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Fynd's Remarkable 129% Increase in Retention Through Predictive Segmentation
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
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。
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。
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
数量效益
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