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Fixed the voice mixing bug, then our own analytics started lying to us

Quick follow up. Three days ago I posted here about a bug where outbound almost crossed two clients' voices before any prospect saw a single message. We fixed that fast, hard separation at the data layer. What broke next was harder to catch because nothing looked wrong at first. The graph that tracks every piece from views to conversations to sales started crediting one client's closed deal to a different client's campaign. Both businesses happened to run outbound in the same ten minute win

五维评分

付费意愿
72
需求真实度
62
个人可落地
55
竞争空间
35
新鲜度
68

AI 分析

痛点:多客户外呼/营销SaaS中,多租户数据、语音和时间窗口隔离不彻底,导致归因看板把A客户的成交错误记到B客户,老板无法信任唯一的效果数据。

目标用户:为多个客户做外呼和私域转化的营销代理机构、小型SaaS/CRM工具团队。

证据:We're at 3 paying businesses running on this right now, plus our own company. ... the graph that tracks every piece from views to conversations to sales started crediting one client's closed deal to a different client's campaign. ... that graph is the only way a business owner knows what actually worked.

变现:按月订阅的按客户隔离的外呼归因分析SaaS;或作为现有CRM/外呼工具的付费插件,按客户数/坐席数收费。

MVP:2周内做出最小版:接入一个外呼/私信渠道(如LinkedIn或邮件),按客户维度强制隔离队列时间戳和事件ID,提供从内容→对话→成交的归因看板,并用锁机制防止跨租户窗口重叠。

竞品:Smartlead、Instantly、lemlist、HubSpot、Salesforce、Segment

摘要:发帖人做的是多客户外呼归因SaaS,修复语音串线后又发现跨客户归因串单,原因是队列时间戳重叠。已加客户级锁,并称目前有3家付费企业客户加自己公司在用,11月3日开放注册。