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Google Cloud Platform > 实例探究 > 通过数据分析和自动化增强零售决策
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American Eagle Outfitters: Leveraging IoT for Enhanced Retail Decision-Making

技术
  • 分析与建模 - 大数据分析
  • 分析与建模 - 机器学习
适用行业
  • 消费品
  • 零售
适用功能
  • 质量保证
  • 销售与市场营销
用例
  • 实验自动化
  • 零售店自动化
服务
  • 云规划/设计/实施服务
  • 测试与认证
挑战
面对不断变化的客户偏好的压力比以往任何时候都更大,零售商在定价、促销、分类、技术和店内体验方面进行投资,不断进行创新。高管们需要对这些活动的投资回报率有信心,以证明此类相关支出的合理性。
关于客户
American Eagle Outfitters 是一家美国服装制造商和零售商,为全球消费者提供生活方式服装和配饰。他们拥有数据驱动的文化,并拥有从材料采购到销售和服务的自己的产品履行。
解决方案
American Eagle 选择 Google Cloud 和合作伙伴埃森哲来转变其数据分析方法并增强整个企业不同投资的决策。他们将数据迁移到单一系统中,彻底修改了数据仓库方法,并自动化数据科学,以实现更好的大规模结果。
运营影响
  • The implementation of Google Cloud and Accenture’s solutions has allowed American Eagle to leverage automated analytics to run in-store tests to optimize pricing, layout, and store location decisions, as well as to improve overall brand experiences based on more dynamic, timely customer insights. For instance, the company can quickly conduct in-store testing on promotions using control data from times before the promotion begins and real-time sales performance. This enables the retailer to understand whether a buy-one, get-one sale will be more profitable than a buy-one, get-one half-off sale, and exactly what types of customers each of them are attracting and how the program can be further fine-tuned. The experiment solution built on top of BigQuery opens the doors to testing products more efficiently before a season leading to more successful product placement in stores.
数量效益
  • Centralized data store for transaction, inventory, and web data that can be used for multiple solutions without compromising on performance
  • Accelerated solution development and deployment from concept to production in four months
  • Millions of dollars in savings through store testing and a cost-effective platform

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