Shopify Store Scraper — brand profiles, not just products

Get a complete profile of any Shopify store: how big the catalogue is, where it prices, how heavily it discounts, and how fast it publishes new products. Plus the full product catalogue if you want it.

Point it at a list of domains and get one comparable row per brand.

Why this is different

Every other Shopify scraper fetches the product feed and hands you a dump. That is fine if you want products. It is useless if you want to evaluate a brand.

Nobody buying this data actually wants products. App vendors want to know which stores are big enough to sell to. Wholesalers want to know where a brand prices. Agencies want to know who is growing. Investors want catalogue velocity.

This actor answers those questions directly:

Signal	What it tells you
Product and variant count	Catalogue depth, and whether they are a real operation
Price min / median / max	Where they actually sit in the market
Price positioning	Budget, mid-market, premium or luxury
Discount share	Percentage of catalogue on sale — a permanently high number means a discount-led brand
New products last 30 / 90 days	Whether they are actively trading or dormant
Monthly publish rate	The growth signal, in one number
Top product types, vendors, tags	What they actually sell

Median, not mean

Price positioning uses the median, not the average. One £5,000 outlier in a £35 catalogue would drag a mean into "luxury" and mislabel the brand entirely. The median resists that. Small detail, and it is the difference between a usable dataset and a misleading one.

Honest discount detection

A product counts as on sale only when its compare-at price genuinely exceeds its price. Many stores leave compare-at set equal to price, which naive scrapers count as a discount and inflate the number.

Input

{
  "domains": ["allbirds.com", "gymshark.com"],
  "includeProfile": true,
  "includeProducts": false
}

Paste bare domains or full URLs — https://www.allbirds.com/collections/mens normalises to allbirds.com automatically.

Set includeProducts: false for a fast, tiny dataset when you only want to compare brands. Set maxProductsPerStore to cap large catalogues.

Use cases

• Shopify app and SaaS sales — qualify stores by catalogue size and price band before you pitch
• Wholesale and dropshipping — find brands at the right price point
• Competitive analysis — track a rival's pricing, discounting and launch cadence
• Agency prospecting — a store publishing 40 products a month has budget; one publishing zero does not
• Market research — profile an entire category in one run

Reliability

One store failing never fails the run. Point it at 200 domains and the handful that are password-protected or not on Shopify come back as a clear record of what failed and why — you keep the rest. You are only charged for rows actually returned.

Stores that are not Shopify get an explicit message saying so, rather than an empty result you have to diagnose yourself.

Data comes from the public JSON endpoints Shopify exposes by default on every store. No login, no browser automation, no session.

Notes

Price bands are currency-naive — compare stores in the same currency. The currency is included on every profile row so you can group correctly.

Unofficial and not affiliated with Shopify. Product data belongs to the respective stores; use it in line with applicable laws and terms.