The situation: DTC apparel brand running one PMax campaign for everything. $180K/yr spend ($15K/month). Blended ROAS showed 2.8x — which looked fine until we dug in. Cold traffic ROAS was 1.2x. Remarketing was inflating the number. The algorithm was feeding budget to the easiest conversions (existing customers) and starving new customer acquisition.
What changed:
- Week 1: Audited the account. Identified cold/warm traffic mixing as the primary structural problem. 200 SKUs competing for the same budget with no segmentation.
- Week 2: Implemented the 3-campaign architecture. Feed-Only PMax for product traffic. Demand Gen campaign for cold audiences. Remarketing PMax for warm traffic. Separated budgets.
- Week 3: Ran the Emotional Truth Extraction on their top 3 customer segments. Generated and scored 75 headline candidates. Built the 80-image library with the Image Mix Formula.
- Week 4: Launched with Maximize Conversions bidding (not tROAS). Policy compliance checklist completed. All settings locked.
- Weeks 5-8: Weekly X-Ray cadence. Replaced 12 LOW-rated headlines from the scored pool. Shifted 15% of budget from Remarketing to Feed-Only after cold traffic ROAS stabilized.
The results (month by month):
- Month 1: Blended ROAS dipped to 2.4x (expected — cold traffic getting more budget). Cold traffic ROAS improved from 1.2x to 1.8x.
- Month 2: Blended ROAS recovered to 3.0x. Cold traffic ROAS hit 2.1x. New customer acquisition up 40%.
- Month 3: Blended ROAS hit 3.4x. Cold traffic ROAS stabilized at 2.3x. $8,400/month in incremental revenue.
- Annualized: $100K+ in additional revenue. Same products. Same total budget. Different architecture.
The single biggest lever was separating cold from warm traffic so the algorithm could optimize each audience independently. That's Module 2.