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我在LinkedIn上进行冷联系已经两年了。并不是大规模的联系——每天大约发送10到15条消息给潜在客户。问题从来不是找到可以联系的人。LinkedIn的搜索功能很好用，Sales Navigator也存在，推荐也会发生。问题在于打开他们的个人资料后……盯着看。 “好吧，他们是某家B轮公司的工程副总裁。他们上周发过关于技术债务的帖子。我该如何让自己在他们的收件箱中不显得和其他人一样？” 删除。重写。检查是否太长。太短。太商业化。内容不够具体。四十七分钟后，我写了四条消息。真正的问题大多数外联工具解决的是错误的问题。它们提供：带合并标签的模板（{{firstName}}在{{company}}工作）违反LinkedIn服务条款的自动发送功能批量序列自动化但这并不是我卡住的地方。我知道该联系谁。我只是无法快速想出该说什么。 ChatGPT的帮助也不大。除非我花10分钟时间精心编写完美的提示，包括他们的个人简介、我的产品细节和语气指南，否则它给我的都是一些泛泛而谈的内容。到那时，我不如自己写。我所构建的我制作了一个Chrome扩展，它： 1. 只需设置一次——添加你的产品描述并为不同的声音（技术性、咨询性、随意等）创建“角色”。 2. 当你打开LinkedIn个人资料时，点击扩展。 3. 它读取他们的个人资料，将信号与您的产品匹配，应用您的角色，并在大约5秒内生成一条消息。 4. 你审阅，如果需要编辑，然后手动复制粘贴到LinkedIn中。没有自动化。没有自动发送。没有违反LinkedIn的行为。只是更快的消息撰写。技术方法该扩展抓取可见的个人资料数据（没有API，因为LinkedIn多年前关闭了这一功能）。将其发送到后端，后端：提取关键信号（角色、公司阶段、最近活动）将这些信号与您的产品背景匹配应用特定角色的提示工程返回一条消息，遵循严格的规则（没有流行词，没有“希望你一切安好”，保持在150字以内）角色系统是有趣的部分。您可以在不同的声音之间切换，而不是一个通用的提示。“前顾问”角色的语气与“技术联合创始人”角色的语气不同——句子结构和参考点都不同。我学到的最大的惊喜是：人们并不想要更多的自动化。他们希望保持控制，但又想消除空白页面的问题。每当我在早期用户访谈中提到“自动发送”，人们就会变得紧张。但“为我写，我会审阅并发送”则引起了立即的兴趣。第二个惊喜是：质量标准比我预期的要高。一条消息如果有80%的好，但有一句奇怪的内容？人们会重写整条消息。它需要达到95%的好，否则就没用。当前状态现在处于私人测试阶段。大约有40人正在使用。平均消息生成时间为6秒。大多数人在发送前会编辑大约20%的消息。我不确定这是否是一个真正的商业模式，但它解决了我的问题。也许它也能解决你的问题。很高兴回答有关技术实现或我所观察到的用户行为模式的问题。它叫做Prospectee。如果你感兴趣，可以在prospectee.io查看。

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I've been doing cold outreach on LinkedIn for two years. Not at scale — maybe 10-15 messages a day to potential customers.The problem was never finding people to message. LinkedIn search works fine. Sales Navigator exists. Referrals happen.The problem was opening their profile and... staring."Okay, they're a VP of Engineering at a Series B company. They posted about technical debt last week. How do I not sound like every other person in their inbox?"Delete. Rewrite. Check if it's too long. Too short. Too salesy. Not specific enough.Forty-seven minutes later, I'd written four messages.The real issueMost outreach tools solve the wrong problem. They give you:Templates with merge tags ({{firstName}} works at {{company}}) Auto-send features that violate LinkedIn's ToS Bulk sequence automationBut that's not where I was stuck. I knew WHO to message. I just couldn't figure out WHAT to say without it taking forever.ChatGPT didn't help much either. It would give me generic garbage unless I spent 10 minutes crafting the perfect prompt with their bio, my product details, and tone guidelines. At that point, I might as well write it myself.What I built I made a Chrome extension that:1. You set up once — add your product description and create "personas" for different voices (technical, consultative, casual, whatever) 2. When you open a LinkedIn profile, click the extension 3. It reads their profile, matches signals to your product, applies your persona, and generates a message in ~5 seconds 4. You review it, edit if needed, copy and paste it into LinkedIn manuallyNo automation. No auto-send. No LinkedIn violations. Just faster message writing.Technical approach The extension scrapes visible profile data (no API, since LinkedIn shut that down years ago). Sends it to a backend that:Extracts key signals (role, company stage, recent activity) Matches those against your product context Applies persona-specific prompt engineering Returns a message with strict rules (no buzzwords, no "I hope this finds you well", keep it under 150 words)The persona system was the interesting part. Instead of one generic prompt, you can switch between voices. A "former consultant" persona sounds different than a "technical cofounder" persona — different sentence structure, different reference points.What I learnedThe biggest surprise: people don't want more automation. They want to stay in control but eliminate the blank-page problem.Every time I mentioned "auto-send" in early user interviews, people got nervous. But "write it for me, I'll review and send" got immediate interest.Second surprise: the quality bar is higher than I expected. A message that's 80% good but has one weird line? People rewrite the whole thing. It needs to be 95% good or it's useless.Current stateIn private beta now. About 40 people using it. Average message generation time is 6 seconds. Most people edit about 20% of messages before sending.Not sure if this is a real business yet, but it solved my problem. Maybe it'll solve yours too.Happy to answer questions about the technical implementation or user behavior patterns I've seen.It's called Prospectee. You can check it out at prospectee.io if you're curious.

我开发了一个工具，以避免在LinkedIn上浪费时间发送外联消息。