Carrasco, Mariflor Vega;
Musolesi, Mirco;
O'Sullivan, Jason;
Prior, Rosie;
Manolopoulou, Ioanna;
(2024)
Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models.
Applied Stochastic Models in Business and Industry
10.1002/asmb.2890.
(In press).
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Abstract
Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs. Product availability may vary geographically due to local demand and local supply, thus driving the importance of analysing transactions within their corresponding store and regional context. Topic models provide a powerful tool in the analysis of transactional data, identifying topics that display frequently-bought-together products and summarising transactions as mixtures of topics. We use the segmented topic model (STM) to capture customer behaviours that are nested within stores. STM not only provides topics and transaction summaries but also topical summaries at the store level that can be used to identify regional topics. We summarise the posterior distribution of STM by post-processing multiple posterior samples and selecting semantic modes represented as recurrent topics, and employ Gaussian process regression to model topic prevalence across British territory while accounting for spatial autocorrelation. We implement our methods on a dataset of transactional data from a major UK grocery retailer and demonstrate that shopping behaviours may vary regionally and nearby stores tend to exhibit similar regional demand.
| Type: | Article |
|---|---|
| Title: | Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/asmb.2890 |
| Publisher version: | http://dx.doi.org/10.1002/asmb.2890 |
| Language: | English |
| Additional information: | Copyright © 2024 The Author(s). Applied Stochastic Models in Business and Industry published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Latent Dirichlet allocation; retail analytics; segmented topic model; spatial modelling; topic modelling |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10199385 |
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