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市場調査レポート
商品コード
1670413
小売業におけるビッグデータ分析市場規模、シェア、成長分析:コンポーネント別、展開別、組織規模別、用途別、地域別 - 産業予測 2025~2032年Big Data Analytics in Retail Market Size, Share, and Growth Analysis, By Component (Software, Service), By Deployment (On-Premise, Cloud), By Organization Size, By Applications, By Region - Industry Forecast 2025-2032 |
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小売業におけるビッグデータ分析市場規模、シェア、成長分析:コンポーネント別、展開別、組織規模別、用途別、地域別 - 産業予測 2025~2032年 |
出版日: 2025年02月28日
発行: SkyQuest
ページ情報: 英文 183 Pages
納期: 3~5営業日
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小売業におけるビッグデータ分析の世界市場規模は2023年に52億6,000万米ドルと評価され、2024年の63億8,000万米ドルから2032年には296億8,000万米ドルに成長し、予測期間中(2025年~2032年)のCAGRは21.2%で成長する見通しです。
予測分析は、企業が過去のデータを活用して、進化する消費者行動や市場動向による売上成長を予測できるようにすることで、小売業界の状況を一変させています。このプロアクティブな戦略により、小売企業は競争力を維持し、世界のビッグデータ分析分野で大きな市場シェアを獲得することができます。プロモーション戦略の強化、クロスセリングの促進、顧客関係の育成など、予測アナリティクスは収益性の向上に重要な役割を果たしています。オンライン・オフラインを問わず、小売業者は消費者の購買パターンを読み解き、商品を嗜好に合わせ、マーケティング施策を洗練させるために、データ主導の手法を採用する傾向が強まっています。統合生産システム(IPS)、セルフレジ自動化、ロボット工学などの革新的技術は、体系的なガバナンスによって管理できるデータ統合の潜在的課題にもかかわらず、市場をさらに前進させています。
Global Big Data Analytics in Retail Market size was valued at USD 5.26 billion in 2023 and is poised to grow from USD 6.38 billion in 2024 to USD 29.68 billion by 2032, growing at a CAGR of 21.2% during the forecast period (2025-2032).
Predictive analytics is revolutionizing the retail landscape by enabling businesses to leverage historical data to forecast sales growth driven by evolving consumer behaviors and market trends. This proactive strategy empowers retailers to maintain a competitive edge and capture significant market share within the global big data analytics sector. By enhancing promotional strategies, facilitating cross-selling, and nurturing customer relationships, predictive analytics plays a crucial role in driving profitability. Retailers, both online and offline, are increasingly adopting data-driven methodologies to decipher consumer buying patterns, aligning products with preferences, and refining marketing initiatives. Innovative technologies like Integrated Production Systems (IPS), self-checkout automation, and robotics are further propelling the market forward, despite potential data integration challenges that can be managed through systematic governance.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Big Data Analytics In Retail 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 Big Data Analytics In Retail Market Segments Analysis
Global Big Data Analytics in Retail Market is segmented by Component, Deployment, Organization Size, Applications and region. Based on Component, the market is segmented into Software and Service. Based on Deployment, the market is segmented into On-Premise and Cloud. Based on Organization Size, the market is segmented into Large Enterprises and SMEs. Based on Applications, the market is segmented into Sales and Marketing Analytics, Supply Chain Operations Management, Merchandising Analytics, Customer Analytics and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Big Data Analytics In Retail Market
The Global Big Data Analytics in Retail market is significantly driven by the transformative effects of e-commerce on traditional brick-and-mortar retailing, diminishing their dominance and highlighting the importance of data-driven strategies. A streamlined supply chain, which facilitates the efficient transition of products from suppliers to warehouses and ultimately to customers, is essential for any retail business. Big data analytics plays a pivotal role in this transformation by enabling real-time tracking of inventory and product movement, analyzing customer data to forecast purchasing trends, and even employing robotic systems for order fulfillment in expansive automated warehouses, ensuring operational efficiency and responsiveness to consumer needs.
Restraints in the Global Big Data Analytics In Retail Market
The Global Big Data Analytics in Retail market faces significant restraints primarily due to pressing security issues. Concerns surrounding fake data generation, the demand for real-time security measures, and the protection of customer data privacy are paramount. Additionally, vulnerabilities arise from remote data storage, inadequate identity governance, insufficient investments in system and network security, human errors, and the proliferation of connected devices and Internet of Things (IoT) applications. Addressing these challenges is crucial for organizations. Moreover, the rising frequency of data breaches and cyberattacks targeting customer information across various sectors poses a substantial threat to market growth.
Market Trends of the Global Big Data Analytics In Retail Market
The global Big Data analytics market in retail is experiencing significant growth, driven by the rise of edge computing solutions. With an unprecedented surge in the number of connected IoT devices-projected by the International Data Corporation (IDC) to reach 152,200 connections per minute by 2025-retailers are increasingly leveraging Machine Learning (ML) and Artificial Intelligence (AI) to analyze data in real-time. This shift towards edge computing enables faster data processing and insights generation, enhancing customer experiences and operational efficiency. As a result, demand for advanced Big Data analytics tools is set to rise, transforming the retail landscape into a data-driven ecosystem.