一家 B2B 营销代理公司押注 AI,6 个月内将 ARR 增长至 150 万美元
A B2B marketing agency grew to $1.5M ARR in 6 months by betting on AI
我们发现了什么
一家 B2B 营销代理公司押注 AI,6 个月内将 ARR 增长至 150 万美元。六个月前,我们押注于代理公司模式本身已不适用于 AI 时代,因此我们拆掉原有模式并重建。
- 来源:Hacker News(发现于 2026-07-21)
- 证据等级:B · 来源中出现收入或付费客户自述;本站未核对该金额,不代表本站背书。
- 商业模式:AI-enabled Service
- 主题:营销与增长
- 初筛评分:45.4/100 · 收录 1 次
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中文辅助译文(全文)
我运营 GrowthSpree,这是一家面向美国和欧洲市场的 B2B SaaS 营销代理机构。六个月前,我们判断代理模式本身在 AI 时代已经失效,于是拆掉了原有架构并重新构建。下面是我们做的事情以及实际发生的情况。我们的赌注是:成为第一家真正 AI 原生的营销代理机构。不是那种把 ChatGPT 拼接到 2015 年工作流上、号称"使用 AI 工具"的机构,而是把 AI 深度嵌入到我们发现需求、赢得客户和交付执行的方式中。我们重建的是运营模式,而不仅仅是工具栏。关键的背景是:我们服务过 300 多家 B2B SaaS 公司,但过去两年 ARR 一直徘徊在 $500K 到 $800K 之间,陷入了增长平台期。然而自重建以来的六个月,我们的 ARR 增长到了 $1.5M,而且几乎全部来自我们此前毫无品牌认知度的美国和欧洲市场。目前客户包括 Datahub、PriceLabs、Hasura、Rocketlane、Proton AG、Spoke 等。发生变化的关键在于:1. 我们押注 AEO 而非 SEO。买家现在会先询问 LLM,再去问 Google。因此我们内部构建了自己的答案引擎优化(Answer Engine Optimization)引擎,针对模型实际如何检索、排序和引用来源进行优化。它成为我们在那些无人知晓的市场中获取需求和建立信任的主要渠道。成为模型给出的答案,就是新的"排在首页",而且这种效应会复利累积。2. 我们用自己的 GTM 自我实践(dogfood)。我们卖给客户的获客方式,正是让我们自己增长起来的那一套。
它是基于群组的 ABM(cohort-led ABM):我们基于真实的购买信号构建紧密的目标客户群组,运行一个永不中断的全天候 LinkedIn 预热动作,在此之上叠加跨 LinkedIn 和邮件的多渠道触达,然后根据潜在客户的互动情况重新分组,再循环一次。没有大面积撒网。AI 以人工团队无法企及的规模完成调研、细分和首版信息起草。3. 成交变得更容易,而非更困难。我们的关单率达到历史最高的 40%,即便在陌生线索(cold leads)上也如此。当潜在客户可以用 AI 询问你所在的赛道、不断看到你的思考内容,然后被相关且具体的触达预先"加热"之后,销售电话的开场白从"你是谁?"变成了"我已经信任你了"。信任在第一次回复之前就已经建立。4. 我们推出了自研工具。两款工具承担了主要工作:一款是面向 B2B 营销的 MCP 服务器,让 AI 智能体可以直接对我们的技术栈和数据采取行动,调用实时数据并执行操作,而不是依赖截图进行猜测;另一款是 OLA AI,我们的 LinkedIn 广告优化层,以任何人类团队都无法匹配的速度管理出价、受众和创意迭代。重点不是演示本身,而是同样的人力现在能够覆盖和高质量运行远超以往的作业面积。5. 我们重写了 SOP。大多数代理机构的操作手册默认由人类完成首稿,再由 AI 润色。我们反了过来:AI 完成调研、定向、文案和分析的第一遍;资深人员掌握判断力、品味和最终拍板。从客户开发到报告输出,再到我们自己的 newsletter《The Compound》,每一个流程都围绕这一顺序重新构建。6. 我们只以资深人员组成的封闭式小组运行团队。没有任何初级层…
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 run GrowthSpree, a B2B SaaS marketing agency, selling into the US and Europe.Six months ago we made a bet that the agency model itself was broken for the AI era, so we tore ours down and rebuilt it.This is what we did and what actually happened.The bet: become the first truly AI-native marketing agency.Not an agency that "uses AI tools" by bolting ChatGPT onto a 2015 workflow, but one where AI is wired into how we find demand, win clients, and run delivery.We rebuilt the operating model, not just the toolbar.The context that matters: we have worked with 300+ B2B SaaS companies, but we'd been stuck between $500K and $800K ARR for two years.Plateaued.
Then in the six months since the rebuild we went to $1.5M, almost entirely in the US and Europe, where we had no brand.Clients now include Datahub, PriceLabs, Hasura, Rocketlane, Proton AG, Spoke and more.What changed: 1.We bet on AEO over SEO.Buyers now ask an LLM before they ask Google.So we built our own Answer Engine Optimization engine in-house and pointed it at how models actually retrieve, rank, and cite sources.It became our primary channel for demand capture and trust-building in markets where nobody knew us.Being the answer the model gives is the new being on page one, and it compounds. 2.We dogfood our own GTM.The motion we sell clients is the one that grew us.
It's cohort-led ABM: we build tight account cohorts from real buying signals, run an always-on LinkedIn warm-up that never switches off, layer multi-channel outreach across LinkedIn and email on top, then re-cohort people based on how they engage and loop it again.No spray-and-pray.AI does the research, segmentation, and first-draft messaging at a scale a manual team can't touch. 3.Closing got easier, not harder.Our close rate is at an all-time high: 40%, even on cold leads.When prospects can interrogate an AI about your space, keep landing on your thinking, and then get warmed up by relevant, specific outreach, the sales call starts with "I already trust you" instead of "Who are you?
" Trust is now built before the first reply. 4.We shipped our own tooling.Two pieces do the heavy lifting: an MCP server for B2B marketing that lets AI agents act directly on our stack and data, pulling live numbers and taking actions instead of guessing from screenshots;and OLA AI, our LinkedIn ads optimization layer that manages bidding, audiences, and creative iteration at a cadence no human team can match.The point isn't the demos.It's that the same headcount now runs far more surface area, well. 5.We rewrote the SOPs.Most agency playbooks assume humans do the first draft and AI cleans up.We flipped it: AI does the first pass on research, targeting, copy, and analysis;
senior people own judgment, taste, and the final call.Every process from prospecting to reporting to our own newsletter, The Compound, was rebuilt around that order of operations. 6.We run in closed cohorts of seniors only.No junior layer to babysit AI
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