✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12
Amazon Seller Central generates dozens of report types: inventory health, business reports, FBA fee previews, advertising performance, and order data. These reports use different date formats, inconsistent column naming, and embed Amazon-internal codes that are meaningless outside the platform. dataclean.to consolidates and cleans your Seller Central exports into analysis-ready data.
The Problem
Seller Central reports use different date formats across report types (some ISO, some US locale). Settlement reports mix transaction types (orders, refunds, adjustments) in a single file. Inventory reports include FNSKU and ASIN columns that confuse non-Amazon tools. Fee columns contain negative values mixed with positive amounts. Merging multiple report types requires column name normalization that changes with each Amazon update. Amazon Seller Central reports reference
How to Fix It
1
Download Seller Central reports
Export the reports you need from Amazon Seller Central: All Orders, Inventory Health, FBA Inventory, Settlement, or Business Reports. Save each as a CSV or TSV file.
2
Upload reports to dataclean.to
Import one or more Seller Central report files. The platform identifies report types by their column structure and applies appropriate cleaning rules for each.
3
Normalize dates and identifiers
Convert all date columns to a consistent ISO 8601 format. Validate ASINs and SKU formats. Separate FNSKU from ASIN where both appear. Standardize order ID formatting.
4
Clean financial data
Separate positive and negative amounts in settlement reports. Convert fee columns to absolute values with proper signs. Normalize currency codes. Calculate net amounts per order.
5
Export analysis-ready data
Download cleaned reports as CSV or Excel files. The standardized format works in spreadsheets, accounting software, and business intelligence tools without further transformation.
Frequently Asked Questions
Can I merge multiple Seller Central report types?
dataclean.to cleans each report type individually based on its structure. You can then join them using order IDs or ASINs in your analysis tool. The platform ensures consistent ID formatting across reports for reliable joins.
How are FBA fees handled in the cleaning process?
FBA fee columns in settlement reports often use negative values. dataclean.to normalizes these to consistent signed numbers and can separate them into dedicated fee-type columns for clearer analysis.
What if Amazon changes their report format?
Amazon occasionally adds, removes, or renames columns in Seller Central reports. dataclean.to detects columns by content patterns rather than fixed names, so it handles format variations without breaking.
Example: Input → Output
name
email
phone
city
status
Alice Johnson
alice@example.com
+1-555-0101
New York
active
alice johnson
ALICE@EXAMPLE.COM
5550101
new york
Active
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.