<![CDATA[This study aims to analyze the implementation of business intelligence in understanding consumer behavior. Research data were collected through observation, interviews, and documentation, then processed using clustering techniques based on the K-Means algorithm and visualized through an analytics dashboard using Microsoft Power Business Intelligence. The research method employed is Research and Development (R&D) with the 4D model (Define, Design, Develop, Disseminate). This study integrates customer relationship management and machine learning as tools to manage, analyze, and visualize consumer behavior data. The results indicate that the application of business intelligence can group consumers into eight clusters based on behavioral patterns and transaction characteristics. The resulting analytics dashboard assists property management in making strategic decisions more efficiently. Furthermore, the use of business intelligence has been proven to enhance effectiveness in understanding consumer preferences, optimizing data management, and supporting marketing strategies. This study recommends implementing data-driven technology to increase the company’s competitiveness amid increasingly intense business competition.]]>
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