{"title":"A market basket analysis of the US auto-repair industry","authors":"Hilde Patron, Laureano Gomez","doi":"10.1080/2573234x.2020.1838958","DOIUrl":null,"url":null,"abstract":"ABSTRACT Market basket analysis (MBA), or the mining of transactional data to uncover association rules, is a popular methodology used in managerial decision making. MBA is centered around three key parameters: support, confidence, and lift, and the choice of starting values for these parameters can have a significant impact on the results of the analysis. We develop a procedure in R around the Apriori algorithm to help in identifying lift maximising rules when the support covers a specified proportion. The procedure facilitates the choice of minimum parameters, eliminates redundancies, and organizes the resulting association rules into actionable formats. When applied to the US auto repair data, we find un-exploited bundling packages that can be added to the scheduled maintenance services of traditional marketing campaigns.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"9 1","pages":"79 - 92"},"PeriodicalIF":1.7000,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2573234x.2020.1838958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 4
Abstract
ABSTRACT Market basket analysis (MBA), or the mining of transactional data to uncover association rules, is a popular methodology used in managerial decision making. MBA is centered around three key parameters: support, confidence, and lift, and the choice of starting values for these parameters can have a significant impact on the results of the analysis. We develop a procedure in R around the Apriori algorithm to help in identifying lift maximising rules when the support covers a specified proportion. The procedure facilitates the choice of minimum parameters, eliminates redundancies, and organizes the resulting association rules into actionable formats. When applied to the US auto repair data, we find un-exploited bundling packages that can be added to the scheduled maintenance services of traditional marketing campaigns.
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