营收团队的 AI 队友
2 分•作者: davismartens•10 个月前
根据我的经验，优秀的营收团队和表现不佳的团队之间的差距一直都很大，对于那些做得好的团队来说，这是一个巨大的优势。这通常取决于他们与客户保持联系的持续性。在正确的时间进行跟进，在问题升级之前发现问题，或者仅仅是确保不放过任何机会。但大多数团队没有时间和纪律来做到这一点。
这就是促使我开始构建 https://chuff.co 的原因。它允许你用自然语言创建代理，帮助进行外展、跟进、支持和客户管理。
代理可以使用电子邮件、API 和网络搜索等工具来查找信息或采取行动。他们还有一个小的内部数据库来跟踪人员和公司，该数据库与你已经使用的任何工具并存。
在与创始人及营收团队交流时，我看到了一些有趣的用例，例如：一个代理检查 Shopify 中的订单状态，并在客户发邮件时起草更新；另一个代理跟踪 Stripe 中的发票状态，并跟进逾期付款；或者同步收件箱并要求代理建议重新联系谁以及撰写跟进邮件。
目前还处于早期阶段。很想听听其他正在研究这个问题或思考在面向客户的工作流程中使用 AI 的人的想法。
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In my experience the difference between good and bad revenue teams has always been huge and a massive advantage for those that get it right. It often comes down to how consistently they stay in touch with customers. Following up at the right time, surfacing issues before they escalate, or just making sure no opportunity slips through. But most teams don’t have the time or discipline to do this.<p>That’s what led me to start building https://chuff.co. It lets you create agents in natural language that help with outreach, follow-ups, support, and account management.<p>Agents can use tools like email, APIs, and web search to look things up or take action. They also have a small internal database to keep track of people and companies, which sits alongside whatever tools you already use.<p>Speaking to founders and revenue teams, I’ve seen some interesting use cases, for example: an agent that checks order status in Shopify and drafts updates when a customer emails in, another that tracks invoice status in Stripe and follows up on overdue payments or syncing an inbox and asking an agent to suggest who to re-engage and write follow-ups.<p>Still early. Would be curious to hear from others working on this problem or thinking about AI in customer-facing workflows.