Amazon fees fell too, but only 6.1%.
The fee total went down. The problem was that sales fell much faster.
Fees as % of Sales increased from 39.0% to 59.4%.
A seller looking only at sales might see a slowdown.
A seller looking only at fees might see a lower fee total.
Neither view shows the full picture.
Margiyo analyzes the Amazon Payments Transaction Report to show how sales, fees, refunds, storage costs, and product-level activity are moving relative to each other.
Sales fell 38.3%. Amazon fees fell only 6.1%. Fees ended up taking a much larger share of every sales dollar.
Why can Amazon sales and profit tell different stories?
Because product sales are revenue, not profit.
One important question is how much of that revenue remains after selling fees, fulfillment costs, refunds, storage charges, and other Amazon-side activity.
In the example above, Amazon fees did not rise in dollars.
They fell from $835.87 to $784.75.
But sales fell much faster, so fees took a larger share of sales.
That is the signal.
It does not tell us, by itself, why the change happened. It tells us where to look next.
A seller may look at the fee total and think fees improved because the dollar amount went down.
The percentage-of-sales view tells a different story.
What should Amazon sellers look at besides sales?
The useful question is rarely just “Did this number go up or down?” It is usually “How did it move relative to sales?”
Fees as % of Sales
How much of product sales is going to Amazon fees?
Looking at the ratio makes it easier to see whether fees are moving in line with sales or taking a larger share over time.
Refunds as % of Sales
Refund dollars can rise or fall for many reasons.
What matters is also how they change relative to sales.
Storage costs relative to sales
Storage is another area where a dollar total can be misleading without context.
A cost may stay flat while sales decline, making it much more significant to the business.
Product-level cost patterns
Account-level numbers show that something changed.
Product-level activity can show where the change is concentrated.
That still does not prove the root cause, but it gives the seller a better place to investigate.
Why does percentage-of-sales context matter?
Because the same cost can mean very different things at different sales volumes.
In one Margiyo analysis, Storage & Inventory-related Amazon costs totaled $1,734.46:
- FBA Aged / Long-Term Storage: $929.98
- AWD Storage: $457.80
- FBA Monthly Storage: $346.68
The stronger signal was not just the dollar amount.
Those costs represented 24.3% of product sales during the analyzed period.
A $1,734 storage cost against $100,000 in sales is one situation.
The same $1,734 against roughly $7,000 in sales is another.
The cost did not change.
Its importance did.
This does not mean the storage cost was automatically avoidable.
The useful question is whether the amount and its relationship to sales make sense for the account.
Can sales growth still come with weaker economics?
Yes.
A separate historical Margiyo analysis showed:
- Sales: $867.96 → $16,664.03
- Sales growth: +1,819.9%
- Amazon fees growth: +2,224.5%
- Fees as % of Sales: 51.9% → 62.9%
Sales grew dramatically.
Amazon fees grew even faster.
So the seller generated far more revenue, but a larger share of that revenue was going to Amazon fees.
That does not tell us whether the business was profitable overall.
It does show that stronger sales did not automatically translate into stronger Amazon-side economics.
Understanding the composition of Amazon FBA fees is one part of that analysis.
Sales, payout, Amazon-side economics, and true profit are different numbers
Product sales
Product sales are revenue, not profit.
Money remaining after Amazon costs
This view shows what remains after the Amazon-side costs represented in the report. It is not complete business profit.
Payout
Payout does not equal profit.
True business profit
Complete profitability can also require:
- COGS
- advertising
- freight and inbound logistics
- software
- labor
- other operating expenses
That is an analytical boundary, not a shortcut.
How Margiyo analyzes Amazon economics
- Start with the signal.
- Compare relationships.
- Do not assume every large fee is a problem.
- Do not call every cost lost profit.
- Do not treat a change as proof of root cause.
- Say when more data is required.
Show what changed, show how the numbers relate, and help the seller ask a better next question.
That approach grew from real Amazon seller data and the operating questions behind Margiyo.