The Strategic Importance of Data Mining Analysis for Customer-Centric Marketing Strategies

The Strategic Importance of Data Mining Analysis for Customer-Centric Marketing Strategies

Valerio Veglio
DOI: 10.4018/978-1-4666-2524-2.ch007
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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 function.
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Introduction

The development of the Internet and the World Wide Web has completely changed the way marketing is done. They have made the process of collecting data easier, adding to volume of data available to business. Companies have realized that the knowledge in this enormous database is the key to supporting the various business decisions, in particular for the marketing function. Bueren, Schierholz, Kolbe, and Brenner (2004) define knowledge as a strategic intangible resource at the base of the competitive advantages. Besides, the most important type of knowledge would appear to be customer knowledge. An efficient utilization of customer knowledge determines the development of firms. This is particularly true in marketing area because of the proliferation of customer data collect in the huge databases.

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