Enhancing Retail Supermarket Financial Performance Through Market Basket Analytics Using Apriori Algorithm in Indonesia Market Case

Abstract

Market Basket Analysis is a powerful technique in data mining and retail analytics that explores associations and patterns among items frequently purchased together by consumers. This technique reveals insights into consumer purchasing behaviour and facilitates the creation of compelling product bundles. This study identifies five distinct product bundling strategies tailored to diverse consumer personas prevalent in the Indonesian market, such as "Health enthusiast", "Exotic Flavor Explorer", "Food Enthusiast", "Fitness Freak", and "Budget-conscious Home Cook". These product bundling strategies leverage market basket analysis to enhance the shopping experience, meeting Indonesian consumers' diverse preferences and lifestyles in the retail supermarket landscape. The analysis provides a basis for effective promotional campaigns and personalized marketing efforts. By recognizing associations between products, supermarkets in Indonesia can design targeted promotions, encouraging customers to explore complementary items and potentially increase their overall spending.