{"title":"使用购物篮分析识别客户购买模式","authors":"K. Rakhmanaliyeva","doi":"10.55452/1998-6688-2021-18-3-95-101","DOIUrl":null,"url":null,"abstract":"Market Basket Analysis (MBA) is an approach that finds the strength of association between pairs of products that customers buy and can determine patterns of co-occurrence. The main aim of MBA is to determine customer buying behavior and predict next purchase. It can help companies to increase cross-selling.To generate association rules, the Apriori algorithm employs frequently purchased item-sets. It is based on the idea that a frequently purchased item’s subset is also a frequently purchased item. If the support value of a frequently purchased item-set exceeds a minimum threshold, the item-set is chosen. This paper observes the advantages of implementing MBA, algorithms that applies in this technique and ways to identify customer buying patterns.","PeriodicalId":447639,"journal":{"name":"Herald of the Kazakh-British technical university","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"IDENTIFYING CUSTOMER BUYING PATTERNS USING MARKET BASKET ANALYSIS\",\"authors\":\"K. Rakhmanaliyeva\",\"doi\":\"10.55452/1998-6688-2021-18-3-95-101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Market Basket Analysis (MBA) is an approach that finds the strength of association between pairs of products that customers buy and can determine patterns of co-occurrence. The main aim of MBA is to determine customer buying behavior and predict next purchase. It can help companies to increase cross-selling.To generate association rules, the Apriori algorithm employs frequently purchased item-sets. It is based on the idea that a frequently purchased item’s subset is also a frequently purchased item. If the support value of a frequently purchased item-set exceeds a minimum threshold, the item-set is chosen. This paper observes the advantages of implementing MBA, algorithms that applies in this technique and ways to identify customer buying patterns.\",\"PeriodicalId\":447639,\"journal\":{\"name\":\"Herald of the Kazakh-British technical university\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Herald of the Kazakh-British technical university\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.55452/1998-6688-2021-18-3-95-101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Herald of the Kazakh-British technical university","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55452/1998-6688-2021-18-3-95-101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IDENTIFYING CUSTOMER BUYING PATTERNS USING MARKET BASKET ANALYSIS
Market Basket Analysis (MBA) is an approach that finds the strength of association between pairs of products that customers buy and can determine patterns of co-occurrence. The main aim of MBA is to determine customer buying behavior and predict next purchase. It can help companies to increase cross-selling.To generate association rules, the Apriori algorithm employs frequently purchased item-sets. It is based on the idea that a frequently purchased item’s subset is also a frequently purchased item. If the support value of a frequently purchased item-set exceeds a minimum threshold, the item-set is chosen. This paper observes the advantages of implementing MBA, algorithms that applies in this technique and ways to identify customer buying patterns.