Shopify Products Scraper — Full Store Catalogs

Scrape the complete product catalog of any Shopify store — no API key, no login, no proxy. Just paste store URLs and get clean, structured JSON: titles, prices, variants, SKUs, stock flags, images and tags.

What it does

• Works on any Shopify-powered store (millions of them: fashion, beauty, electronics, supplements, home goods…)
• Extracts titles, descriptions, vendors, product types and tags
• Full variant data: SKU, price, compare-at price, stock availability, weight
• All product images with per-product image counts
• Price range per product (priceMin / priceMax) and in-stock flag
• Handles pagination automatically (up to 100,000 products per store)
• Resilient fetching — browser-grade TLS fingerprinting rides through the bot walls that block plain HTTP scrapers (added Jul 2026)
• Returns product creation/update/publish timestamps for change tracking

Use cases

• Price monitoring — track competitor pricing and discounts over time (run it daily on a Schedule)
• Dropshipping research — find winning products and suppliers
• Competitor analysis — full catalog snapshots of any store in your niche
• Market research — assortment breadth, price positioning, stock levels
• Feed generation — build product feeds for ads or affiliate sites
• Brand protection — spot unauthorized resellers carrying your SKUs

Input

{
  "storeUrls": ["allbirds.com", "https://colourpop.com"],
  "maxProductsPerStore": 100
}

Field	Type	Default	Description
storeUrls	array	required	Store domains or URLs — bare domain, homepage, or any deep link; the store is resolved automatically
maxProductsPerStore	integer	100	Cap per store, up to 100,000

Output

One dataset item per product:

{
  "storeDomain": "allbirds.com",
  "productId": 7292464955472,
  "title": "Men's Cruiser - Shadow Blue",
  "handle": "mens-cruiser-shadow-blue",
  "productUrl": "https://allbirds.com/products/mens-cruiser-shadow-blue",
  "description": "Lightweight everyday sneaker made from merino wool.",
  "vendor": "Allbirds",
  "productType": "Shoes",
  "tags": ["mens", "sneakers"],
  "priceMin": 120.0,
  "priceMax": 120.0,
  "available": true,
  "variantCount": 14,
  "variants": [
    {
      "id": 43220960985376,
      "title": "US 9 / Shadow Blue",
      "sku": "A11449M080",
      "price": 120.0,
      "compareAtPrice": null,
      "available": true,
      "grams": 340
    }
  ],
  "imageUrls": ["https://cdn.shopify.com/s/files/1/1104/4168/products/...jpg"],
  "imageCount": 6,
  "createdAt": "2024-08-28T10:00:00-07:00",
  "updatedAt": "2024-09-01T14:12:00-07:00",
  "publishedAt": "2024-08-28T10:00:00-07:00"
}

Every run's dataset exports as JSON, CSV, Excel or XML from Apify Console or the API. The variants array carries the full per-option breakdown (title, price, compareAtPrice, available, sku, grams) — ideal for inventory-style analysis without hitting the storefront again.

Real example — a 3-store price watch

Input:

{
  "storeUrls": ["allbirds.com", "colourpop.com", "gymshark.com"],
  "maxProductsPerStore": 500
}

Output: ~1,400 products across the three stores, each with live prices, availability and SKUs. Schedule this daily and you have a competitor price-tracking table — join on handle or sku to detect price drops, restocks and discontinued lines. At $0.001/product the whole daily snapshot costs about $1.40 in event fees.

Run it on a schedule or from your code

Point a Schedule at your competitor list for daily price snapshots, or call it from anywhere:

curl -X POST "https://api.apify.com/v2/acts/darknezz~shopify-products-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"storeUrls": ["allbirds.com"], "maxProductsPerStore": 200}'

The call returns the products directly as JSON — ideal for piping into a price tracker, spreadsheet, or LLM pipeline. Also available through the Apify SDK (Python/JS), Zapier/Make, and MCP-enabled AI agents.

# Python SDK
from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
result = client.actor("darknezz~shopify-products-scraper").call(
    run_input={"storeUrls": ["allbirds.com"], "maxProductsPerStore": 200})
items = client.dataset(result["defaultDatasetId"]).list_items().items

Pricing

Pay-per-event: $0.001 per product scraped, plus Apify's standard compute. A full 1,000-product catalog snapshot costs about $1 in event fees. No subscription, no minimum — you only pay for what you actually extract.

FAQ

How do I find out if a store runs on Shopify? Just try it — if the domain isn't a Shopify storefront the Actor logs it and moves on. (Checkout on myshopify.com, cdn.shopify.com assets, or a /products.json endpoint are the usual tells.)

Does it get sales numbers or product costs? No — those are private to the merchant. Everything public in the catalog (prices, variants, stock flags, images) is extracted.

What about collections or a single product? Paste any URL from the store — the Actor resolves the store and scrapes its catalog; use maxProductsPerStore to bound the run.

Which currency are prices in? The store's default storefront currency, exactly as the shop publishes it.

Can a store block scraping? A small minority disable the public catalog endpoint or password-protect the storefront — those stores are logged and skipped, never failing your whole run. Anti-bot walls (Cloudflare and similar) are handled by the browser-fingerprint fetcher, which survived the mid-2026 wave of plain-HTTP blocking.

How fresh is the data? Scraped live at run time. Schedule daily or hourly runs for time-series price tracking.

Does it respect maxProductsPerStore exactly? Yes — it stops pulling new pages for a store once the cap is reached, so you can bound cost tightly on large catalogs.

Can I track stock-outs? Yes. The available flag and per-variant available fields are live at scrape time; run twice daily and diff on productId to build a restock alert feed.

Limits & reliability

• Up to 100,000 products per store per run
• Multiple stores per run supported; failed stores are skipped, not fatal
• Resilient to rate limiting via the TLS-fingerprint fetch layer
• Retries on transient network errors with backoff