使用购物篮分析识别客户购买模式

K. Rakhmanaliyeva
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引用次数: 1

摘要

市场购物篮分析(Market Basket Analysis, MBA)是一种发现客户购买的产品对之间关联强度的方法,可以确定共现模式。MBA的主要目的是确定客户的购买行为并预测下一次购买。它可以帮助公司增加交叉销售。为了生成关联规则,Apriori算法使用频繁购买的商品集。它基于一个经常购买的物品的子集也是一个经常购买的物品的想法。如果经常购买的项集的支持值超过最小阈值,则选择该项集。本文观察了实现MBA的优点、应用于该技术的算法以及识别客户购买模式的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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