费城 76 人队如何利用 DataRobot 的机器学习赢得场外胜利
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- DataRobot Enterprise AI platform
技术栈
- Machine Learning
- Predictive Modeling
- Data Analytics
实施规模
- Enterprise-wide Deployment
影响指标
- Revenue Growth
- Customer Satisfaction
技术
- 分析与建模 - 预测分析
- 分析与建模 - 机器学习
适用功能
- 销售与市场营销
用例
- 补货预测
服务
- 数据科学服务
关于客户
费城 76 人队是美国职业篮球联赛 (NBA) 的一支职业篮球队。球队由哈里斯布利策体育娱乐公司 (HBSE) 所有，该公司还拥有国家冰球联盟的新泽西魔鬼队以及其他体育和娱乐资产。76 人队被认为是 NBA 中一支冉冉升起的强队，也是费城和世界各地球迷中最受欢迎的球队之一。该组织以高度重视数据分析而闻名，利用数据为各个层面的决策过程提供信息。76 人队的分析团队一直在寻找提高工作效率的方法，并使其数据驱动的流程更具活力。
挑战
费城 76 人队是 NBA 的一支职业篮球队，也是新一波利用数据分析来优化场上表现和业务运营的体育特许经营球队之一。该组织非常注重使用数据来指导各个层面的决策过程。76 人队分析团队面临的主要挑战之一是提高季票续订流程的效率。该团队一直在使用数据科学和简单的建模技术，但缺乏一种能够在收集更多数据时进行调整和学习的动态机器学习工具。这意味着该团队必须在休赛期做大量工作来制作静态模型。目标是将续订流程从一年一次的活动转变为全年的保留流程。
解决方案
为了应对这一挑战，76ers 分析团队求助于 DataRobot 的企业 AI 平台来改进其季票续订的建模流程。该平台允许团队构建动态、预测性的机器学习模型，可以全年跟踪、测量和分析数据。这使团队能够识别风险账户和对续订影响最大的因素。这些模型还帮助销售续订团队优化其流程，优先安排时间并更加认真地关注高风险账户。展望未来，76ers 分析团队计划将机器学习和预测模型的使用扩展到业务的其他部分，例如提高潜在客户评分和向粉丝提供更好的优惠。他们还计划扩大他们的工作范围，并将其应用于 Harris Blitzer Sports & Entertainment 旗下的其他体育特许经营权。
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