate marketing performance within global organizations. Particular attention is paid to the identification of the best marketing activities to which firms should concentrate their future marketing investments. The criteria is based on the loss functions that confirm the accuracy of this model.

Gordini, N., Veglio, V. (2014). Customer Relationship Management and Data Mining: A Classification Decision Tree to Predict Customer Purchasing Behavior in Global Market. In P.M. Vasant (a cura di), Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications (pp. 1-40). IGI Global [10.4018/978-1-4666-4450-2.ch001].

Customer Relationship Management and Data Mining: A Classification Decision Tree to Predict Customer Purchasing Behavior in Global Market

GORDINI, NICCOLO'
Primo
;
VEGLIO, VALERIO
Ultimo
2014

Abstract

In the global market of today, Customer Relationship Management (CRM) plays a fundamental role in market-oriented companies to understand customer behaviors, achieve and maintain a long-term relationship with them, and maximize the customer value. Moreover, the digital revolution has made information easy and fairly inexpensive to capture. Thus, companies have stored a large amount of data about their current and potential customers. However, this data is often raw and meaningless. Within the CRM framework, Data Mining (DM) is a very popular tool for extracting useful information from this data and for predicting customer behaviors in order to make profitable marketing decisions. This research aims to demonstrate the classification decision tree as one of the main computational data mining models able to forecast accurate marketing performance within global organizations. Particular attention is paid to the identification of the best marketing activities to which firms should concentrate their future marketing investments. The criteria is based on the loss functions that confirm the accuracy of this model.
Capitolo o saggio
Customer Relationship Management, Customer Satisfaction, Data Mining
English
Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications
Vasant, PM
2014
9781466644502
1-2
IGI Global
1
40
Gordini, N., Veglio, V. (2014). Customer Relationship Management and Data Mining: A Classification Decision Tree to Predict Customer Purchasing Behavior in Global Market. In P.M. Vasant (a cura di), Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications (pp. 1-40). IGI Global [10.4018/978-1-4666-4450-2.ch001].
none
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/53495
Citazioni
  • Scopus 13
  • ???jsp.display-item.citation.isi??? 20
Social impact