Provectus > 实例探究 > 机器学习驱动的潜在客户评分:提高 Carson Group 的营销效率

机器学习驱动的潜在客户评分:提高 Carson Group 的营销效率

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技术
  • 分析与建模 - 机器学习
  • 应用基础设施与中间件 - 事件驱动型应用
适用行业
  • 教育
  • 设备与机械
适用功能
  • 产品研发
  • 销售与市场营销
用例
  • 预测性维护
  • 虚拟培训
服务
  • 数据科学服务
  • 培训
关于客户
卡森集团控股有限责任公司是一个顾问生态系统,提供顾问辅导计划、流程优化开发和投资策略等服务。他们希望利用人工智能/机器学习来优化营销工作并帮助客户更有效地获取新客户。
挑战
卡森集团控股有限责任公司希望加大营销力度,帮助其投资顾问客户更有效地获取新客户。他们决定采用 AI/ML 并实施机器学习模型来对从 Salesforce 收到的销售线索进行评分。
解决方案
Provectus 开发了一种用于线索评分的机器学习模型,从数据发现和评估开始。他们从头开始构建模型,包括 EDA、特征工程以及训练和推理管道的开发。该模型旨在处理新数据并生成预测。 Provectus 为每个开发阶段提供了文档。
运营影响
  • The Provectus Data and ML Engineering teams managed to deliver the lead scoring model within five weeks. Carson Group was quick to adopt the solution and take advantage of the results of the ML work in a matter of days. The delivered ML lead scoring solution took data from Salesforce, processed and analyzed it, and delivered the predictions to the sales and marketing professionals, making it easy for them to use the lead scores in their work. The ability to see the “potential to convert” score next to every lead enabled Carson to quickly look up promising clients, massively reducing the effort and time for conversion. This not only meant more efficient conversions for Carson’s clients, but also improved customer satisfaction, significant cost reduction, and better flexibility and scalability of the Carson Group business as a whole.

数量效益
  • Highly accurate and precise ML model delivered in 5 weeks

  • Model accuracy of 96% with actual conversions predicted from new data hitting the eight-out-of-10 mark (recall of 88%, precision of 67%)

  • Significant reductions in operations costs for Carson’s BUs and clients

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