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Home | News | Paper by Dennis Fok and Bas Donkers in Marketing Science
News | April 12, 2021

Paper by Dennis Fok and Bas Donkers in Marketing Science

In the paper ‘Large-Scale Dynamic Purchase Behavior,’ faculty members Dennis Fok (Erasmus University Rotterdam) and Bas Donkers (Erasmus University Rotterdam) with co-author Bruno Jacobs (The University of Maryland, United States) develop a new model to gain insights in dynamic purchase behavior for retail contexts with a large product assortment and customer base. These insights are described in terms of purchase motivations, which they discover using purchase history data. They illustrate the model on data from a Fortune 500 retailer involving more than 4000 products. The code has been made available as an open source Python Package.

Paper by Dennis Fok and Bas Donkers in Marketing Science

In modern retail contexts, retailers sell products from vast product assortments to a large and heterogeneous customer base. Understanding purchase behavior in such a context is very important. Standard models cannot be used because of the high dimensionality of the data. We propose a new model that creates an efficient dimension reduction through the idea of purchase motivations. We only require customer-level purchase history data, which is ubiquitous in modern retailing. The model handles large-scale data and even works in settings with shopping trips consisting of few purchases. Essential features of our model are that it accounts for the product, customer, and time dimensions present in purchase history data; relates the relevance of motivations to customer- and shopping-trip characteristics; captures interdependencies between motivations; and achieves superior predictive performance. Estimation results from this comprehensive model provide deep insights into purchase behavior. Such insights can be used by managers to create more intuitive, better informed, and more effective marketing actions. As scalability of the model is essential for practical applicability, we develop a fast, custom-made inference algorithm based on variational inference. We illustrate the model using purchase history data from a Fortune 500 retailer involving more than 4,000 unique products.

Article Citation:

Bruno Jacobs, Dennis Fok, and Bas Donkers, ‘Large-Scale Dynamic Purchase Behavior’, Marketing Science, published online April 6, 2021, https://doi.org/10.1287/mksc.2020.1279.