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Princess Polly Leverages Modern Data Stack for Enhanced Retail Analytics
技术
- 功能应用 - 库存管理系统
适用行业
- 电子商务
- 零售
适用功能
- 采购
- 仓库和库存管理
用例
- 拣选/分拣/定位
- 时间敏感网络
服务
- 系统集成
挑战
澳大利亚时尚精品店波莉公主 (Princess Polly) 在不确定的时期面临着有效利用数据的挑战。该公司正在准备进军美国市场,需要支持内部部门做出明智的决策。业务分析主管阿南德·巴特 (Anand Bhatt) 的任务是构建能够快速有效地展示价值的分析基础设施。作为团队中的唯一成员,阿南德需要最大限度地利用自己的时间为业务创造价值,并尽量减少耗时的手动任务。重点关注的领域是现金流量分析,目的是了解哪些决策正在影响企业的利润,从而做出更有效的决策。
关于客户
Princess Polly 是一家澳大利亚时尚精品店,成立于 2010 年。公司始于澳大利亚黄金海岸的一间海滨公寓,现已发展到拥有 200 多人的团队,总部设在黄金海岸和洛杉矶。该公司是一家 100% 电子商务网站,最近在美国市场推出。 Anand Bhatt 于 2020 年 5 月加入这家时尚初创公司,担任业务分析主管,当时该公司在美国成立后不久。他的职责是提升公司数据的使用方式,尤其是在不确定的时期。
解决方案
阿南德决定使用他曾经使用过的工具 Fivetran 来构建分析基础设施。他需要一个完善的 Shopify 连接器,该连接器可以支持公司的澳大利亚和美国 Shopify 帐户,并将两个帐户的数据结合起来进行分析。他还需要一个连接器将数据从 PR 系统传输到数据仓库,并通过 Klaviyo 支持将所有 NPS 分数导入到他们的系统中。为其库存计划程序、退货数据池创建了一个 AWS Lambda 函数,使用 Fivetran 连接器进行摄取。经过两周的试用后,Anand 能够将 Shopify API 连接到 Fivetran,运行成功的测试,并开始历史数据同步。他还加入了 Mode Analytics,让团队能够访问开始填充的数据集。
运营影响
数量效益
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