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Databricks > 实例探究 > 利用 Databricks Lakehouse 平台推动业务影响:AIR MILES 案例研究
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Leveraging IoT and Machine Learning to Enhance Customer Experience: A Case Study on AIR MILES Reward Program

技术
  • 分析与建模 - 机器学习
  • 传感器 - 环境传感器
适用行业
  • 消费品
  • 零售
适用功能
  • 产品研发
  • 销售与市场营销
用例
  • 零售店自动化
  • 盗窃检测
服务
  • 数据科学服务
挑战
AIR MILES 拥有传统的基础设施,难以提供客户的整体视图,阻碍了他们建立亲密联系以及提高保留率和客户终身价值的能力。他们还面临扩展数据能力和访问旧数据的挑战。
关于客户
AIR MILES 是一项联盟奖励计划,拥有近 1000 万个活跃收藏家帐户,通过在 300 多家零售商的日常购物获得奖励。他们通过网络创造了 700 亿美元的收入,并拥有来自收藏家和零售合作伙伴的数十亿条数据记录。
解决方案
AIR MILES 实施了 Databricks Lakehouse 平台,以实现基础设施现代化并统一数据。该平台使他们能够利用大量客户数据进行销售和营销、产品和优惠开发以及合作伙伴参与。它还支持客户细分、保留和生命周期价值分析。
运营影响
  • With the Databricks Lakehouse Platform, AIR MILES surpassed the initial goal of obtaining real-time data insights and fully integrated a data-first approach throughout the company. The platform's performance resulted in faster insights to the end users. They implemented a metrics catalog framework that allowed them to curate and manage all their business rules in one centralized location. This higher throughput accelerated the time-to-market of new insights and ML-powered solutions. Over 100 internal AIR MILES associates across departments and teams, plus additional users and data vendors, are now able to access data insights fed through BI tools. With over 23,000 collector attributes at their fingertips, their data science teams have developed over 250 ML models to hone personalization for business growth.
数量效益
  • Data pipeline development time reduced from 3-4 months to just 2 days
  • Access to over 30 years of historical data
  • Over 100 data pipelines delivering faster time-to-insights

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