A Predictive Model of Customer Monetary Spending Based on Geometric Purchase Time and Lognormal Monetary Model

10.6186/IJIMS.2014.25.2.6

Hui-Hsin Huang

Interpurchase time ； monetary ； geometric distribution

International Journal of Information and Management Sciences

25卷2期（2014 / 07 / 01）

181 - 194

英文

The monetary amount of customers' purchases and interpurchase time are two related and important variables in the realm of business marketing. Yet most research has formulated them independently in prediction models. This paper proposes a prediction model of customer monetary spending using information on interpurchase time. Unlike previous research, we consider interpurchase time according to geometric distribution. Moreover, our monetary prediction model combines interpurchase time and an underlying (basic unit) monetary amount which is assumed as log normal distribution. This study collects empirical data to validate the proposed model and estimate its parameters. We also compare our results with those of interpurchase time following exponential distribution. The results show that our proposed model performances better at monetary forecasting than the exponential model does.

1. Kao, L. L., Jen, L. and Allenby, G. M. (2005). A state-space model of purchase timing for direct marketing, working paper
2. Bell, D. R.,Lattin, J. M.(1998).Shopping behavior and consumer preference for store price format: Why 'large basket' shoppers prefer EDLP.Marketing Science,17,66-88.
3. Boatwright, P.,Borle, S.,Kadane, B. J.(2003).A model of the joint distribution of purchase quantity and timing.Journal of the American Statistical Association,98,564-572.
4. Boizot, C.,Robin, J. M.,Visser, M.(2001).The demand for food products: an analysis of interpurchase times and purchased quantities.The Economic Journal,111,391-419.
5. Borle, S.,Singh, S. S.,Jain, D. C.(2008).Customer lifetime value measurement.Management Science,54,100-112.
6. Bucklin, R. E.,Gupta, S.(1999).Use of UPC scanner data: Industry and academic perspectives.Marketing Science,18,247-273.
7. Choi, J.,Kim, B. K.,Choi, I.,Yi, Y.(2006).Variety-seeking tendency in choice for others: interpersonal and intrapersonal causes.Journal of Consumer Research,32,590-595.
8. Fader, S. P.,Hardie, G. S. B.,Lee, K.(2005).RFM and CLV: Using iso-value curves for customer base analysis.Journal of Marketing Research,12,415-430.
9. Goukens, C.,Dewitte, S.,Pandelaere, M.,Warlop, L.(2007).Wanting a Bit(e) of everything: extending the valuation effect to variety seeking.Journal of Consumer Research,34,386-394.
10. Gupta, S.(1988).Impact of sales promotions on when, what and how much to buy.Journal of Marketing research,25,342-356.
11. Homburg, C.,Gierin, A.(2001).Personal characteristics as moderators of the relationship between customer satisfaction and loyalty - an empirical analysis.Psychology and Marketing,18,4366.
12. Jen, L.,Chou, C. H.,Allenby, G. M.(2009).The importance of modeling temporal dependence of timing and quantity in direct marketing.Journal of marketing research,46,482-493.
13. Miglautsch, J.(2002).Application of RFM principles: What to do with 1-1-1 Customers?.Journal of Database Marketing,9,319-324.
14. Oliveira-Castro, J. M.,James, V. K.,Foxall, G. R.(2007).Postreinforcement pause in grocery shopping: Comparing interpurchase times across products and consumers.The Psychological Record,57,483-500.
15. Roehm, H. A.,Roehm, M. L.(2005).Revisiting the effect of positive mood on variety seeking.Journal of Consumer Research,32,330-336.
16. Rossi, P. E.,McCulloch, R. E.,Allenby, G. M.(1996).The value of purchase history data in target marketing.Marketing Science,15,147-165.
17. Stone, B.(1995).The Successful Direct Marketing.Lincolnwood, IL.:NTC Business Books.