Market Basket Analysis for Sales Transaction in Shopping Stores

Abstract

Market Basket Analysis (MBA) system is a widely used technique among marketers, especially for undirected data mining analysis. MBA is also known as product association analysis and the outcome of this analysis is called association rules. The outcome can be used to schedule marketing or advertising strategies and design catalogs for different shop layouts. Discovering the pattern from the customer's buying habits in the shopping stores was collected in their buying transaction. This study aims to compare the item purchased by the respondents between Store A and Store B and to find out the most potential products that customers have bought along with a specific category of products. Convenience non-probability sampling was involved with structured questionnaires of items in store was collected to analyze data. Association analysis was used by analyzing the result from support, confidence, and lift. The findings showed that there are 13 interesting rules of association revealed in this study. Moreover, the result also found that most products that were purchased together are tissues, condiments, instant food, cooking oil, meat, biscuits, dry goods, beverages, and cleaning products.