下载PDF
Faster, More Accurate Customer Segmentation
技术
- 分析与建模 - 预测分析
- 分析与建模 - 大数据分析
适用功能
- 销售与市场营销
用例
- 预测性维护
服务
- 数据科学服务
挑战
Dentsu Aegis 是一家媒体购买公司，它使用有针对性的细分来分配广告商在各种媒体上的广告活动预算。在向潜在客户推销其服务时，销售人员会推荐最适合通过特定广告活动定位的特定细分市场，以最大化回报。在完成销售后，团队需要能够兑现这些承诺，并通过有效的细分真正实现回报最大化。然而，该部门很难快速向销售团队提供细分建议。团队建立了一个数据湖来从多个来源收集数据，但实际使用这些数据意味着每次都要开始编写新代码（Python、Spark 或 SQL）的痛苦过程。每次他们有一个项目时，团队成员都必须编写查询、获取结果、使用另一个工具分析这些结果，并编写更多代码来重新处理和使用数据。由于没有简单的方法来复制过去的工作，每个项目都需要他们从头开始他们的流程，无论两个潜在客户或客户的用例有多么相似。
关于客户
电通安吉斯集团有限公司是一家跨国媒体和数字营销传播公司，总部位于英国伦敦。它是日本广告和公关公司电通的全资子公司。其主要服务是通过数字创意执行、媒体规划和购买、体育营销和内容创作、品牌跟踪和营销分析来制定传播策略。电通安吉斯是一家媒体购买公司，它使用有针对性的细分来分配广告商的预算，用于各种媒体（电视、数字、搜索等）的广告活动。
解决方案
Dentsu Aegis 选择 Dataiku Data Science Studio (DSS) 作为一体化工具，为数据部门带来巨大的效率提升。现在，借助 Dataiku，该部门可以快速为客户细分的新方法设计原型。如果细分效果良好，得益于 Dataiku 的协作环境，整个团队可以轻松地反复重复使用这些模型。他们不再需要为类似的项目编写单独的查询。相反，团队只需为直接在 Spark 上的 Scala 中运行的代码专用管道设计原型。这些效率提升使团队可以腾出更多时间设计创新的新方法来细分客户并为公司提供价值。例如，他们使用 Dataiku 进行预测机器学习，以找到共同特征和弱信号。这些弱信号使他们能够定义会对某些广告做出反应（或不做出反应）的特定受众。
运营影响
数量效益
相关案例.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Asset Management and Predictive Maintenance
The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.
