Use case
Catalog sync playbooks store-by-store
In-house ops: run Data Sync Google Sheets → Shopify imports on each store separately—map columns, preview, schedule—with row limits from that store’s plan.
Highlights
What you get out of this flow
Outcomes you can expect when you run this playbook on Shopify.
- One Google Sheet connection and mapping per Shopify store
- Preview before apply; never hard-delete—archive or zero inventory policies
- Row limits (1k / 5k) follow the plan on that store
Why not one sync for every store
Catalogs, vendors, and SKU conventions differ by brand. A single shared apply would overwrite the wrong store. EShopSet keeps Data Sync scoped to the store you enabled—repeat the playbook deliberately.
How it works in EShopSet
On store N: connect Google, pick spreadsheet/worksheet, map columns, choose match keys (SKU/handle/barcode/ID), set row policies, then manual preview/apply or schedule. Check Logs. Move to store N+1 with its own plan and sheet.
Example: shared supplier, two brands
Ops maintained one supplier workbook with BrandA and BrandB tabs. They ran Data Sync on Brand A’s store against tab A (Growth, hourly), then repeated on Brand B’s store against tab B (Starter, daily)—no cross-store overwrite.
Playbook
- Document sheet URL + tab name per store.
- Enable Data Sync; map and match keys.
- Preview; fix sheet errors; apply.
- Schedule only after a clean manual run.
- Review Logs after the first scheduled job on each store.
What to measure
- Preview vs apply error rate per store
- Rows processed vs plan row limit
- Time from sheet update to successful Logs run
