Market basket analysis is a data processing methodology for discovering relationships between different items. The primary goal of market basket analysis in retail is to provide information to the distributor about a customer’s purchasing habits, which can aid the distributor in making the best choices. Market basket analysis can be performed using a variety of algorithms. This paper compares two popular market basket analysis techniques, to determine which approach is optimal for rule generation and visualization on a common dataset. The results can be used as a guide for cross-selling, creating promotions, and determining the best location for products in the store to boost sales. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.