Client case study · Fashion ecommerce · UK
ClosureLDN: different stock needs different decisions.
- SKUs treated in four Shopping routing groups
- 591
- High-return SKUs
- 340
- Broken-size SKUs
- 66
- Period
- UK, 1 March–31 August 2026 (six months).
- Basis
- SKU counts and campaign results observed across four differentiated Shopping groups; no before-and-after baseline is asserted.
- Source
- Client quarterly business review, prepared 16 September 2026; routing-layer analysis. Reviewed figures only.
Commercial problem
In stock does not mean worth promoting alike.
ClosureLDN's catalogue carries the usual fashion problems at scale. Some products come back at high rates, so their checkout revenue overstates what the business actually keeps. Some styles are technically in stock but the sizes customers want have sold through, so the click is worth less than it looks. Some stock exists to turn into cash, and a small number of products earn their keep by bringing in new customers.
The account was treating all of these products the same way. A single product-level target cannot express "protect margin here, chase cash there, pay for acquisition over there". Every SKU was effectively being asked to do the same job, and the budget drifted towards whatever Google found easiest to spend on, not what the business needed sold.
The question we set out to answer was simple: which products deserve aggressive bids, which deserve restraint, and how do we make the account act on that difference?
Why we did it
A product's availability and job should set its advertising treatment.
In fashion, the commercial value of a click changes with the size run behind it. A style with a full size run can absorb aggressive bidding. The same style with only scattered sizes left cannot, because most of the demand it attracts cannot convert. High-return lines have the same problem in reverse: the sale happens, then part of it comes back.
Left to a single target, Shopping and Performance Max will happily spend against all of these products at the same intensity. The platform sees conversion data; it does not see the return rate, the broken size run or the cash position behind each product. That judgement has to come from the business, and it has to be built into the account structure.
What we did
Four Shopping routing groups, each with its own level of restraint.
We audited the catalogue and assigned 591 SKUs to four routing groups based on the commercial job each product needed to do: High Returns, Cash Flow, New Customer and Broken Sizes. Each group was given its own Shopping treatment, with bids and budgets set to match the job rather than a single blended target.
High-return and broken-size products were deliberately restrained, so the account stopped paying full price for weak clicks. Cash-flow and new-customer products were allowed higher bids, because those groups justified paying more for the right traffic.
The four groups
What each group was for.
| Role | SKUs | Commercial job | How it was treated |
|---|---|---|---|
| High Returns | 340 | Protect contribution | Restrained. Bids held back so the account was not paying full price for clicks on products with a history of coming back. |
| Cash Flow | 170 | Convert stock into cash | Allowed higher bids. These products had a cash-recovery job, so they were given room to compete for volume. |
| New Customer SKUs | 15 | Acquire customers | Allowed higher bids. A small group of products carrying an acquisition role, where a first order is worth more than its immediate margin. |
| Broken Sizes | 66 | Limit wasted spend | Heavily restrained. Technically in stock, but the sizes customers actually want were gone, so the click was worth far less. |
The result
£78,085 attributed revenue across four product groups.
The four routing groups ran as differentiated Shopping campaigns over the six months, and the structure worked as intended. The restrained high-return and broken-size groups bought traffic cheaply, while the cash-flow and new-customer groups carried the higher bids they were designed for. The catalogue was no longer being treated as one undifferentiated block.
Separately, the review's product grading showed how concentrated the catalogue was: Grade-A products represented 17% of active items (547 SKUs) and generated 80.4% of net sales. That concentration is exactly why a single blended target wastes money.
Measurement note: £78,085 is Google Ads attributed conversion-time revenue on £13,968 of ad spend across the four groups, a reported 5.59x ROAS. These are observational figures; they do not measure incremental sales or profit.
- Period
- UK, 1 March–31 August 2026 (six months).
- Basis
- Google Ads attributed conversion-time revenue and spend across four Shopping routing groups; observational, with no incremental or profit inference. Grade-A share is a separate descriptive observation of the catalogue.
- Source
- Client quarterly business review, prepared 16 September 2026; routing layer and product grading analysis. Reviewed figures only.
What happens next
Routing was not the end of the job.
The September 2026 review identified the next step: tightening routing negatives across the main Performance Max campaign so high-return and broken-size products stay out of it. Allocation work is never finished, because stock, sizes and return rates keep moving.
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