Auto Parts E-Commerce
From 250% to
450%+ ROAS
The Challenge
US-based auto parts store with 50,000+ SKUs across brakes, suspension, engine components, and aftermarket accessories. ROAS was stuck at 200–250% for over a year under a previous agency. The account wasn’t failing — it was stagnating.
The root problem was invisible: 25% of the catalog (12,500+ products) was disapproved in Google Merchant Center. Missing GTINs, incorrect brand mapping, and product titles with zero fitment data. A title like “Front Brake Pads” instead of “2019 Ford F-150 Front Brake Pads — Bosch OEM Quality.” For auto parts, fitment is everything — customers search by vehicle, and if titles don’t contain Year/Make/Model, Google can’t match the product.
One Performance Max campaign handled all 50,000 SKUs with one bidding target. A $5 air filter and a $400 turbocharger shared the same strategy. No segmentation by margin, vehicle popularity, or performance tier. Browser-only tracking was missing ~20% of purchases due to iOS restrictions and ad blockers.
What We Did
Feed audit & title rewriting
Rewrote all 50K product titles using automated scripts pulling Year/Make/Model from the fitment database. Fixed disapprovals — missing GTINs, incorrect brand mapping. Approval rate went from 70% to 96%, recovering 13,000+ previously invisible products.
Custom label segmentation
Created labels across three dimensions: margin tier (A: 30%+, B: 15-20%), vehicle popularity (F-150, Silverado = dedicated asset groups), and performance tier (top 500 SKUs flagged as hero products).
Campaign restructure: 1 → 4 tiers
Hero Products (top 500 SKUs, aggressive bids), Catalog (long-tail, conservative), Brand Defense, and Clearance. Each tier with its own ROAS targets matching the economics of those products.
Server-Side Tracking
Implemented Server-Side GTM to recover the ~20% of conversions browser-side setup was missing. Algorithms finally had complete purchase data to optimize against.
Controlled scaling
First 3 months: spend stayed flat while efficiency gains compounded. Months 4-6: budget increased 20-30% per cycle while ROAS held above 400%.
The Results
Revenue grew while ad spend stayed flat for the first 3 months — pure efficiency gain from better feed matching, smarter segmentation, and complete conversion data.
Hero product tier (top 500 SKUs) delivered 65% of total revenue. Ford F-150 and Chevy Silverado parts — segmented into own asset groups — generated 35% of Shopping revenue from ~8% of catalog.
They found problems in our product feed that our previous agency never even looked at. Within two months, our ROAS nearly doubled — and we didn’t increase our ad budget.
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