Shopify Catalog Monitor & QA

Monitor any public Shopify storefront, detect catalog changes, flag QA issues, and export variant-ready data for BI, alerts, and RAG workflows.

Unofficial tool. This Actor is not affiliated with, endorsed by, or sponsored by Shopify.

This Actor is built for teams that need more than a raw Shopify dump. It turns a storefront snapshot into structured outputs you can use immediately:

• one normalized row per variant or SKU
• change detection against a saved baseline
• catalog QA summaries
• CSV and JSON outputs ready for downstream automation

Who this is for

• Shopify store operators who want a daily catalog health check
• agencies managing multiple Shopify clients
• BI and data teams that need a clean storefront feed
• teams building alerts, internal dashboards, or RAG ingestion pipelines

What it does

Input:

• storeUrl
• mode: snapshot or monitor
• includeProductHtml
• baselineUrl or inline baselineItems
• baselineStoreName
• webhookUrl
• maxProducts
• requestTimeoutSecs

Output:

• default dataset with one normalized row per variant
• RUN_MANIFEST with product and variant counts
• QA_SUMMARY with data-quality signals and samples
• DIFF_SUMMARY with changes against the previous baseline
• CATALOG_ROWS.csv for export workflows

In monitor mode, the Actor stores the latest normalized rows in a named key-value store so the next run can compare automatically without extra setup.

Why teams use it

• recurring catalog monitoring instead of one-off exports
• QA checks for SKU, pricing, availability, and catalog hygiene issues
• variant-level outputs ready for BI, alerts, spreadsheets, and AI workflows
• baseline diffs that make daily changes easy to review

Typical use cases

• daily catalog checks for price and availability changes
• QA detection for missing SKUs, duplicate SKUs, and incomplete product metadata
• normalized storefront feed for internal analytics
• baseline diffs before ad launches, promotions, or seasonal drops
• export clean variant data to spreadsheets, dashboards, or AI pipelines

Variant-level outputs

The default dataset is variant-level by design, so a store can produce more rows than products.

This is intentional because monitoring, pricing, stock, and SKU QA make more sense at the sellable-variant level.

The RUN_MANIFEST keeps both counts so the user can see products and variants clearly in every run.

Quick start

1. Enter the Shopify storefront URL.
2. Choose snapshot for a one-time export or monitor for ongoing change detection.
3. Run the Actor once to seed the baseline.
4. Run it again or schedule it daily to start receiving diffs.

Recommended first input:

{
  "storeUrl": "https://canvasinkcol.com",
  "mode": "monitor",
  "includeProductHtml": false,
  "requestTimeoutSecs": 30
}

Current scope

• public Shopify storefronts via products.json
• normalization to one row per variant
• baseline persistence for monitoring mode
• QA summaries
• CSV export
• webhook summary delivery

Out of scope in the current version:

• Shopify Admin API auth
• browser automation
• vendor-specific enrichments
• full historical warehousing outside Apify

Notes

This Actor is intentionally focused on public Shopify storefront monitoring, baseline diffs, and export-ready outputs.

If you need custom integrations, downstream syncs, or a more tailored workflow for your catalog operations, the public version can serve as a starting point.