The Situation
A flat shopping structure treats a €180 dress and a €28 accessory identically. When budget is constrained, Google maximises conversion volume — often by spending heavily on low-AOV, low-margin products. Scaling the budget amplified this problem: more spend, but on the wrong products, resulting in ROAS collapse.
The Turning Point
A product-level ROAS analysis revealed that 20% of SKUs drove 74% of contribution margin but received only 31% of ad spend. The budget allocation was inverted relative to profit.
What We Did — And Why
We restructured shopping campaigns into three tiers: star products (top 20% by margin), standard, and clearance — each with independent budgets and bidding targets. Performance Max campaigns were layered over the standard shopping campaigns with CRM audience signals (past purchasers, high-LTV segments) as inputs to the algorithm. The product feed was overhauled: titles rewritten with search term data, product types mapped to Google taxonomy, and missing attributes filled for 1,200 SKUs.
Our Approach
- 1.Shopping campaign architecture by margin tier — high-margin products got aggressive bids, low-margin products were profit-protected
- 2.Performance Max campaigns layered over shopping with audience signals from CRM data
- 3.Feed optimisation: titles, descriptions, and attributes rewritten with commercial keyword data
The Results
Within 4 months, monthly revenue from paid grew from €68k to €180k — a 164% increase — while ROAS actually improved from 4.2x to 4.8x. Contribution margin held at 32% across the scaled spend.
In Their Own Words
“Shopping structure is the difference between scaling profitably and scaling into losses. The same budget, structured correctly, delivers completely different results.”