Abstract
The main goal of this paper is the calculation of a multi-product model of Customer Potential Value using the Probit method. The results of this first analysis are used to perform an ex-post segmentation of customers, whose output can be employed to improve Customer Relationship Management strategies of the companies. Our research contributes to the consumer behaviour literature insofar as, according to our knowledge, no previous work has examined collectively the proposed drivers of Customer Potential Value in a multi-services retailer. To achieve these objectives, we use a panel data of a Spanish bank. The results allow us to confirm the influence of a set of behavioural variables on the ownership of different banking products and identify those customers whose value is higher and lower through the calculation of Customer Potential Value.
Highlights
Due to the rise of the new concept of Customer Relationship Management (CRM) a new age for companies began in the eighties in which making a sale was just the beginning of a relationship with a customer, not the end
To check the existence of multicollinearity, we examine bivariate correlation values and the Variance Inflation Factor (VIF) criterion
In this research we have carried out a dynamic analysis, which implies the calculation of Customer Potential Value (CPV) of customers of a multi-services retailer estimating a multi-product model
Summary
Due to the rise of the new concept of Customer Relationship Management (CRM) a new age for companies began in the eighties in which making a sale was just the beginning of a relationship with a customer, not the end. An increasing number of companies have realized that their most valuable asset is its customer base (Schulze et al 2012) and these customer relationships have been termed relational market-based assets of companies for decades (Srivastava et al 1998, 2001). This fact has further increased the focus on managing relationships with customers (CRM) and led to the Journal of Business Economics and Management, 2016, 17(4): 580–597 implementation of a Customer Relationship approach (Reinartz et al 2004), using customer data for the benefit of the company, and for the benefit of the customer (Saarijärvi et al 2013). Customers play a key role in the creation of value for the firm and, the process of identification of the most profitable/ valuable customers is essential to secure an effective competitive advantage for the firm
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