Linking Multi-Category Purchases to Latent Activities of Shoppers: Analysing Market Baskets by Topic Models

Harald Hruschka

No 482, University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics

Abstract: We investigate the application of two topic models, latent Dirichlet allocation (LDA) and the correlated topic model (CTM), to market basket analysis. Topic models measure the association between observed purchases and underlying latent activities of shoppers by conceiving each basket as random mixture of latent activities. We explain the structure of the two topic models used. We discuss estimation of LDA models by blocked Gibbs sampling. In addition we show how to evaluate the performance of topic models on estimation and holdout data. In the empirical study we analyse a total of 18,000 purchases made at a medium-sized supermarket which refer to 60 product categories. The LDA model performs better than the CTM in terms of log likelihood values. Latent activities inferred by this models are intuitive and interpretable, e.g., related to shopping of beverages or personal care, to baking or to an inclination towards luxury food. To illustrate the managerial relevance of estimated topic models we sketch the core of a recommender system which ranks purchase probabilities of other product categories conditional on the basket of a shopper.

Keywords: multi-category buying behavior; market basket analysis; topic models (search for similar items in EconPapers)
JEL-codes: C11 C35 L81 (search for similar items in EconPapers)
Date: 2014-09-05
New Economics Papers: this item is included in nep-dcm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://epub.uni-regensburg.de/30747/1/Diskussionsbeitrag%20Complete.pdf (application/pdf)
https://epub.uni-regensburg.de/30747/7/Diskussionsbeitrag%20Komplett.pdf (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:bay:rdwiwi:30747

Access Statistics for this paper

More papers in University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Gernot Deinzer ().