我们发现了什么
Show HN:Revliu——从获客到收入的多触点归因。如今,Revliu 可跟踪获客来源、回访访客、会话、触点和收入。
- 来源:Hacker News(发现于 2026-09-10)
- 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
- 商业模式:Subscription SaaS
- 主题:营销与增长
- 初筛评分:24.2/100 · 收录 1 次
证据,比故事更重要。
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中文辅助译文(全文)
我是一名创始人,刚刚打造了 Revliu。在开发过多款产品之后,我一直想了解我的客户究竟是如何找到我的。是哪个营销活动带来了他们,他们来自哪个来源,以及他们的完整旅程是怎样的。市面上已经有相关的工具,但我反复遇到的一个问题是,它们往往只停留在首次触点或末次触点。因此,我把 Revliu 围绕多触点归因和完整的客户旅程来构建。一旦有人访问你的网站,Revliu 就会为他们分配一个匿名 ID,并开始追踪他们的旅程。一旦他们注册,这个旅程就可以与真实的客户关联起来。从那里,你可以看到他们是否处于试用阶段、他们多久回来一次、他们打开过多少会话,以及最终何时付费。对我来说,这也让我更容易与该用户沟通,理解他们为什么在那个特定时刻决定继续推进。目前,Revliu 可追踪获客来源、回访访客、会话、触点和收入。我不想仅仅知道某个营销活动获得了多少曝光量,而是想知道它究竟带来了多少收入。曝光量并不是我真正关心的。应用本身相当简洁。主页面提供按来源划分的收入概览。Traffic(流量)展示访客、他们的旅程以及他们的会话。Campaigns(营销活动)展示获客漏斗。对于 SaaS 而言,这可以是访客 → 线索 → 试用 → 付费客户。对于在线商店而言,则可以简化为获客 → 购买。Customers(客户)让你可以单独查看每位客户,查看他们的触点、来源、旅程以及购买时间。技术层面的原理很简单。从一个获得 ID 的匿名访客开始。我们记录他们的访问和触点。当他们注册时,那段匿名旅程会与该客户关联起来。Stripe 也已接入,所以当客户付费时,营收可以回链到同一段旅程。
目标基本上是把获客 → 访问 → 注册 → 客户 → 营收串联起来。目前,该应用仍处于第一阶段。我还没有构建所有我想要的集成。我接下来想打造的不只是展示数据的东西。如果有人留下了邮箱但始终没有完成注册、多次回访但没有购买,或者表现出真正的兴趣却没有转化,我想利用这些信息来尝试挽回这个潜在客户。想法是通过邮件再次触达他们,或者根据集成的不同,通过 LinkedIn 等其他渠道。这就是为什么我今天仍然认为这个应用是有限的。我想先测试这个归因部分,看看这个问题是否真正具有吸引力,然后再构建其他所有东西。我未来真正感兴趣的部分是营收回收(revenue recovery)。通过与 AI 结合,目标将是适配不同的客户,理解哪些客户在犹豫,并做得不仅仅是展示数据。我想要的是这些数据……
译文由上游机器翻译生成,可能有误;判断请以英文原文为准。
英文原文(来源本站未改写)
I’m a founder and I just built RevliI’m a founder and I just built Revliu.After building several products, I always wanted to understand how my customers were actually finding me.Which campaign brought them in, which source they came from, and what their full journey looked like.There are already tools for this, but one problem I kept running into is that they often stop at first touch or last touch.That’s why I built Revliu around multi-touch attribution and the full customer journey.As soon as someone lands on your website, Revliu gives them an anonymous ID and starts tracking their journey.Once they sign up, that journey can be connected to the actual customer.
From there, you can see if they’re on a trial, how often they come back, how many sessions they open, and eventually when they pay.For me, this also makes it easier to talk to that user and understand why they decided to move forward at that specific moment.Today, Revliu tracks acquisition sources, returning visitors, sessions, touchpoints, and revenue.Instead of just knowing that a campaign got a certain number of impressions, I want to know how much money it actually brought in.Impressions are not really what I care about.The app itself is pretty simple.The main page gives you an overview of revenue by source.Traffic shows visitors, their journey, and their sessions.
Campaigns shows the acquisition funnel.For a SaaS, that can be visitor → lead → trial → paying customer.For an online store, it can simply be acquisition → purchase.Customers lets you look at each customer individually, see their touchpoints, where they came from, their journey, and when they bought.The technical side is simple in principle.It starts with an anonymous visitor who gets an ID.We keep track of their visits and touchpoints.When they sign up, that anonymous journey is connected to the customer.Stripe is connected as well, so when the customer pays, the revenue can be linked back to the same journey.
The goal is basically to connect acquisition → visits → signup → customer → revenue.Right now, the app is still in its first phase.I haven’t built all the integrations I want yet.What I want to build next is something that does more than just show data.If someone leaves their email but never finishes signing up, comes back several times without buying, or shows real interest without converting, I want to use that information to try to recover that potential customer.The idea would be to reach them again by email or, depending on the integrations, through other channels like LinkedIn.That’s why I still see the app as limited today.
I first want to test this attribution part and see if there’s real traction around the problem before building everything else.The part I’m really interested in for the future is revenue recovery.By combining it with AI, the goal would be to adapt to different customers, understand which ones are hesitating, and do more than just display data.I want the data
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