Fernhouse Goods · E-commerce
Return on ad spend
2.1×4.3×
Monthly trend · Dec to Sep
Change
+105%
Sample case study. The client, quotes and every figure are illustrative.
(01)
Where it started
An online home goods store was growing revenue and losing margin. We rebuilt the product feed and campaign structure around profit, fixed the checkout, and turned email from 9% of revenue into 27%.
Fernhouse sold 420 products through one shopping campaign with a single ROAS target. Best sellers with thin margins took most of the budget while profitable products barely showed.
Cart abandonment sat at 78%, shipping costs appeared only at the last step, and the only automated email was an order confirmation.
(02)
What we changed
- Campaigns built on margin tiers
Products grouped into three margin tiers with their own targets. Feed titles rewritten with material, size and use, and 64 products with poor photos reshot.
- A break-even ROAS for every tier
With gross margins of 38%, 52% and 64%, break-even ROAS is 2.6x, 1.9x and 1.6x. Bids now follow contribution profit instead of one blended number.
- Checkout fixes first, then tests
Shipping estimate on the product page, guest checkout by default and express pay buttons. Cart abandonment fell from 78% to 64% before the first formal test.
- Seven email flows
Welcome, browse abandonment, cart abandonment, post-purchase care guide, review request, replenishment and win-back. Each one written, designed and measured against a holdout group.
Timeline
- Month 1
Margin data mapped to every product. Feed rebuilt. Server-side purchase tracking verified against the store's order export.
- Months 2 to 3
Tiered campaigns launched. Checkout fixes shipped. Welcome and cart flows go live.
- Months 4 to 7
Remaining five email flows. Product page tests on photos, reviews placement and bundles.
- Months 8 to 10
Budget raised 40% with ROAS holding above 4x. Holiday calendar and creative planned.
(03)
What it led to
Fernhouse Goods went from 2.1× to 4.3× on return on ad spend in 10 months. The numbers on this page are sample data, laid out the way a real report would be.
| Metric | Before | After | Change |
|---|---|---|---|
| Return on ad spend | 2.1× | 4.3× | +105% |
| Orders per month | 1,240 | 2,680 | +116% |
| Cost per order | $31 | $17 | -45% |
| Revenue from email | 9% | 27% | +18 pts |
Store sessions
Dec to Sep
View data as a table
| Month | Store sessions |
|---|---|
| Dec | 41,000 |
| Jan | 38,500 |
| Feb | 42,200 |
| Mar | 46,800 |
| Apr | 51,000 |
| May | 55,400 |
| Jun | 60,200 |
| Jul | 63,800 |
| Aug | 68,100 |
| Sep | 72,500 |
Orders per month
Dec to Sep
View data as a table
| Month | Orders |
|---|---|
| Dec | 1,240 |
| Jan | 1,105 |
| Feb | 1,290 |
| Mar | 1,480 |
| Apr | 1,690 |
| May | 1,880 |
| Jun | 2,110 |
| Jul | 2,290 |
| Aug | 2,470 |
| Sep | 2,680 |
Cost per order
Dec to Sep
View data as a table
| Month | Cost per order |
|---|---|
| Dec | $31 |
| Jan | $30 |
| Feb | $27 |
| Mar | $24 |
| Apr | $22 |
| May | $20 |
| Jun | $19 |
| Jul | $18 |
| Aug | $18 |
| Sep | $17 |
Return on ad spend
Dec to Sep
View data as a table
| Month | ROAS |
|---|---|
| Dec | 2.1x |
| Jan | 2.2x |
| Feb | 2.6x |
| Mar | 2.9x |
| Apr | 3.3x |
| May | 3.6x |
| Jun | 3.8x |
| Jul | 4.0x |
| Aug | 4.1x |
| Sep | 4.3x |
“We used to celebrate revenue and wonder where the money went. Now every campaign has a break-even number and we know which ones clear it.”
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