Real-time data analytics in retail: A review of USA and global practices

Mustafa Ayobami Raji, H. B. Olodo, Timothy Tolulope Oke, Wilhelmina Afua Addy, Onyeka Chrisanctus Ofodile, A. Oyewole
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Abstract

Real-time data analytics has emerged as a pivotal tool in the retail sector, revolutionizing decision-making processes and operational strategies. This study delves into the extensive landscape of real-time data analytics in retail, offering a comprehensive review of practices both in the USA and on a global scale. In the United States, retail giants have harnessed real-time data analytics to gain unprecedented insights into consumer behavior, preferences, and market trends. From personalized marketing campaigns to dynamic pricing strategies, retailers leverage real-time analytics to optimize inventory management and enhance the overall customer experience. The integration of technologies like RFID, IoT devices, and advanced analytics platforms has facilitated the seamless flow of data, enabling retailers to respond swiftly to changing market dynamics. On a global scale, diverse retail markets have embraced real-time data analytics to stay competitive in an ever-evolving landscape. Cross-border e-commerce and the proliferation of online marketplaces have intensified the need for real-time insights into global consumer trends. Retailers worldwide are adopting predictive analytics to forecast demand, reduce stockouts, and streamline supply chain operations. Moreover, the integration of artificial intelligence and machine learning algorithms enhances the ability to analyze vast datasets, uncovering hidden patterns and predicting future market trends. Challenges such as data privacy concerns, integration complexities, and the need for skilled professionals are acknowledged in this review. Despite these challenges, the transformative impact of real-time data analytics on the retail sector is undeniable. As technology continues to advance, the synergy between real-time data analytics and retail practices is expected to deepen, fostering innovation and reshaping the industry's landscape. This study provides a glimpse into the dynamic and evolving realm of real-time data analytics in retail, offering insights into the strategies employed by both the USA and global players to thrive in an era of rapid technological change.
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零售业的实时数据分析:美国和全球实践回顾
实时数据分析已成为零售业的重要工具,彻底改变了决策过程和运营战略。本研究深入探讨了实时数据分析在零售业中的广泛应用,对美国和全球范围内的实践进行了全面回顾。在美国,零售业巨头利用实时数据分析技术,对消费者行为、偏好和市场趋势获得了前所未有的洞察力。从个性化营销活动到动态定价策略,零售商利用实时分析来优化库存管理和提升整体客户体验。无线射频识别(RFID)、物联网设备和高级分析平台等技术的整合促进了数据的无缝流动,使零售商能够迅速应对不断变化的市场动态。在全球范围内,各种零售市场都采用了实时数据分析技术,以便在不断变化的环境中保持竞争力。跨境电子商务和在线市场的激增加剧了对实时洞察全球消费趋势的需求。全球零售商正在采用预测分析技术来预测需求、减少缺货并简化供应链运营。此外,人工智能和机器学习算法的整合提高了分析庞大数据集、发现隐藏模式和预测未来市场趋势的能力。数据隐私问题、集成的复杂性以及对熟练专业人员的需求等挑战在本综述中都有所提及。尽管存在这些挑战,但实时数据分析对零售业的变革性影响是不可否认的。随着技术的不断进步,实时数据分析与零售实践之间的协同作用有望进一步深化,从而促进创新并重塑行业格局。本研究报告让我们一窥零售业实时数据分析的动态和演变领域,深入了解美国和全球零售商在技术快速变化的时代为实现繁荣所采取的战略。
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