<![CDATA[This study examines the problem of inconsistent sales target achievement faced by a motorcycle dealer in Indonesia, where sales targets were achieved in only a limited number of months. One of the main causes identified is the absence of clear customer segmentation, which leads to undifferentiated sales strategies and inefficient allocation of sales resources. This study aims to identify distinct customer segments based on transaction-based purchasing behavior and to demonstrate how these segments can be utilized to formulate more targeted sales strategies. A quantitative case study approach was employed using the CRISP-DM framework and transaction data from 4,289 motorcycle sales recorded between January 2022 and October 2025. Customer segmentation was conducted using the K-Modes clustering algorithm based on categorical transaction attributes, resulting in three distinct customer segments with different purchasing characteristics. The findings show that each segment exhibits unique behavioral and economic profiles, requiring differentiated sales approaches rather than a uniform strategy. Based on the segmentation results, this study proposes segment-specific sales strategies that support more focused resource allocation and improved sales effectiveness. The results highlight the importance of transaction-based customer segmentation as a practical decision-support tool for enhancing sales performance in motorcycle retail.]]>
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