The Need for Market Segmentation in Buy-Till-You-Defect Models

47 Pages Posted: 25 Apr 2014

See all articles by Evsen Korkmaz

Evsen Korkmaz

Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management

D. Fok

Econometric Institute - Erasmus University Rotterdam; Erasmus Research Institute of Management (ERIM); Tinbergen Institute Rotterdam

R. Kuik

Erasmus Research Institute of Management (ERIM)

Date Written: April 25, 2014

Abstract

Buy-till-you-defect [BTYD] models are built for companies operating in a non- contractual setting to predict customers’ transaction frequency, amount and timing as well as customer lifetime. These models tend to perform well, although they often predict unrealistically long lifetimes for a substantial fraction of the customer base. This obvious lack of face validity limits the adoption of these models by practitioners. Moreover, it highlights a flaw in these models. Based on a simulation study and an empirical analysis of different datasets, we argue that such long lifetime predictions can result from the existence of multiple segments in the customer base. In most cases there are at least two segments: one consisting of customers who purchase the service or product only a few times and the other of those who are frequent purchasers. Customer heterogeneity modeling in the current BTYD models is insufficient to account for such segments, thereby producing unrealistic lifetime predictions. We present an extension over the current BTYD models to address the extreme lifetime prediction issue where we allow for segments within the customer base. More specifically, we consider a mixture of log-normals distribution to capture the heterogeneity across customers. Our model can be seen as a variant of the hierarchical Bayes [HB] Pareto/NBD model. In addition, the proposed model allows us to relate segment membership as well as within segment customer heterogeneity to selected customer characteristics. Our model, therefore, also increases the explanatory power of BTYD models to a great extent. We are now able to evaluate the impact of customers’ characteristics on the membership probabilities of different segments. This allows, for example, one to a-priori predict which customers are likely to become frequent purchasers. The proposed model is compared against the benchmark Pareto/NBD model (Schmittlein, Morrison, and Colombo 1987) and its HB extension (Abe 2009) on simulated datasets as well as on a real dataset from a large grocery e-retailer in a Western European country. Our BTYD model indeed provides a useful customer segmentation that allows managers to draw conclusions on how customers’ purchase and defection behavior are associated with their shopping characteristics such as basket size and the delivery fee paid.

Keywords: buy-till-you-defect models, segmentation, mixture of normals, Bayesian estimation, customer base analysis

Suggested Citation

Korkmaz, Evsen and Fok, Dennis and Kuik, R., The Need for Market Segmentation in Buy-Till-You-Defect Models (April 25, 2014). ERIM Report Series Reference No. ERS-2014-006-LIS. Available at SSRN: https://ssrn.com/abstract=2429239 or http://dx.doi.org/10.2139/ssrn.2429239

Evsen Korkmaz (Contact Author)

Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management ( email )

RSM Erasmus University
PO Box 1738
3000 DR Rotterdam
Netherlands

Dennis Fok

Econometric Institute - Erasmus University Rotterdam ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31 10 408 1333 (Phone)
+31 10 408 9162 (Fax)

Tinbergen Institute Rotterdam ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

R. Kuik

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Register to save articles to
your library

Register

Paper statistics

Downloads
148
rank
194,215
Abstract Views
1,224
PlumX Metrics
!

Under construction: SSRN citations while be offline until July when we will launch a brand new and improved citations service, check here for more details.

For more information