{"title":"Market Basket Analysis of a Health Food Store in Thailand","authors":"Kanokwan Singha, Parthana Parthanadee, Ajchara Kessuvan, Jirachai Buddhakulsomsiri","doi":"10.4018/ijkss.333617","DOIUrl":null,"url":null,"abstract":"This article presents a market basket analysis of a health food store in Thailand. The analysis identifies data attributes that frequently occur together in the dataset. Frequent occurrences of data attributes representing customer purchasing behaviors are extracted as association rules using the frequent pattern growth algorithm. The generated associations are evaluated using standard measures based on occurrence counts and an additional financial measure. Marketing strategies in the form of cross-selling pairs of specific products are then designed based on the data attributes appearing in the significant associations. The cross-selling products are offered at discounted prices and promoted in marketing campaigns. A break-even analysis is performed to estimate the required number of additional sales volumes from each marketing campaign to compensate for the discounted prices. The presented use case demonstrates the effectiveness of extending the market basket analysis to include a financial measure that can lead to practical marketing campaigns.","PeriodicalId":43448,"journal":{"name":"International Journal of Knowledge and Systems Science","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Knowledge and Systems Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijkss.333617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents a market basket analysis of a health food store in Thailand. The analysis identifies data attributes that frequently occur together in the dataset. Frequent occurrences of data attributes representing customer purchasing behaviors are extracted as association rules using the frequent pattern growth algorithm. The generated associations are evaluated using standard measures based on occurrence counts and an additional financial measure. Marketing strategies in the form of cross-selling pairs of specific products are then designed based on the data attributes appearing in the significant associations. The cross-selling products are offered at discounted prices and promoted in marketing campaigns. A break-even analysis is performed to estimate the required number of additional sales volumes from each marketing campaign to compensate for the discounted prices. The presented use case demonstrates the effectiveness of extending the market basket analysis to include a financial measure that can lead to practical marketing campaigns.
期刊介绍:
The mission of the International Journal of Knowledge and Systems Science (IJKSS) is to promote the development of knowledge science and systems science as well as the collaboration between the two sciences among academics and professionals from various disciplines around the world. IJKSS establishes knowledge and systems science as a vigorous academic discipline in universities. Targeting academicians, professors, students, practitioners, and field specialists, this journal covers the development of new paradigms in the understanding and modeling of human knowledge process from mathematical, technical, social, psychological, and philosophical frameworks. The International Journal of Knowledge and Systems Science was originally launched by the International Society of Knowledge and Systems Science, which was initiated in 2000 in Japan and founded by Prof. Y. Nakamori, Professor Z. T. Wang and Professor J. Gu in 2003 in Guangzhou. Professor Z. T. Wang was its Founding Editor.