How a Vancouver E-Commerce Brand Scaled Google Shopping to 4x Revenue.
Client: A Vancouver e-commerce brand
Results
Revenue from Google Shopping channel in 7 months
Up from 1.8x baseline
Reduction in cost per conversion
Up from 1.1% via CRO
The Challenge
Google Shopping was live but underperforming at 1.8x ROAS. Feed had missing attributes, incorrect categories, and no margin-based bidding. PMax was not in use. Conversion rate on product pages was 1.1%.
Our Solution
Full product feed rebuild with supplemental feed for custom labels; PMax campaigns with segmented asset groups by product category; landing page CRO to lift conversion rate before scaling spend.
Our Google Shopping campaigns were running but not really working. Now they're our biggest channel by revenue.
Full Story
The Challenge
This Vancouver outdoor lifestyle brand had Google Shopping campaigns running for over a year but had never properly invested in feed quality or campaign structure. ROAS sat at 1.8x — profitable, but well below what well-managed Shopping campaigns should deliver in their category.
The product feed was the core problem: missing GTINs, incorrect Google product categories, no custom labels for margin or seasonality, and product titles that didn't reflect how customers actually searched. Performance Max was not in use. Product pages converted at 1.1% — meaning the potential upside from better campaigns was being limited by the website itself.
Our Approach
We rebuilt the product feed from scratch, adding GTINs for all eligible products, correcting product type hierarchies, and adding custom labels for margin tier (high / medium / low) and seasonality (in-season / off-season). A supplemental feed dynamically updated product titles to match high-volume search queries identified in the search terms report.
Performance Max campaigns were structured with asset groups segmented by product category — hiking gear, camping equipment, apparel, footwear — each with tailored creative assets and audience signals. Margin-based bidding ensured the algorithm prioritised high-margin SKUs.
Parallel CRO sprints on product pages tested image count (6 vs. 10 images), review display position, and size guide placement. The winning combination lifted conversion rate from 1.1% to 2.4% — more than doubling the return on every ad click.
Results
Google Shopping revenue grew 4x in seven months. ROAS improved from 1.8x to 3.4x. Cost per sale fell 35%. The channel now accounts for the brand's single largest revenue stream.
The Challenge
- Google Shopping ROAS at 1.8x — campaigns live but never properly built
- Product feed missing key attributes: GTINs, product types, colour/size variants
- No margin data in bidding — high-margin and low-margin products bidding identically
- Product page conversion rate at 1.1% — limiting the ceiling on any ad scaling
What We Did
- Full product feed rebuild: added GTINs, corrected categories, added custom labels for margin tiers
- Supplemental feed for dynamic titles and descriptions optimised for search queries
- Performance Max campaigns with asset groups segmented by product category and buyer intent
- Margin-based bidding: high-margin SKUs bid 40% higher than low-margin equivalents
- CRO sprints: product page A/B tests on image count, review display, size guide placement — conversion rate lifted to 2.4%
Service Mix
By the Numbers
| Metric | Before | After | Δ |
|---|---|---|---|
| Google Shopping revenue | baseline | 4x | +300% |
| ROAS | 1.8x | 3.4x | +1.6x |
| Cost per sale | high | -35% | -35% |
| Product page conversion rate | 1.1% | 2.4% | +1.3pp |
How It Unfolded
Feed audit; attribute gap analysis; CRO sprint on product pages begins
Rebuilt feed submitted; PMax campaigns structured and launched
Margin-based bidding live; supplemental feed active
ROAS crosses 2.5x
Conversion rate at 2.4%; spend scaled on best-performing asset groups
Google Shopping revenue at 4x baseline; ROAS at 3.4x
Typical Outcome Ranges
Frequently Asked Questions
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