Mapping the Wuling vehicle market with K-Means Clustering: An effective digital marketing strategy - Giri Teguh Ardiansyah; Muhammad Satir Hasibuan; Suhari Santosa; Jerry Heikal (Universitas Ahmad Dahlan, 2024)
This study focuses on Indonesia’s automotive industry sector, which is currently experiencing growth, particularly in terms of Wuling's contribution to the economy through sales. The aim is to identify customer clusters for Wuling vehicle and the marketing mix strategy after the most dominant customer cluster for Wuling vehicle. The research method used was a quantitative survey, which involved collecting data from 111 potential Wuling customer using purposive sampling and data collection through questionnaires. The analysis included an F-Test to examine the differences between clusters. The results show that the clustering of Wuling customer using the K-Means Clustering method successfully divided them into three different clusters, namely Perfectionist, Easy Going, and Beginner, with the Easy Going being the most dominant. Therefore, it is necessary to adjust marketing strategies to focus more on the needs and preferences of the Easy Going, including optimizing the use of promotion channels that have been proven effective, such as direct marketing and sales websites. Thus, this study emphasizes the importance of applying the K-Means Clustering method in automotive market segmentation, providing valuable insights for Wuling to formulate more effective and relevant marketing strategies to meet the diverse needs of customer in a dynamic market.