Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/3732
Title: Business Intelligence and Data Mining to Support Sales in Retail
Authors: Castelo-Branco, Francisca
Reis, José Luís
Carvalho Vieira, José
Cayolla, Ricardo
Keywords: Data mining
Business intelligence
Market basket analysis
Sales
Retail
Issue Date: Jan-2020
Publisher: Springer
Citation: Castelo-Branco F., Reis J.L., Vieira J.C., & Cayolla R. (2020). Business Intelligence and Data Mining to Support Sales in Retail. In: Rocha Á., Reis J., & Peter M., Bogdanović Z. (eds.), Marketing and Smart Technologies. Smart Innovation, Systems and Technologies,167. Springer, Singapore. https://doi.org/10.1007/978-981-15-1564-4_38. Disponível no Repositório UPT, http://hdl.handle.net/11328/3732
Abstract: Markets are increasingly competitive, and organizations are constantly finding ways to improve their data processing in order to be able to find their customers’ behavioral patterns when they buy their products. The aim of this study is to create a body of knowledge, so that a project can use the tools and techniques associated with data mining in retail sales in a proper way, presented concepts and key techniques like market basket analysis, association rules and cross-selling and up-selling. Companies make expert use of statistics and modeling to improve a wide variety of functions. In the paper are presented some common applications of business intelligence. As well as successful examples of data mining applied to retail sales, some information is also presented in this work to explain the prospects for the future of retail.
URI: http://hdl.handle.net/11328/3732
ISBN: 978-981-15-1563-7 (Print)
ISSN: 978-981-15-1564-4 (Online)
Appears in Collections:REMIT - Livros e Capítulos de Livros / Books and Book Chapters



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