The Implementation of the apriori algorithm to increase sales of clothing stores based on purchase patterns

Abstract

In the growing digital era, retail industries face significant challenges and
opportunities. Clothing stores, as one type of retail industry, need to adapt to
changes in consumer behavior that are increasingly complex. With the
increasing variety of choices and easy access to information, understanding
customer purchasing patterns is key to gaining a competitive advantage.
Purchasing patterns reflect consumer preferences, not only that but can also
reveal something hidden that if analyzed properly, can be utilized for a more
effective marketing strategy. By applying a data-driven approach, it is hoped
that clothing stores can formulate more targeted marketing strategies, improve
customer satisfaction, and ultimately, drive sustainable sales growth. This
research approach is exploratory quantitative, which aims to find customer
purchase patterns from clothing store transaction data using the Apriori
algorithm. The results of data exploration are used to develop data-based sales
strategies.