Like most sellers, I knew my sales. I could see orders, payouts, fees, refunds, storage charges, and reports full of transaction detail.
The problem wasn’t a lack of data.
I had plenty of it.
I didn’t need more Amazon data. I needed the data I already had to make more sense.
That is where Margiyo started.
The numbers were there. The relationship wasn’t obvious.
While reviewing my own Amazon account, I compared two similar 60-day periods.
Sales had fallen 38.3%.
Amazon fees had fallen too, but only 6.1%.
Looking at either number alone would have told a reasonable story:
Sales were down.
Fees were down.
But together they told a different one.
Amazon was charging fewer fee dollars than before, yet those fees were taking a much larger share of every sales dollar.
That was the part I cared about.
Not another total.
Not another dashboard.
The relationship between the numbers.
Then storage changed an inventory decision
The same analysis showed that storage and inventory-related Amazon costs represented 24.3% of product sales during the period I was reviewing.
A large storage number by itself would not have told me much.
Twenty-four percent of sales did.
It made me look differently at inventory I was carrying into the next selling season and question whether every product deserved the same inventory strategy.
Margiyo did not tell me that all of that storage cost was unnecessary.
The data could not prove that.
It told me something more useful:
This deserves a closer look.
That distinction became important to how I wanted Margiyo to work.
I was already used to asking these kinds of questions
My professional background is in business analysis, business transformation, data, and technology.
A large part of that work has always been taking complicated systems and turning them into questions people can actually make decisions from:
- What changed?
- What matters?
- Where is the process behaving differently?
- What deserves attention?
- What information is still missing before we can make a conclusion?
When I looked at Amazon’s transaction data, the problem felt familiar.
The information existed.
It just wasn’t organized around the questions I wanted to ask as a seller.
Margiyo grew from combining those two perspectives: business analysis and actual Amazon selling.
Not every large Amazon fee is a problem
This is an important part of Margiyo.
A large storage fee does not automatically mean inventory was managed badly.
A high refund total does not automatically mean a product has a refund problem.
Fees becoming a larger percentage of sales tells us that something changed. It does not automatically tell us why.
And a number that looks unusual is not automatically “lost profit.”
I would rather show a real pattern and explain its limits than turn every number into a dramatic claim.
Margiyo shows the signal first. It only goes further when the data supports it.
The goal is not another Amazon dashboard
Sellers already have dashboards.
They already have reports.
They already have more numbers than they probably want to look at.
Margiyo is being built to make the relationships inside those numbers easier to see.
Sometimes one Amazon Payments Transaction Report is enough to answer the first question.
Other questions need more context: inventory data, advertising, COGS, return reasons, or additional Amazon reports.
That is fine.
A useful analysis should know the difference between what the data shows and what still needs to be investigated.
Better visibility should lead to better questions
The first version of Margiyo starts with Amazon-side costs:
- fees
- refunds
- fulfillment
- storage
- product-level cost patterns
- how those numbers are changing relative to sales
The objective is not to declare every unusual number a problem.
It is to help a seller recognize where the business deserves another look.
Because sometimes the most valuable finding is not an answer.
It is realizing you have been asking the wrong question.
Built by a seller, for the numbers sellers actually have
Margiyo is an independent product built from real Amazon seller data and real operating questions.
It is not affiliated with Amazon.
The Free Snapshot works from an Amazon Payments Transaction Report and analyzes the CSV locally in your browser.
No Seller Central connection is required.