Increasing Cross-Selling Retail Sales Using the Apriori Algorithm on A Groceries Dataset

Abstract

A company's sustainability is highly dependent on the role of consumers in conducting transactions. As it turns out, consumers have diverse behaviors and characteristics, so the ability to analyze consumer patterns or habits in transactions is needed. A similar situation also occurs in the retail business, which faces several problems in the sales process, such as stock scarcity, unsold products, and differences in product popularity and consumer demand. Therefore, it is necessary to analyze consumer habits in transactions. The association method with the Apriori algorithm has proven effective in analyzing consumer transaction habits in the retail business. The grocery dataset calculations show an average percentage of support values of 5% and a confidence value of 3%. Applying the association method with the Apriori algorithm can assist retail businesses in designing products and determining strategic steps to increase sales, such as providing discounts or promotions on certain products.