Price Drop & Restock Tracker for Shopify & WooCommerce

Put any Shopify or WooCommerce store on a schedule and get only what changed since the last run: price drops, price increases, back in stock, sold out, new and removed products. $0.20 per 1,000 products checked + $1 per 1,000 changes.

No full catalog dumps to diff yourself. The Actor remembers each store's last state and saves one row per change, with old and new values side by side.

Quick start

1. Press Start. The form is already filled with this example input, so the first run returns real rows in under a minute:

{
  "stores": [
    "allbirds.com",
    "porterandyork.com"
  ],
  "maxProductsPerStore": 200
}

2. Swap in your own values, or call the Actor through the Apify API, Make, Zapier, n8n or the Python/JS clients with the same JSON.
3. Download the results as JSON, CSV or Excel from the Output tab, or schedule the run to repeat.

Sample change row (real run)

{
  "changeType": "price_drop",
  "store": "allbirds.com",
  "platform": "shopify",
  "productTitle": "Women's Allbirds Flip Flop - Dusty Pink",
  "variantTitle": "5",
  "sku": "A12513W050",
  "url": "https://allbirds.com/products/womens-allbirds-flip-flop-dusty-pink?variant=42146889039952",
  "currency": "USD",
  "oldPrice": 31.25,
  "newPrice": 25,
  "priceChangePercent": -20,
  "wasInStock": true,
  "isInStock": false,
  "compareAtPrice": 50,
  "previousCheckedAt": "2026-10-27T08:07:43.680Z",
  "checkedAt": "2026-10-27T08:08:19.914Z"
}

Change types: price_drop, price_increase, back_in_stock, out_of_stock, new_product, removed. When a store has nothing to report, you get one free status row (baseline_saved or no_changes) with the number of products checked; turn this off with Add a status row when nothing changed. Shopify is tracked per variant (size/colour), WooCommerce per product.

How it works

1. First run of a watchlist saves a baseline and adds one free baseline_saved row per store (you pay only for products checked).
2. Every later run compares with the previous one and saves only the changes you asked for.
3. Run summaries (in the RUN_SUMMARY record) list per store: platform, products checked, changes found, and whether the whole catalog was read.

removed is only reported when the whole catalog was read without errors, so a hiccup or a product cap never creates false "removed" alerts.

Who uses this

• Brands and retailers: know the day a competitor discounts or restocks.
• Resellers and deal sites: catch price drops and restocks across many stores.
• Analysts: build a clean history of price and stock moves.

How to use it

1. Add store domains (platform is detected automatically).
2. Pick the changes to report and an optional minimum price change %.
3. Give the watchlist a name and add a Schedule (e.g. every 6 hours). Connect a webhook, Slack, email, Make, Zapier or n8n to the run to get alerts.

Use different watchlist names for separate schedules or clients; each keeps its own memory.

Pricing

• Product checked: $0.20 per 1,000 (Silver $0.18, Gold $0.16)
• Change found: $1.00 per 1,000 (Silver $0.90, Gold $0.80)
• Plus $0.00005 per run. No per-store fee. Stores that can't be read are free.

Example: 5 stores x 1,000 products, checked daily for 30 days = 150,000 checks = $30, plus $1 per 1,000 changes.

FAQ

Does it see stock quantities? No, only in stock yes/no, which is what stores publish publicly.

What if a store has 20,000 products? Set Max products per store to 0 for the whole catalog, or cap it to cut cost (removed alerts are then skipped for that store).

Is it legal?

This Actor only reads pages and feeds that the website itself publishes to every visitor without a login. It obeys each site's robots.txt, keeps a polite request rate, and never tries to get past logins, paywalls, captchas or bot checks. It does not collect personal data such as emails, phone numbers or names of private individuals. You are responsible for how you use the data: follow the source site's terms, copyright and the privacy laws that apply to you (GDPR, CCPA, etc.). This tool is independent and not affiliated with or endorsed by the platforms it reads.