Cross-Selling Through Database Marketing: A Mixed Data Factor Analyzer for Data Augmentation and Prediction

Intern. J. of Research in Marketing 20 (2003) 45-65

21 Pages Posted: 14 Feb 2014

See all articles by Wagner A. Kamakura

Wagner A. Kamakura

Rice University

Michel Wedel

University of Maryland - Robert H. Smith School of Business, Marketing Department; University of Groningen - Faculty of Economics and Business

Fernando de Rosa

University of Pittsburgh

Jose Mazzon

University of Sao Paulo (USP)

Date Written: 2002

Abstract

An important aspect of the new orientation on customer relationship marketing is the use of customer transaction databases for the cross-selling of new services and products. In this study, we propose a mixed data factor analyzer that combines information from a survey with data from the customer database on service usage and transaction volume, to make probabilistic predictions of ownership of services with the service provider and with competitors. This data-augmentation tool is more flexible in dealing with the type of data that are usually present in transaction databases. We test the proposed model using survey and transaction data from a large commercial bank. We assume four different types of distributions for the data: Bernoulli for binary service usage items, rank-order binomial for satisfaction rankings, Poisson for service usage frequency, and normal for transaction volumes. We estimate the model using simulated likelihood (SML). The graphical representation of the weights produced by the model provides managers with the opportunity to quickly identify cross-selling opportunities. We exemplify this and show the predictive validity of the model on a hold-out sample of customers, where survey data on service usage with competitors is lacking. We use Gini concentration coefficients to summarize power curves of prediction, which reveals that our model outperforms a competing latent trait model on the majority of service predictions.

Keywords: Database marketing,Cross-selling,Customer relationship management

Suggested Citation

Kamakura, Wagner A. and Wedel, Michel and de Rosa, Fernando and Mazzon, Jose, Cross-Selling Through Database Marketing: A Mixed Data Factor Analyzer for Data Augmentation and Prediction (2002). Intern. J. of Research in Marketing 20 (2003) 45-65. Available at SSRN: https://ssrn.com/abstract=2394905

Wagner A. Kamakura (Contact Author)

Rice University ( email )

6100 South Main Street
P.O. Box 1892
Houston, TX 77005-1892
United States
(713) 348-6307 (Phone)

Michel Wedel

University of Maryland - Robert H. Smith School of Business, Marketing Department ( email )

College Park, MD 20742
United States
301.405.2162 (Phone)
301.405.0146 (Fax)

HOME PAGE: http://www.rhsmith.umd.edu/marketing/faculty/wedel.html

University of Groningen - Faculty of Economics and Business ( email )

Postbus 72
9700 AB Groningen
Netherlands

Fernando De Rosa

University of Pittsburgh ( email )

135 N Bellefield Ave
Pittsburgh, PA 15260
United States

Jose Mazzon

University of Sao Paulo (USP) ( email )

Largo São Francisco, 95
São Paulo
Brazil

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