The expansion of Indonesia's ride-hailing sector has been considerable, fueled by technological advancements and the widespread embrace of smartphones. Despite its swift growth, the industry faces difficulties concerning long-term viability, safety issues, and compliance with governmental regulations. Nevertheless, the integration of advanced technologies and strategic plans for service expansion into new regions presents significant opportunities. The competitive environment in Indonesia's ride-hailing market not only stimulates innovation but also shapes a lively and evolving market atmosphere. Originally designed for consumers, the ride-hailing sector has evolved into a versatile transportation solution for various business needs, including employee transportation and goods delivery. These services offer advantages for companies, such as enhanced operational efficiency and reduced logistics costs. Recognizing the diversity of the business market, segmentation becomes vital in comprehending customer needs. Through tailored marketing approaches, companies can deliver more pertinent solutions, boosting competitiveness and enlarging B2B market share. By using K-means clustering, it yields 5 clusters, namely cluster 1: Tech Innovators and Financial Players, cluster 2: Logistics Singular Focus, cluster 3: Logistics, Retail, and Automotive Synergy, cluster 4: Culinary, Logistics, and Travel Dynamics, cluster 5: Tech Titans, Healthcare Giants, and Financial Leaders. The analysis of user clusters on the B2B Ride Hailing Indonesia platform provides useful insights that guide strategic recommendations for improving service offerings, refining marketing strategies, and optimizing business operations. Targeting the millennial demographic through digital channels and influencers, examining marginal costs for high-traffic clusters to identify optimization opportunities, exploring expansion possibilities in clusters with growth potential, and tailoring business solutions for clusters with unique needs are among the recommendations. Keywords: K-means Clustering, Market Innovation, Market Share Expansion, Ride-Hailing Sector, Segmentation, Strategic Decisions.
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