Retail media teams are running more retailer-specific budgets than ever: Amazon Sponsored Products, bol Sponsored Products, Walmart Connect, Mirakl Ads, retailer display, onsite video, offsite audiences and a cheerful little pile of CSV exports. The platforms all promise performance. The awkward question is: performance against what?
A retailer media scorecard is the operating layer that lets you compare channels without pretending they measure the same thing. It sits above native ad consoles and connects spend to retail media analytics, profit analytics, stock, returns, price position and SKU-level contribution margin. Lovely when it works. Slightly feral when it lives in seven spreadsheets.
The goal is not to crown one retailer as “best.” The goal is to know which retailer deserves the next euro of budget for each product, each placement and each commercial job.
Why retailer media scorecards matter now
Retail media budgets used to be easier to review because most spend sat in search placements. In 2026, budget is split across search, product detail pages, brand placements, display, video and offsite audiences. That makes native ROAS less reliable as a decision metric.
A scorecard gives every retailer the same commercial test: did this spend create profitable demand, or did it simply relabel demand we already had? That is where TACoS vs ROAS, placement role and incrementality become more useful than a lonely ROAS column looking proud of itself.
| Scorecard layer | Question it answers | Metric family |
|---|---|---|
| Economics | Can the SKU afford more spend? | Contribution margin, fees, fulfilment, returns |
| Demand role | Is the spend harvesting, defending or building? | Placement mix, search terms, new-to-brand, TACoS |
| Operational readiness | Can we fulfil the demand profitably? | Stock cover, Buy Box, delivery promise, content quality |
| Decision | What happens next? | Scale, cap, test, fix or cut |
The five metrics every retailer scorecard needs
Keep the scorecard tight. If it needs a PhD and three coffees to understand, it will not survive the Monday trading meeting.
- Contribution margin after ads: revenue minus COGS, marketplace fees, fulfilment, returns and ad spend.
- TACoS by retailer: ad spend as a share of total retailer revenue, not only attributed revenue.
- Placement mix: the share of spend in search, PDP, brand, display, video and offsite placements.
- Return-adjusted ROAS: attributed sales corrected for expected refunds and return costs.
- Stock-adjusted opportunity: budget recommendations filtered by available stock and replenishment risk.
How to compare Amazon, bol, Walmart and Mirakl fairly
Walmart Marketplace, Amazon, bol Ads and Mirakl analytics all have different reporting logic. Attribution windows vary. Sponsored placement names vary. Fee structures vary. Even fulfilment quality affects conversion and ranking differently. A fair scorecard normalizes the business question, not the raw export.
For each retailer, map native metrics into a common model: spend, attributed orders, total orders, placement, SKU margin, return risk and stock cover. Then review retailer performance by SKU cohort. A profitable hero SKU on Amazon can be a margin leak on bol if LVB costs, return rate or price parity are different.
| Retailer pattern | Common reporting trap | Profit-first fix |
|---|---|---|
| Amazon | Strong attributed ROAS hides FBA fees and branded-search cannibalization | Add SKU P&L, TACoS and branded/non-branded split |
| bol | Organic rank gains look like ad wins | Compare Sponsored Products with product-rank and return movement |
| Walmart | Low CPCs look cheap before conversion and fulfilment checks | Add conversion rate, stock and delivery promise |
| Mirakl | Marketplace-by-marketplace variance gets averaged away | Score each retailer environment separately |
Build the scorecard around decisions, not reporting
The best scorecards end every row with an action. “ROAS 4.2” is a fact. “Scale search by 15% but cap PDP conquest until returns fall below 8%” is a decision. Much sexier, in a spreadsheet sort of way.
Use five action labels: scale, hold, cap, fix or cut. Scale when margin, demand role and operations agree. Hold when performance is good but volume or stock is limited. Cap when ads are working but the SKU cannot absorb more. Fix when price, content or stock blocks growth. Cut when spend fails the contribution-margin test.
Where FiveX fits
FiveX connects marketplace ads, profitability, inventory and returns in one workspace. That means teams can compare retailer media performance with the same SKU economics instead of manually stitching exports together.
If you already use retail media placement analytics, the retailer scorecard becomes the next layer: which retailer, placement and SKU deserve budget this week? Revenue is invited to the meeting. Profit gets the chair.
FAQ
What is a retailer media scorecard?
It is a shared performance view that compares retail media spend across retailers using normalized profit, placement, inventory and return metrics.
Should every retailer use the same ROAS target?
No. ROAS targets should reflect margin, fees, return risk, channel maturity and the commercial job of the spend.
How often should teams update the scorecard?
Weekly for budget decisions and daily during major events, launches or stock-constrained periods.
What is the biggest mistake in retailer media reporting?
Comparing native ROAS across platforms without normalizing attribution, fees, returns and SKU economics.
Can FiveX support retailer-specific scorecards?
Yes. FiveX brings ad, marketplace, inventory and profitability signals together so retailer media decisions can be reviewed in one operating model.
CTA: Want retailer media scorecards that do not require spreadsheet yoga? Book a FiveX demo and we will walk through the profit view.