Scaling a prop-trading offer to $2.4M in 90 days
The challenge
The operator had a converting funnel but unreliable traffic quality, inconsistent geo delivery, and weak visibility into bot and datacenter activity. Every scale attempt made attribution less trustworthy and cash flow more difficult to predict.
The approach
Rebuilt cloaking and filtering from the request layer up
Replaced the off-the-shelf script with server-side traffic validation, bot and datacenter filtering, consistent offer delivery, and cleaner conversion measurement.
Segmented traffic by geo and intent
Split Tier-1 geos into dedicated funnel variants with appropriate language, currency, eligibility details, and proof while keeping the underlying offer and terms consistent.
Introduced traffic-quality and spend guardrails
Used controlled budget ramps, invalid-traffic alerts, landing consistency checks, and measurement thresholds so spend increased only when the data remained reliable.
Tightened the offer-to-creative feedback loop
Daily creative iteration against cohort ROAS, not vanity CTR — winners scaled, losers cut inside 24 hours.
The results
"We went from praying our accounts survived the week to scaling on schedule. The difference was infrastructure, not luck."
Your numbers could be next.
Same infrastructure, tuned to your offer.