Sales Spotter: An Algorithm to Identify Sale Prices in Point-of-Sale Data

33 Pages Posted: 15 Jun 2015

See all articles by Iqbal A. Syed

Iqbal A. Syed

UNSW Australia Business School, School of Economics

Date Written: June 10, 2015

Abstract

This paper develops an algorithm, called the sales spotter, which identifies the sale prices in the transaction price series provided in point-of-sale data. The goal of the sales spotter is to identify the maximum number of sale prices while minimizing the incorrect attribution of non-sale price reductions to sale prices. The spotter is developed and the values of its parameters are selected by analysing around 7.5 million flagged sales in a US supermarket scanner data. At the optimal values of the parameters, the spotter identifies 84% of authentic flagged sale weeks in the data.

Keywords: Promotional price, regular price, shelf price, sales filter, scanner data

JEL Classification: E30, M37

Suggested Citation

Syed, Iqbal A., Sales Spotter: An Algorithm to Identify Sale Prices in Point-of-Sale Data (June 10, 2015). UNSW Business School Research Paper No. 2015-13. Available at SSRN: https://ssrn.com/abstract=2616090 or http://dx.doi.org/10.2139/ssrn.2616090

Iqbal A. Syed (Contact Author)

UNSW Australia Business School, School of Economics ( email )

High Street
Sydney, NSW 2052
Australia

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