MoEngage > 实例探究 > Fynd 如何使用预测细分将保留率提高 129%

Fynd 如何使用预测细分将保留率提高 129%

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技术
  • 分析与建模 - 预测分析
  • 网络安全和隐私 - 身份认证管理
适用行业
  • 消费品
  • 零售
适用功能
  • 采购
  • 销售与市场营销
用例
  • 库存管理
  • 零售店自动化
关于客户
Fynd 是印度最大的零售企业全渠道平台。他们为零售商提供商店管理门户,为消费者提供市场。他们的目标受众包括 18-35 岁年龄段的交易猎手,其中一部分 18-25 岁的人寻求更高的折扣。
挑战
Fynd 面临的挑战是,只有 2% 的客户在注册后 8 周内返回该应用。低保留率影响了他们的收入指标,并且存在客户流失的风险。
解决方案
Fynd 实施了 MoEngage Predictions,这是一种预测细分工具,可以识别对营销传播做出积极反应的客户,并剔除那些做出负面反应的客户。该工具根据转化、流失、休眠、添加产品和活动有效性等因素创建细分。这使得 Fynd 能够向每个客户发送有针对性的相关电子邮件。
运营影响
  • The use of MoEngage Predictions allowed Fynd to significantly improve their customer retention rates by optimizing their email marketing strategy. By segmenting their audience based on predicted behaviors, they were able to target their communications more effectively, resulting in a more engaged and responsive customer base. This approach not only increased the number of customers returning to the app but also improved the relevance of their communications, reducing the risk of customer churn due to irrelevant emails. The insights-led engagement strategy enabled Fynd to create more delightful experiences for their customers, standing out in a competitive market and driving growth.

数量效益
  • Retention from signups to app open within an 8-week period increased 129%, from 2.29% to 5.24%

  • The email base increased from 15,000 to 25,000 customers, a 66% increase

  • Email open rates doubled to 6-8%

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