A Product Network Analysis Using A Priori Algorithm for Extending the Market Basket in Retail: A Product Network Analysis Using A Priori Algorithm for Extending the Market Basket in Retail

Research output: Chapter in Book/Report/Conference proceedingPaper (Conference contribution)peer-review

Abstract

Market basket analysis provides an insight into customer consumption patterns and trends in the industry. These will be achieved by analyzing and studying the performance of the large datasets of transactions made by consumers held in retail stores. These commercial transactions will be analyzed using the Machine Learning technique called the A priori algorithm by establishing association rules and determining those groups of items in a market basket whose association could represent better economic benefits for companies. This study will analyze the historical sales data of the product groups, in order to identify relationships that al-low companies in the sector to generate patterns to propose the increase of their portfolio based on the products with the greatest purchasing trends. At the end of this investigation, commercial strategies will be proposed to improve sales, take advantage of spaces in stores and implement more effective strategic offers, based on the groups of articles with the best associations found.
Translated title of the contributionUn análisis de la red de productos utilizando un algoritmo a priori para ampliar la cesta de la compra en el comercio minorista: Un análisis de la red de productos utilizando un algoritmo a priori para ampliar la cesta de la compra en el comercio minorista
Original languageAmerican English
Title of host publicationA Product Network Analysis Using A Priori Algorithm for Extending the Market Basket in Retail
Subtitle of host publicationA Product Network Analysis Using A Priori Algorithm for Extending the Market Basket in Retail
EditorsMd Mizanur Rahman
Place of PublicationSydney, Australia
PublisherIEOM Society International
Pages2025- 2034
Number of pages10
Volume12
Edition7
ISBN (Electronic)979-8-3507-0542-3
ISBN (Print)2169-8767
StatePublished - 22 Dec 2022

Publication series

NameIOEM Society
PublisherIOEM Society
Number7
Volume12
ISSN (Print)2169-8767
ISSN (Electronic)2169-8767

OECD Category

  • Ingeniería industrial

Ulima Repository Category

  • Ingeniería industrial / Logística

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