anthropics 的增长营销人员梳理了 AI 营销应用的 4 个层级
大多数人停留在 level 1，即把他们已经在做的事自动化
> level 1: 自动化你已经在做的事（报告、文案、数据拉取） > level 2: 在 AI 比你更擅长的领域将其作为思考伙伴 > level 3: 去做以前低于 ROI 阈值的工作 > level 4: 构建只有你才会去构建的定制工具
level 3 是以前从未有过的工作。那些没人做的事，因为人工成本根本不划算
比如在所有广告组中挖掘否定关键词，或者每天检查全站死链
同样的逻辑也适用于内容、调研、QA 和竞品监控。这些工作在理论上一直存在，但没人有那么多时间去处理
level 4 则是 ROI 产生复利的地方
现在 github 上流传着数百个 AI 营销技能和插件。它们大多数在理论上可行，但在实践中却行不通，因为它们是为通用场景构建的，而不是你的特定场景
你的业务拥有特定的数据、特定的工作流和特定的边缘情况，这是任何通用工具都无法覆盖的。那些围绕自身问题构建定制工具的人，才是真正脱颖而出的赢家
anthropics growth marketer mapped out 4 levels of AI marketing use
most people sit at level 1, automating what they already do
> level 1: automate what you already do (reporting, copy, data pulls) > level 2: use AI as a thinking partner where its better than you > level 3: do work that was below the ROI threshold before > level 4: build custom tools only you would ever build
level 3 is work that never existed before. stuff nobody did because the manual cost was never worth it
mining negative keywords across every ad group. checking your full site for broken links daily
same logic applies to content, research, QA, competitor monitoring. all work that existed in theory but nobody had the hours for
level 4 is where the ROI compounds
there are hundreds of AI marketing skills and plugins floating around github right now. most of them work in theory but fall apart in practice because they are built for the general case, not your case
your business has specific data, specific workflows, specific edge cases that no generic tool will ever cover. the people building custom tools around their own problems are the ones pulling ahead
