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

Описание и применение

Многопроцессорная система из 14 ИИ‑агентов автоматизировала весь цикл инфлюенсер‑маркетинга: от сбора данных и выбора до стратегии, контента, покупки рекламы и расчётов, повысив CTR на 2,7 % и эффективность на 30 %.

Задача

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

Результат

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.

Рабочий процесс

• 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

Доказательства

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.

Источник

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

Источник