PRACTICAL CSV GUIDES · UPDATED SEPTEMBER 23, 2026
What a scoped CSV cleanup delivery looks like
Demonstration only. These are fictional products, not a client case study. No real Shopify import, customer result or revenue is claimed.
The example starts with a small supplier spreadsheet using custom column names and dollar-prefixed prices. We map the agreed fields, preserve SKU strings and record each change.
Four files, one clear handoff.
- Original supplier file — the input is preserved.
- Mapped product CSV — edited output for further review.
- Field mapping and assumptions — how each source field is interpreted.
- Change and verification report — edits, checks and remaining limitations.
See the difference.
| Source | Output | Reason |
|---|---|---|
| product_name | Title | Map agreed source field |
| item_code: 00124 | SKU: 00124 | Preserve leading zeros |
| usd_price: $24.00 | Price: 24.00 | Normalize confirmed USD amount |
| No status field | Status: draft | Demonstration assumption, not an automatic production default |
What the $99 starting scope covers.
One file with up to 500 product records, agreed field mapping and formatting corrections, an output CSV, a change log, and one correction round within the agreed scope. More complex variants or ambiguous source values may require a different quote.
The initial review confirms whether the work fits, the final price, delivery date and acceptance checklist. Store import, entire-store migration, image sourcing, copywriting and ongoing synchronisation are not included unless separately agreed.
What “finished” means.
Input and output record counts are reconciled, agreed mappings are documented, spot checks cover representative records, and unresolved questions are explicit. Passing RowReady’s limited checker is one check, not complete Shopify import acceptance. No order is placed through this demo.
Check your CSV → Ask about cleanup
Source: Shopify’s product CSV documentation, reviewed September 23, 2026.