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Automating Customer Support: A Case Study on Ada's Integration with Square
适用行业
- 服装
- 电信
用例
- 需求计划与预测
- 时间敏感网络
挑战
Square 是一家数字支付公司,在提供高效和个性化的客户支持方面面临着挑战。该公司需要一个可以作为全球客户成功的第一个联系点的解决方案,提供个性化的自助服务,对卖家问题和产品问题进行分类,并在必要时将卖家路由到理想的联系渠道。目标是减少客户的工作量和支持需求,同时提高客户成功的效率和影响力。该公司还希望通过利用卖家资料数据来显示最佳支持路径并减少客户挫败感,从而优化支持渠道。此外,Square 旨在通过提供更广泛的背景信息来提高处理常见问题时的辩护人效率,从而减少卖家的工作量并提高辩护人效率。
关于客户
本案例研究中的客户是 Square,这是一家数字支付公司,提供一系列商业服务、支付和销售点 (POS) 解决方案。 Square 的服务包括支付、硬件和软件,使企业能够接受付款、跟踪销售和管理运营。 Square 的客户群多种多样,从小型企业到大型企业。该公司在全球运营,支持多种市场和语言。 Square 正在寻求一种解决方案来提高客户支持的效率和个性化,减少客户的工作量和支持需求,并提高客户成功团队的效率和影响力。
解决方案
Square 集成了 Ada(一个人工智能驱动的客户服务平台),以实现客户支持的自动化。 Ada 旨在提供个性化的自助服务,对卖家问题和产品问题进行分类,并在必要时将卖家引导至理想的联系渠道。通过使用卖家资料和客户旅程数据,Ada 可以识别卖家的意图并缩小潜在解决方案的范围。 Ada 还能够检测客户特定信息,例如设备类型、浏览器或操作系统,以简化技术故障排除。此外,Ada 通过利用卖家资料数据显示最佳支持路径来优化支持渠道。 Ada 还通过将聊天记录作为创建案例时上下文的辩护人参考点,减少了卖方的工作量并提高了辩护人的效率。 Ada 旨在灵活且可扩展,适用于各种市场和用例,支持 100 多种语言,每天能够处理 1000 万多个对话。
运营影响
数量效益
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