Point of Sale (POS) Data from a Supermarket: Transactions and Cashier Operations

Tomasz Antczak,Rafał Weron

doi:10.3390/data4020067

Tomasz Antczak, Rafał Weron

Open Access

https://doi.org/10.3390/data4020067

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Abstract

As queues in supermarkets seem to be inevitable, researchers try to find solutions that can improve and speed up the checkout process. This, however, requires access to real-world data for developing and validating models. With this objective in mind, we have prepared and made publicly available high-frequency datasets containing nearly six weeks of actual transactions and cashier operations from a grocery supermarket belonging to one of the major European retail chains. This dataset can provide insights on how the intensity and duration of checkout operations changes throughout the day and week.

Highlights

As queues in supermarkets seem to be inevitable, researchers try to find solutions that can improve and speed up the checkout process
The data was retrieved from checkout/point of sale (POS) system logs stored in XML files, which contained various low-level transactional data
It was aggregated into six CSV files with the most important information about (i) transactions; and (ii) cashier operations, see Tables 1 and 2, respectively

Summary

Mou et al [1] reviewed 255 publications from 32 operations research, retailing and management journals over the period 2008–2016 and categorized works by distinguishing seven operational decisions pertinent to store management. These included: (1) demand forecasting; (2) in store logistics;. Even if such data is analyzed, it is often “proprietary and not available to researchers at large”, as in the case of the Mas and Moretti dataset [6] With this in mind, we have prepared and made publicly available high-frequency datasets containing nearly six weeks of actual transactions and cashier operations from a grocery supermarket belonging to one of the major European retail chains. It can be used to provide feedback, e.g., in the form of voice or visual messages, about the current or near-future state of the checkout zone, with the ultimate objective of speeding up the checkout process and increasing consumer satisfaction [8]

Data Description

Methods