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市场调查报告书
商品编码
1670413
零售业巨量资料分析市场规模、份额和成长分析(按组件、部署、组织规模、应用和地区)- 产业预测 2025-2032Big 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 |
2023 年全球零售巨量资料分析市场规模价值为 52.6 亿美元,预计将从 2024 年的 63.8 亿美元成长到 2032 年的 296.8 亿美元,预测期内(2025-2032 年)的复合年增长率为 21.2%。
预测分析正在改变零售格局,它使企业能够利用历史资料来预测由于不断变化的消费行为和市场趋势而导致的销售成长。这项积极主动的策略将使零售商保持竞争力并在全球巨量资料分析领域占据相当大的市场占有率。无论是加强促销策略、促进交叉销售或培养客户关係,预测分析在提高盈利方面都发挥关键作用。线上和线下零售商越来越多地采用资料主导的方法来了解消费者的购买模式、根据偏好自订产品并改善行销倡议。儘管资料整合方面存在潜在挑战(可以透过系统管治来应对),但整合製造系统 (IPS)、自助结帐自动化和机器人等创新技术仍在进一步推动市场的发展。
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.