用AI分析评论筛选创作者：@viktor_com 替代粉丝数过滤
Follower count is the worst filter in creator marketing
这篇展示了如何利用 AI 工具进行具体的创作者筛选工作流，有真实案例数据对比和清晰的执行步骤，写法对同行很有参考价值。
Follower count is the worst filter in creator marketing
粉丝数是创作者营销中最糟糕的筛选标准
Our team matches AI creators with brands. This week a brand asked us for AI creators with a developer audience in the US
我们的团队将 AI 创作者与品牌进行匹配。本周，一个品牌向我们寻求拥有美国开发者受众的 AI 创作者
The old way: sort the roster by followers, pitch the top of the list, hope
旧方法：按粉丝数对名单排序，向列表顶部的创作者推销，然后碰运气
The new way: an AI employee reads who actually shows up
新方法：一名 AI 员工阅读实际互动情况
Viktor took the 50 biggest creators on our roster and read the last 150 replies under each one's posts: where people are, what they build, what they ask
Viktor 选取了我们名单中粉丝量最大的 50 位创作者，并阅读了每位创作者帖子下的最后 150 条评论：人们在哪里、他们构建什么、他们询问什么
12 had an audience that matched the brief. 7 of the 10 biggest did not. 3 accounts under 30K followers were the best fit of all
其中 12 位的受众符合简报要求。前 10 大创作者中有 7 位并不符合。粉丝量低于 3 万的 3 个账号反而是最匹配的
He contacted nobody. Every name came with the replies that made the case. We pitched the 12
他没有联系任何人。每个名字都附带了支撑推荐理由的评论。我们向这 12 位进行了推介
The 8 rules we run it on are in the image
我们运行此流程所依据的 8 条规则见图片
Brands: would you rather book the biggest account, or the one whose replies look like your buyers?
品牌方：你更愿意预订粉丝量最大的账号，还是评论区看起来像你的买家的账号？
Try free at @viktor_com. $100 in credits, no card. Full link in my first reply.
在 @viktor_com 免费试用。赠送 100 美元额度，无需绑卡。完整链接在我的第一条回复中。
更进一步：量化金融体系
看懂新闻只是起点——沿量化金融路径，把它变成能交付的工程能力