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市場調査レポート
商品コード
1724858
車両アナリティクスの市場規模、シェア、成長分析、コンポーネント別、展開モデル別、用途別、最終用途別、地域別 - 産業予測 2025~2032年Vehicle Analytics Market Size, Share, and Growth Analysis, By Component (Software, Services), By Deployment Model (On-Premises, On-Demand), By Application, By End-use, By Region - Industry Forecast 2025-2032 |
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車両アナリティクスの市場規模、シェア、成長分析、コンポーネント別、展開モデル別、用途別、最終用途別、地域別 - 産業予測 2025~2032年 |
出版日: 2025年05月09日
発行: SkyQuest
ページ情報: 英文 196 Pages
納期: 3~5営業日
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車両アナリティクスの世界市場規模は、2023年に37億米ドルと評価され、2024年の46億5,000万米ドルから2032年には289億9,000万米ドルに成長し、予測期間(2025-2032年)のCAGRは25.7%で成長する見通しです。
世界の車両アナリティクス市場は、技術の進歩や効率性、コスト削減、安全性、規制遵守に対する需要の高まりによって、大きな成長を遂げようとしています。共有車両や自律走行車の台頭により、交通管理や保険などの業界がデータの活用による改善を模索しているため、強固な分析機能が必要とされています。テレマティクスやIoTデバイスから膨大な量のデータが得られるため、実用的な洞察を引き出すには高度なアナリティクスが必要となります。2024年のトヨタの未来的な電気自動車への取り組みに見られるように、車両アナリティクスは性能、安全性、ユーザーエクスペリエンスの向上に重要な役割を果たしており、将来の自動車イノベーションにおける重要性が強調されています。
Global Vehicle Analytics Market size was valued at USD 3.7 billion in 2023 and is poised to grow from USD 4.65 billion in 2024 to USD 28.99 billion by 2032, growing at a CAGR of 25.7% during the forecast period (2025-2032).
The global vehicle analytics market is set for significant growth driven by technological advancements and an increasing demand for efficiency, cost reduction, safety, and regulatory compliance. The rise of shared vehicle fleets and autonomous vehicles necessitates robust analytics capabilities, as industries like traffic management and insurance seek to leverage data for improvements. An influx of connected vehicles is expected to further fuel market interest, yielding vast amounts of data from telematics and IoT devices that require sophisticated analytics to extract actionable insights. Notably, as seen in 2024 with Toyota's futuristic electric vehicle initiatives, vehicle analytics plays a crucial role in enhancing performance, safety, and user experience, underscoring its importance in future automotive innovations.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Vehicle Analytics market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Vehicle Analytics Market Segments Analysis
Global Vehicle Analytics Market is segmented by Component, Deployment Model, Application, End-use and region. Based on Component, the market is segmented into Software and Services. Based on Deployment Model, the market is segmented into On-Premises and On-Demand. Based on Application, the market is segmented into Predictive Maintenance, Traffic Management, Safety & Security Management, Driver & User Behavior Analysis, Dealer Performance Analysis, Usage-Based Insurance and Others. Based on End-use, the market is segmented into Original Equipment Manufacturers (OEMs), Automotive Dealers, Fleet Owners, Regulatory Bodies, Insurers and Service Providers. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Vehicle Analytics Market
The Global Vehicle Analytics market is experiencing significant growth driven by the ongoing transformation within the automotive industry, fueled by the integration of artificial intelligence (AI) and the Internet of Things (IoT). AI-powered analytics enable accurate predictions regarding vehicle repair needs while optimizing fuel efficiency for better performance. Additionally, IoT sensors provide real-time data on vehicle performance and condition, greatly enhancing both customer and business experiences. This evolving landscape not only improves operational efficiency but also fosters a more innovative and responsive automotive sector, underscoring the critical role of advanced analytics in shaping the future of transportation.
Restraints in the Global Vehicle Analytics Market
The Global Vehicle Analytics market faces significant challenges due to the substantial initial financial investments required for cloud infrastructure, software, and hardware necessary to implement automotive analytics systems. Moreover, the elevated operating costs arise from the demand for substantial processing capabilities and real-time data analytics inherent in advanced AI-based solutions. Such financial barriers may deter small and medium-sized fleet operators from adopting these technologies, limiting their participation in price-sensitive market segments. This lack of accessibility could impede the growth potential of the market, as smaller players struggle to compete effectively in an increasingly data-driven automotive landscape.
Market Trends of the Global Vehicle Analytics Market
The Global Vehicle Analytics market is witnessing significant growth, primarily driven by the surge in connected and autonomous vehicles. The integration of advanced AI-powered insights facilitates real-time vehicle analytics, enhancing security protocols, optimizing route management, and improving vehicle-to-vehicle (V2V) communications. As manufacturers and fleet operators adopt cloud-based AI solutions and predictive analytics, they are increasingly able to transform intricate vehicle data into actionable insights, thus propelling the transition towards fully autonomous driving. This trend not only underscores the technological evolution in the automotive industry but also highlights the growing demand for data-driven decision-making in enhancing operational efficiency and safety standards.