Google Cloud Platform > 实例探究 > 增强购物体验:bonprix 利用 Google Cloud 实现可扩展 ML 和 AI 自动化的旅程

增强购物体验:bonprix 利用 Google Cloud 实现可扩展 ML 和 AI 自动化的旅程

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技术
  • 分析与建模 - 机器学习
  • 功能应用 - 仓库管理系统 (WMS)
适用行业
  • 消费品
  • 设备与机械
适用功能
  • 产品研发
  • 仓库和库存管理
用例
  • 预测性维护
  • 时间敏感网络
服务
  • 云规划/设计/实施服务
  • 数据科学服务
关于客户
bonprix 是一家国际在线时尚和家居用品零售商,业务遍及欧洲、俄罗斯和北美。他们拥有强大的内部开发和数据工程团队。
挑战
bonprix 拥有过时的本地数据仓库设置,随着数据量的增长,问题变得越来越严重。他们希望增强机器学习和人工智能能力,并将所有数据集中在一处。
解决方案
在 Google Cloud 合作伙伴 KPMG 和 Aliz 的帮助下,bonprix 迁移到了 Google Cloud。他们现在使用 Google Cloud 的数据仓库 BigQuery 来存储和分析结构化和非结构化数据。迁移在 12 个月内按时、按预算完成。
运营影响
  • The migration to Google Cloud has allowed bonprix to shift its IT team's focus from infrastructure management to service creation. The company has been able to test and deploy new machine learning models more quickly and efficiently. It has also been able to build up its machine learning and artificial intelligence capabilities, creating a recommendation engine that recommends similar products to customers based on what they click on, a fraud-detection system, and a programmatic advertising system that forecasts the return on investment for different advertising spots. The company is also developing other machine learning-based use cases. With Google Cloud taking over the management of much of bonprix's infrastructure, the company's developers and engineers can now focus on creating new data-based products and getting them to market faster.

数量效益
  • Migration to Google Cloud completed in 12 months, on time, and on budget

  • Significantly reduces time to develop new ML models to just two weeks

  • 40% to 50% more cost-effective than on-premises solution

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