Ecommerce Google Ads case studies
Every recommendation is data-backed. Every outcome is measurable. Here's what that looks like in practice.
These results come from accounts we manage across Google Ads, Google Shopping, Meta Ads, and marketplace advertising. Read more about each on the relevant service page.
Beyond the Website: Same Brand, New Channel
How the same automotive e-commerce brand from our first case study added $325K in marketplace sales in eight months, without cannibalising the website that was already working.
The Challenge
After the Google Ads restructure in our first case study, the website was performing, but it had a ceiling. Website sales are capped by the demand that reaches your website. A large share of Australian auto-parts buyers never leave eBay: they search, compare, and buy inside the marketplace. For a catalogue of 48,000+ parts listings, that demand was sitting untouched. eBay is about 30% of the store’s total monthly revenue. The question wasn’t whether to expand. It was whether marketplace sales would be genuinely new revenue, or just the same customers buying in a different place.
The Insight
Three findings shaped the expansion.
The demand was channel-native
Marketplace buyers weren’t choosing between the website and eBay: they were shopping on eBay or nowhere. Reaching them meant advertising where they already were, not spending more to drag them to the site.
Breadth beats heroes in parts
Auto parts is a long-tail category: thousands of vehicle-specific SKUs, each selling a handful of units. No hero product would carry the channel. The advertising structure had to monetise the entire 48,756-listing catalogue at once.
Incrementality had to be provable
The expansion would only count as a win if website revenue held. That meant tracking both properties against each other from day one: the same measure-everything standard as the first engagement.
The Strategy
Launch broad, test deliberately, then rebuild around what the data proved.
Launch broad, price the whole catalogue in
- Promoted Listings General campaigns across the full catalogue from November 2025, ad rates tiered by product group.
- Cost-per-sale pricing meant fees only accrued on actual sales: the right risk profile for testing a new channel at scale.
Run a structured test tranche
- A two-week controlled test in May–June 2026 of alternative structures: hero-SKU priority campaigns against long-tail coverage tiers.
- The test campaigns were deliberately ended after two weeks with their answer in hand: the top-100 priority test returned 32× ROAS and the long-tail tiers 25×, proving targeted structures could roughly double the blended efficiency of broad coverage.
Rebuild around vehicle-make segmentation with Smart Bidding
- The test showed efficiency came from tighter product grouping, so the channel was restructured into make and region families: Australian & American, Asian, German, and European makes, on Priority campaigns with Smart Bidding.
- Grouping by make aligned campaigns with how parts buyers actually search, and gave eBay’s bidding algorithm coherent product sets to optimise.
The Results
Before vs After
| Metric | Launch Structure (Nov 25 – Jun 26) | Rebuilt Structure (from mid-Jun 26) | Change |
|---|---|---|---|
| Campaign model | Broad coverage, fixed ad rate | Make-segmented, Smart Bidding CPC | Restructure |
| ROAS | 8.5× | 14.9× | +75% |
| Monthly ad sales | AU $32–46K plateau | AU $47.6K in the first 20 days of July | Record pace |
| Website revenue/mo (GA4) | ~AU $142K (pre-launch baseline) | ~AU $142–148K | Held: fully incremental |
The Takeaway
Marketplace expansion is usually pitched as a volume play and measured sloppily. This one was run like the first engagement: prove the increment, test the structure before scaling it, and let the data end campaigns as decisively as it launches them. Eight months in, the marketplace channel adds roughly $40K a month in attributed sales. eBay ad fees were 3.4% of eBay sales, and the website kept every dollar it was already earning. The channel is different. The operating discipline is the same.
Client name anonymised. Advertising figures as reported by eBay Seller Hub advertising reports for 29 Nov 2025 – 20 Jul 2026; ad-attributed sales use eBay’s attribution. Website revenue is actual GA4 e-commerce purchase revenue, not modelled. All figures AUD.
Scaling Spend Without Losing ROAS
5.3x → 5.5x ROAS while ad spend scaled 2.3x for an Australian automotive parts store.
The Challenge
Before April 2024 the store spent about $6,900 a month on Google Ads. Shopping was barely running, so most product searches were not covered by product ads. Performance Max was also spending heavily on existing customers who would likely have bought anyway.
The Insight
Growth had to come from people who had not bought before. Spend going to existing customers looked efficient in the platform, but it added few new orders.
The Strategy
- Ramped up Shopping spend so product searches were covered by product ads.
- Restructured Performance Max around new-customer acquisition instead of existing customers.
The Results
Before vs After
| Metric | Before | After | Change |
|---|---|---|---|
| Monthly Spend | AUD $6,851 | AUD $15,852 | 2.3x |
| Monthly Orders | 143 | 316 | +121% |
| Monthly Ad Revenue (ex GST) | AUD $36.5k | AUD $86.8k | +138% |
| ROAS | 5.3x | 5.5x | Held |
Google Ads reported purchases only, excluding calls and form fills. Revenue ex GST.
The Takeaway
Ad spend scaled 2.3x and orders rose 2.2x, with ROAS steady at 5.3x to 5.5x. The growth came from more orders, not bigger baskets: average order value moved from about $255 to $275 ex GST.
Client name anonymised. All figures AUD.
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