Data Driven Approach to Analyze Customer Buying Behavior on Milkyway Cookies

Currently, bundling has become a popular strategy in the business world, where two or more products are sold together at a lower price compared to purchasing them separately. This strategy is widely used because it can attract customers, increase purchase value, and encourage customer loyalty. The main objective of this study is to identify the most preferred types of products among consumers so that the bundling packages created align with the majority’s preferences. To achieve this goal, the study employs data analysis using the RapidMiner application, which applies the data mining concept and apriori algorithm. This approach is used to identify consumer purchasing patterns, discover relationships between frequently purchased products, and optimize sales strategies. This research is to give advantages for business, especially in increasing and boosting sales volume by focusing on selling bundling packages. The result of this research is a strong correlation between consumers who purchase CNY hampers and those who buy Xmas hampers. Furthermore, customers who purchase the Valentine package usually also buy sugar cookies (M) and sugar cookies in a jar. Moreover, customers who buy sugar cookies in a jar and cookies dip intend to also purchase Xmas hampers and CNY hampers. These findings provide a framework for similar effectiveness of bundling strategies in FnB industry.