WIT Press

Customer Valuation Through Data Mining


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285 kb

Paper DOI



WIT Press


C. Fernando Nogueira & N. F. F. Ebecken


In this study, a comprehensive assessment of a variety of customer contribution components is done, whereby the appropriate approach or its close alternatives are applied to the large number of parameters that drive customer value. Apart from the measurable actual contributions, represented by each customer’s current portfolio of products and services, and the company’s costs to provide and deliver them, the potential contribution is discussed, from a marketing standpoint, and considered through a data mining approach. As a Managerial Information System, the proposed individual customer valuation methodology is driven to support concrete decisions, thereby differentiating it from a simple P&L (Profits and Losses) split, among customers. The proposed methodology is implemented in a real customer base sample, allowing the measurement of benefits it would effectively capture. 1 Introduction Everyday, new Customers cost more to be acquired. On the other hand, the actual offer has a tendency to devaluate, due to the effects of the competition imposed by the markets maturity Gensch et al. [1]. Managing customers, and not just Products, means the possibility of rationalizing the companies functions, in order to better explore their source of survival, which for a long time considered being their products. They could try to sell more, to customers that potentially could have superior profiles of use, or better for those that are a priority to keep, being less profitable or more attentive, for example. Companies can also proactively establish stronger and lasting ties with the right Customers. \“CRM strategies and technologies are designed to help organizations build profitable relationships with customers through the collection and dissemination of actionable customer insight across the company. CRM assists in recognizing