An advertising report should help you decide what to do next. A page of green arrows cannot tell you whether a campaign earned its budget, whether product costs changed, or whether a profitable month depended on one unusually strong ASIN.
In his reporting breakdowns, Alfredo Roselli starts outside the campaign dashboard. He looks at the business trend, then connects advertising to units, revenue and product economics. This guide follows that sequence. It is a review framework you can use with an agency report or a spreadsheet; it does not require another dashboard subscription.
Agree on the question before reviewing the numbers
Write down the account's current objective. Are you protecting contribution, introducing a product, or increasing sales within a spending limit? The same increase in advertising cost can be acceptable for a planned launch and unacceptable for an established product whose sales are flat.
Give the report a consistent date range, marketplace, currency and product scope. Record when it was exported and whether recent advertising conversions are still developing. Amazon explains that attribution metrics remain incomplete until the lookback window ends. Compare like periods and add seasonal context. A holiday week and the following January week are not a clean performance experiment.
Start with sales, units and the selling price
Read revenue alongside units and orders. Revenue can rise because more people bought, because prices increased, or because shoppers bought a different mix of products. Each explanation changes the advertising decision.
For example, $30,000 from 1,000 units gives $30 revenue per unit. Next period, $33,000 from the same 1,000 units gives $33 per unit. Revenue grew 10%, but unit volume did not. Check prices and product mix before describing the change as stronger demand. Revenue divided by units is average selling price per unit; revenue divided by orders is average order value. Label them separately.
Connect advertising efficiency to the business
| Measure | Question it helps answer |
|---|---|
| Ad spend | How much did we invest, and where? |
| ACOS | How does spend compare with attributed ad sales? |
| TACOS | How does spend compare with total sales? |
| Contribution after ads | What remains after the variable costs included in our model? |
| Ad-attributed sales share | Is more of our reported revenue receiving advertising credit? |
Use product-specific ACOS targets rather than one number for the whole catalog. Then ask whether total contribution dollars and contribution per order support the campaign result. A lower ACOS with fewer profitable orders can still be an undesirable outcome.
Read Amazon ads attribution before reconciling advertising and sales exports. Different reporting scopes and crediting rules can create apparent discrepancies. A rise in attributed revenue is not, on its own, evidence that advertising created that much additional demand.
Investigate the cost lines that changed
In Alfredo's P&L walkthrough, refund costs remained relatively steady while revenue fell after the holiday period. That made refunds a larger share of current revenue. The useful finding was in the relationship between the lines, not the advertising ratio alone.
Make a short bridge from last period's contribution to this period's. Separate changes in selling price, units, product mix, cost of goods, fees, discounts, refunds and advertising. Check when costs posted before blaming a new campaign. Refunds recorded this month can relate to earlier sales; the exact treatment depends on your reporting method.
Keep gross and net revenue definitions explicit. If refunds or discounts already reduce your revenue line, do not subtract them a second time. Use the same treatment in both comparison periods.
Look below the portfolio average
Start with the products responsible for most contribution and the products with the largest changes. Do not automatically begin with the campaign that has the worst-looking percentage. A tiny campaign and a major product decline have different financial consequences.
Add three monthly checks to your weekly review: advertising dependency, catalog concentration, and cost and margin drift. Together they test whether the headline result hides rising dependence on ads, fewer dependable products, or higher selling costs.
End the report with a decision log
Every important finding should produce a proposed action or a deliberate decision to wait. Record the evidence, the explanation you are testing, the person responsible, and the next review date.
- Observation: Product A's revenue is steady, but its contribution fell.
- Check: Separate increased ad spend from refunds and fulfillment costs.
- Action: Correct the cost input or adjust the identified spending segment after checking conversion maturity.
- Guardrail: Monitor contribution dollars, orders and inventory while the change runs.
A useful report can say that the evidence is incomplete. That is better than attaching a confident explanation to every movement. The next report should revisit the decision log and show what happened, not simply replace last week's charts with new ones.
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