Use of Data Science for Promotion Optimization in Convenience Chain

Sławomir Mazurowski , Elżbieta Lewańska

Abstract

This paper describes research being conducted in field of promotion planning and optimization for a chain of convenience stores. The motivation for choosing this subject is an important role of promotions in retail market and availability of large amount of data that can be used to improve profitability of promotions. In addition, most of existing studies analyzed promotions in super- and hypermarkets which have a different sales characteristic than a convenience chain. Since transaction amount is typically small (in comparison to transactions in bigger stores), we want to check whether findings from previous studies can be confirmed in our testing environment. In this paper, we show how both internal and external data can be used in order to improve accuracy of forecasts and obtain more reliable performance metrics. The thesis and research goals are presented along with key results of literature review.
Author Sławomir Mazurowski (WIiGE / KIE)
Sławomir Mazurowski,,
- Department of Information Systems
, Elżbieta Lewańska (WIiGE / KIE)
Elżbieta Lewańska,,
- Department of Information Systems
Pages649-660
Publication size in sheets0.55
Book Abramowicz Witold, Corchuelo Rafael (eds.): Business Information Systems Workshops: BIS 2019 International Workshops Seville, Spain, June 26-28, 2019, Revised Papers, Lecture Notes in Business Information Processing, vol. 373, 2019, Springer, ISBN 978-3-030-36690-2, [978-3-030-36691-9], 698 p., DOI:10.1007/978-3-030-36691-9
Keywords in Polishplanowanie działań promocyjnych, optymalizacja działań promocyjnych, retail, sklepu convenience, data-driven decision making
Keywords in EnglishPromotion planning, Promotion optimization, Retail, Convenience store, Data-driven decision making
ASJC Classification1802 Information Systems and Management; 2611 Modelling and Simulation; 1710 Information Systems; 1403 Business and International Management; 2207 Control and Systems Engineering; 1404 Management Information Systems
DOIDOI:10.1007/978-3-030-36691-9_54
Languageen angielski
Score (nominal)70
Score sourceconferenceList
ScoreMinisterial score = 70.0, 22-04-2020, ChapterFromConference
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