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Fiverr Pro
English
$
USD
I will clean your supplier product CSV and flag data errors
About this Gig
Messy supplier files can hide duplicate SKUs, inconsistent prices and missing product details.
This service cleans one product CSV using rules agreed with you: column mapping, whitespace cleanup, SKU preservation, price and stock formatting, and checks for missing values and duplicate identifiers.
You receive:
- A cleaned CSV and an Excel workbook
- A separate list of records that need your decision
- A change log and source-to-output record counts
The starter package covers one UTF-8 CSV, up to 100 product rows and 10 columns, using one currency and one agreed number format. One revision is included for the original scope.
Duplicates are flagged, not silently removed. Missing facts are never invented. Store uploads, variant restructuring, scraping and product copywriting are excluded. This is not a guarantee of Shopify import compatibility.
AI and deterministic scripts assist processing. Files are checked against the agreed rules. The gallery shows fictional sample data, not client results.
Please send an anonymized sample and your desired column layout before ordering.
FAQ
Do you need my store password or upload the file to my store?
No. I work on the product file you provide. Store access and publishing are excluded. The output is generic cleaned data, not automatically Shopify-import-ready; platform-specific mapping and a test import need a separate agreed scope.
What happens to duplicate SKUs and unclear prices or stock?
All records affected by duplicate SKUs are separated for your decision, not silently deleted. Ambiguous prices, currencies and stock values are flagged with a reason. I do not invent missing facts or convert currencies without agreed rules.
Do you use AI, and are the gallery samples real client results?
AI assists analysis and code; deterministic scripts process the data, with checks against agreed rules. Please provide product-only data and remove personal information. The gallery uses fictional sample data, not customer results or sales claims.
