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.
TopIntroduction
Globalization draws new competitive boundaries, modifying the traditional concepts of time and space (Brondoni, 2008a, 2008b, 2008c). In the global market, companies have crossed spatial and temporal borders (both regional and cultural), selling their products to customers located everywhere and have been aided greatly by the digital revolution that has permitted them to interact with a large amount of data.
Key Terms in this Chapter
Market-Oriented Companies: Are companies committed to understanding the expressed and latent needs of their customers and of the others players in the market better and before than competitors.
Customer Value: Is a process that puts the customer’s interest first, while not excluding those of other stakeholders in order to create a competitive advantage for the firm.
Customer Relationship Management: Is a coherent and complete set of methodologies for managing relationships with current and potential customers.
Customer Purchasing Behavior: Is the set of factors and beliefs that lead customer to make a purchase.
Data Mining: Is the process that uses soft computing techniques to extract and identify useful information and subsequently gain knowledge from large databases.
Globalization: Is a process that, from the 80s, draws new competitive boundaries and rules.
Decision Trees: As a hierarchical collection of rules that describe how to divide a large collection of records into successively smaller group of records. With each successive division, the member of the resulting segment became more and more similar to one another with respect to the dependent variable.