Application of K-Means algorithm for market segmentation (Case study: Lily’s cake Pontianak)

Abstract

In business, effective customer preference and segmentation are essential for decision making. Since data, especially data sales, is a crucial indicator. Data mining is needed to help companies process data into useful resources. Therefore, the author Recommends grouping several attributes from Lily’s cake sales data using the K-Means algorithm for clustering, a data mining approach, to determine client preferences during significant holidays. 599 data points from Christmas, Chinese New Year, and Eid al-Fitr sales from 2023 to 2024 will be handled, even though the research participants have never processed and evaluated data before. Using four clusters, the study aims to ascertain the K-Means method’s validity for clustering. The findings of this study enhance Lily’s cake capacity to connect with various customer segments by allowing them to better customize their product offers to suit customer preferences.