Predictive Modeling in Marketing: Ensemble Methods for Response Modeling
Gabriela Alves Werb and
Martin Schmidberger
Die Unternehmung - Swiss Journal of Business Research and Practice, 2021, vol. 75, issue 3, 376-396
Abstract:
Ensemble methods have received a great deal of attention in the past years in several disciplines. One reason for their popularity is their ability to model complex relationships in large volumes of data, providing performance improvements compared to traditional methods. In this article, we implement and assess ensemble methods’ performance on a critical predictive modeling problem in marketing: predicting cross-buying behavior. The best performing model, a random forest, manages to identify 73.3 % of the cross-buyers in the holdout data while maintaining an accuracy of 72.5 %. Despite its superior performance, researchers and practitioners frequently mention the difficulty in interpreting a random forest model’s results as a substantial barrier to its implementation. We address this problem by demonstrating the usage of interpretability methods to: (i) outline the most influential variables in the model; (ii) investigate the average size and direction of their marginal effects; (iii) investigate the heterogeneity of their marginal effects; and (iv) understand predictions for individual customers. This approach enables researchers and practitioners to leverage the superior performance of ensemble methods to support data-driven decisions without sacrificing the interpretability of their results.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.nomos-elibrary.de/10.5771/0042-059X-2021-3-376 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nms:untern:10.5771/0042-059x-2021-3-376
Ordering information: This journal article can be ordered from
Nomos Verlagsgesellschaft mbH & Co. KG, Waldseestraße 3-5, 76530 Baden-Baden, Germany
https://www.nomos-sh ... w.aspx?product=13597
DOI: 10.5771/0042-059X-2021-3-376
Access Statistics for this article
Die Unternehmung - Swiss Journal of Business Research and Practice is currently edited by Prof. Dr. Artur Baldauf, Universität Bern, Prof. Dr. Manfred Bruhn, Universität Basel, Prof. Dr. Pascal Gantenbein, Universität Basel (geschäftsführend), Prof. Dr. Markus Gmür, Universität Fribourg, Prof. Dr. Klaus Möller, Universität St. Gallen, Prof. Dr. Günter Müller-Stewens, Universität St. Gallen, Prof. Dr. Dr. h.c. Margit Osterloh, Universität Zürich, Prof. Dr. Dieter Pfaff, Universität Zürich and Prof. Dr. Martin Wallmeier, Universität Fribourg
More articles in Die Unternehmung - Swiss Journal of Business Research and Practice from Nomos Verlagsgesellschaft mbH & Co. KG
Bibliographic data for series maintained by Nomos Verlagsgesellschaft mbH & Co. KG ().