14 agents filtered 120,000 influencers down to 30 and improved CTR by 2.7% — multi-agent in production

说明与用途

14个AI代理自动化完成了从数据收集、影响者筛选、策略制定、内容创作、媒体购买到结算的完整影响者营销流程，提升CTR 2.7%并提高30%的工作效率。

问题

Influencer marketing workflows are manual, fragmented, and coordination-heavy, leading to slow, inconsistent, and costly campaigns.

结果

The multi-agent system reduced influencer selection from 120k to 30 with consistent scoring, personalized briefs, automated media buying, and end-to-end settlement, yielding a 2.7% CTR increase and 30% workflow efficiency improvement.

工作流

• Connect data collection agents to platform APIs for audience and performance data
• Scan ~120,000 influencer profiles and score them on style, audience overlap, conversion, and pricing
• Select top 30 influencers based on multi-dimensional ranking
• Generate 60-point, per-influencer strategy briefs tailored to content format and audience
• Produce text, image, and video assets aligned with briefs via coordinated agents
• Auto-purchase and optimize ad placements through platform APIs, adjusting spend in real-time
• Track performance from impression to lead to payment and settle payments automatically

证据

120,000 to 30. That's a 99.975% reduction. A human team doing this manually might review a few hundred profiles in a day if they're fast.

来源

After a 1-month trial run: Natural click-through rate improved by 2.7% compared to comparable campaigns

来源