Implementation Of Data Mining On Cuctomer Purchasing Intentions For Retail Store Layout Optimization And Strategic Bundle Propostition

Abstract

It has been demonstrated that encouraging customers to make more trips across a grocery store leads to an increase in revenue due to an increase in the number of impulsive purchases. The research problem is to develop a design for the optimized layout of the grocery store that allocates product categories to store shelves to extend the total amount of time that customers spend shopping within the store. Market Basket Analysis, often known as MBA, is the approach used here. MBA is a data mining technique that investigates what customers are buying together. In this article, the Apriori Algorithm is used to perform an analysis of grocery transactional data to discover the relation between products and product categories. The findings are then used as a model in order to optimize the layout of grocery stores and make decisions regarding the selection of bundles.