Perdhana, Rizkita Bagus
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Mendorong Pertumbuhan Pangsa Pasar B2B untuk Sektor Ride-Hailing Menggunakan Segmentasi Pasar Strategis Kamaratih F, Yositalida; Perdhana, Rizkita Bagus; Nugroho, Yusuf Wahyu; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 5 No 2 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v5i2.9609

Abstract

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.
Enhancing Customer Segmentation in Online Transportation Services: A Comprehensive Approach Using K-Means Clustering and RFM Model Perdhana, Rizkita Bagus; Heikal, Jerry
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 7 No 2 (2024): Sharia Economics
Publisher : Sharia Economics Department Universitas KH. Abdul Chalim, Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v7i2.4851

Abstract

In the rapidly evolving landscape of online transportation services, companies face complex challenges to maintain and expand their market positions. Understanding customer dynamics has become crucial for success, extending beyond mere acquisition to encompass retention. This study presents a comprehensive approach to customer segmentation in online transportation services using K-Means Clustering and the RFM Model. K-Means Clustering categorizes customers based on behavioral patterns, while the RFM Model provides a detailed insight into customer engagement in acquisition activities. The integration of these methodologies aims to enable companies to tailor services, enhance customer experiences, and formulate targeted marketing strategies. The analysis identifies 5 diverse customer groups: (1) Urban Luxury Commuters, (2) Non-Motorized Urban Users, (3) Tech-Savvy Urban Commuters, (4) Diverse Urban Commuters, and (5) Budget-Conscious Urban Commuters. Among these groups, the (2) Non-Motorized Urban Users group is the focus due to its high monetary value and the second-highest frequency level. Users in this cluster tend to transact frequently, indicating consistent and recent engagement with transportation services. Factors such as high transaction frequency and total transaction value underscore the importance of this cluster in generating overall revenue. Additionally, the research will consider additional factors such as user demographics, travel purposes, and promotional activities to further understand user behavior patterns in this cluster. The goal is to formulate targeted strategies to enhance user satisfaction, engagement, and potential revenue growth for transportation service providers. This study also introduces an RFM-based marketing program targeting different customer segments, such as (1) Platinum Membership, (2) Rush Hour Bonanza, (3) Bundle Extravaganza, (4) Revive and Thrive Offer, and (5) Back in the Saddle Campaign. Furthermore, the Refer-a-Friend Program encompasses all RFM segments, encouraging users to expand the network of online transportation service users. The seamless integration between customer segmentation and RFM-based initiatives has the potential to enhance customer retention, drive revenue growth, and improve operational efficiency, contributing significantly to adaptive business strategies in the dynamic online transportation services sector.