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Leveraging Machine Learning to Analyze Impact of Promotional Campaigns on Sales
技术
- 分析与建模 - 机器学习
- 机器人 - 协作机器人
适用行业
- 设备与机械
- 零售
适用功能
- 采购
- 销售与市场营销
用例
- 实验自动化
- 时间敏感网络
服务
- 系统集成
- 培训
挑战
面临的挑战是分析促销活动对一家领先的中欧和东欧 (CEE) 食品公司销售额增长的影响。这些数据涉及海量的数据源、数百种不同的产品、承包商和承包商的客户、不同的促销类型、不同的促销周期、重叠的促销以及竞争对手的行为。
关于客户
该客户是一家领先的中欧和东欧 (CEE) 食品公司。他们针对果汁、果酱和泡菜等食品开展促销活动，并希望分析这些活动对销量增长的影响。
解决方案
该解决方案涉及使用机器学习模型来预测促销活动中给定产品的每日销售数量。该团队决定对每种产品、承包商甚至客户类型使用单独的模型，从而产生了 7000 多个单独的案例。他们使用指定工具 Neptune 进行实验跟踪、模型工件和可视化。 Neptune 帮助他们组织和跟踪项目的元数据、比较多个促销结果，并运行超过 120k 次实验，而不会出现存储不足和磁盘故障。
运营影响
数量效益
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