Why performance teams switch from Northbeam to Traqly
Northbeam's ML attribution models are accurate but slow — results arrive 24–72 hours after ad spend. Traqly's server-side CAPI closes the loop in real time, so your agents can bid while the data is still hot.
Northbeam's biggest limitation: Northbeam's modeled attribution introduces a 24–72 hour lag between ad spend and reported results. For teams scaling Meta campaigns intraday, this delay means you're optimising on yesterday's model while today's CPMs are already different.
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4 autonomous agents monitor attribution, creative fatigue, bidding efficiency and identity stitching 24/7.
Events stream in under 200 ms. Attribution updates within the same minute — no next-day lag.
Feature comparison
| Feature | Traqly | Northbeam |
|---|---|---|
| Real-time reporting (<200ms) | ||
| Server-side CAPI delivery | Limited | |
| First-party fingerprinting | ||
| Reporting lag | Real-time | 24–72h |
| Claude AI autonomous agents | ||
| Creative fatigue detection | AI-powered | |
| Identity stitching | Model-based | |
| Meta CAPI | Limited | |
| Google Enhanced Conversions | ||
| TikTok Events API | ||
| YouTube CAPI | ||
| Post-purchase survey | ||
| Shopify native webhooks | ||
| AI chat analyst | Claude Sonnet | |
| Starter pricing | $299/mo | Enterprise only |
“Northbeam's accuracy was fine but the lag killed us. By the time we saw a campaign was over-spending it had already wasted $12k. Traqly flagged it inside the hour.”
— E-commerce founder, $600k/month Meta spend (beta customer)
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