Use case
Map sheet columns to Shopify fields
Map Google Sheet columns to Shopify handle, title, SKU, price, inventory, and images in Data Sync before the first sync to avoid mismatched products.
Highlights
What you get out of this flow
Outcomes you can expect when you run this playbook on Shopify.
- Map handle, title, SKU, price, inventory, images deliberately
- Prevent duplicate products from weak identity keys
- Document the mapping so agencies and freelancers don’t drift
Why mapping is pillar setup
Sheets are flexible; Shopify is strict. Ambiguous identity (title-only matching) creates duplicates. Over-mapping description columns can overwrite carefully written PDP copy on every sync. Treat mapping as a published internal standard.
How it works in EShopSet
In Data Sync Settings, map each sheet column to a Shopify field. Prefer stable keys (handle or SKU). Leave rich merchandising fields unmapped if Shopify remains the source of truth—combine with price/inventory-only policy when needed.
Example: multi-warehouse sheet
A brand maintained warehouse_A_qty and warehouse_B_qty columns. They mapped a computed inventory column (SUM) to Shopify inventory and kept warehouse columns unmapped. Preview then showed clean updates without creating phantom products from warehouse codes mistaken as SKUs.
Playbook
- Define the identity column (handle recommended for existing catalogs).
- Map price and inventory next; validate types (numbers, not text).
- Decide which content fields Shopify owns vs sheet owns.
- Save mapping; run preview on a 50-row sample tab first.
- Document mapping in the sheet header row comments for the team.
What to measure
- Duplicate product creates after first mapped sync (target 0)
- Fields unexpectedly overwritten (audit 10 PDPs)
