Studies from R. Vanoest and Co-Authors Have Provided New Information about Marketing Research.

According to recent research from Oslo, Norway, "Extant customer-base models like the beta geometric/negative binomial distribution (BG/NBD) predict future purchasing based on customers' observed purchase history. We extend the BG/NBD by adding an important non-transactional element that also drives future purchases: complaint history."

"Our model retains several desirable properties of the BG/NBD: it can be implemented in readily available software, and estimation requires only customer-specific statistics, rather than detailed transaction-sequence data. The likelihood function is closed-form, and managerially relevant metrics are obtained by drawing from beta and gamma densities and transforming these draws to a sample average. Based on more than two years of individual-level data from a major United States. internet and catalog retailer, our model with complaints outperforms both the original BG/NBD and a modified version. Even though complaints are rare and non-transactional events, they lead to different substantive insights about customer purchasing and drop-out: customers purchase faster but also drop out much faster," wrote R. Vanoest and colleagues.

The researchers concluded: "Furthermore, there is more heterogeneity in drop-out rates following a purchase than a complaint."

Vanoest and colleagues published their study in International Journal of Research in Marketing (Extending the BG/NBD: A simple model of purchases and complaints. International Journal of Research in Marketing, 2011;28(1):30-37).

For additional information, contact R. Vanoest, BI Norwegian School Management, Nydalsveien 37, N-0442 Oslo, NORWAY.

Publisher contact information for the International Journal of Research in Marketing is: Elsevier Science BV, PO Box 211, 1000 AE Amsterdam, Netherlands.

Keywords: City:Oslo, Country:Norway, Region:Europe, Advertising, Marketing, Marketing Research, Software

This article was prepared by Computer Weekly News editors from staff and other reports. Copyright 2011, Computer Weekly News via VerticalNews.com.