Shopify Scraper — Products, Collections, Reviews & Emails

What is 🛍️ Shopify Scraper — Products, Collections, Reviews & Emails?

Use this Apify Actor to extract Shopify store data into one dataset, with each record representing one product, one collection, one customer review, or one merchant contact result. It accepts Shopify store URLs or bare domains, and it is designed for known stores rather than keyword discovery. The output can include product IDs, handles, URLs, titles, prices, compare-at prices, discounts, variants, images, review ratings, review counts, merchant email, phone, address, language, currency, and social links. The result is CRM-ready JSON that you can use in apps, pipelines, and Apify MCP workflows.

Best fit and connected workflows

This actor fits workflows where the input is already a specific Shopify store and the goal is structured data from that store.

It routes well into:

• product catalog export when you need titles, pricing, stock, variants, images, and product metadata
• collection mapping when you want categories, handles, descriptions, and product counts
• review analysis when you want star ratings, review text, verified buyer status, and helpful votes
• merchant lead capture when you want public contact details for outreach or account research
• scheduled monitoring when you want repeatable snapshots of the same store over time
• downstream enrichment or filtering by record_type in your own systems

Related Shopify workflows that connect naturally:

• Use Shopify Products Scraper for a more focused product-only step
• Use Shopify App Store Scraper when your next step is Shopify app research

Practical scenario

Maya, a sales operations specialist, starts with a known store domain, gymshark.com, and wants a contact record plus a small product sample for context. She enables scrapeContactInfo and scrapeProducts, then sets a product cap for a quick run.

The actor returns fields such as merchant_email, merchant_phone, store_currency, store_language, title, price, currency, available, and discount_percentage. Maya uses the merchant email to route the lead to the right account owner, then reviews the product pricing and availability before planning outreach.

Input

Field	Type	Purpose
storeUrls	array of strings	Shopify store URLs or bare domains for known stores
scrapeProducts	boolean	Extract product data from public Shopify catalog endpoints
scrapeCollections	boolean	Extract collection data from public Shopify collection endpoints
scrapeReviews	boolean	Extract customer reviews when a supported review platform is detected
scrapeContactInfo	boolean	Extract public merchant contact details from the store pages
maxProductsPerStore	integer	Upper bound for products per store
maxCollectionsPerStore	integer	Upper bound for collections per store
maxReviewsPerProduct	integer	Upper bound for reviews per product

Focused input example

{
  "storeUrls": [
    "https://www.allbirds.com",
    "gymshark.com"
  ],
  "scrapeProducts": true,
  "scrapeCollections": true,
  "scrapeReviews": false,
  "scrapeContactInfo": true,
  "maxProductsPerStore": 25,
  "maxCollectionsPerStore": 50,
  "maxReviewsPerProduct": 20
}

Output

Each dataset item includes record_type so you can filter records by product, collection, review, or contact.

Field	Type	Purpose
record_type	string	Record discriminator: product, collection, review, or contact
store_url	string	Full base URL of the Shopify store
store_domain	string	Hostname of the store
scraped_at	string	ISO 8601 extraction timestamp
source_url	string	Source page or endpoint used for the record
product_id	string or null	Shopify product ID for product records
product_handle	string or null	Shopify product slug
product_url	string or null	Direct product URL
title	string or null	Product title or collection title
vendor	string or null	Product vendor or brand
product_type	string or null	Product type from Shopify
tags	array or null	Product tags
description	string or null	Plain-text product description
price	number or null	Current lowest selling price
compare_at_price	number or null	Original price before discount
discount_percentage	number or null	Calculated discount value
currency	string or null	ISO 4217 currency code
available	boolean or null	Current availability status
variants_count	number or null	Number of variants
variants	array or null	Variant details such as SKU, barcode, and option values
images	array or null	Image URLs in store order
image_url	string or null	Main image URL
sku	string or null	SKU from the first variant
barcode	string or null	Barcode from the first variant
review_platform	string or null	Detected review platform
review_rating	number or null	Average review rating
review_count	number or null	Number of scraped reviews
created_at	string or null	Shopify creation timestamp
updated_at	string or null	Last update timestamp
published_at	string or null	Storefront publish timestamp
collection_id	string or null	Shopify collection ID
collection_handle	string or null	Collection slug
collection_title	string or null	Collection title
collection_description	string or null	Plain-text collection description
collection_image_url	string or null	Collection image URL
collection_product_count	number or null	Product count in collection
review_id	string or null	Review platform ID
reviewer_name	string or null	Review author name
review_title	string or null	Review headline
review_body	string or null	Full review text
review_date	string or null	Review submission date
review_star_rating	number or null	Individual star rating
verified_buyer	boolean or null	Verified buyer flag
helpful_votes	number or null	Helpful vote count
merchant_name	string or null	Store or merchant name
merchant_email	string or null	Public business email
merchant_phone	string or null	Public business phone number
merchant_address	string or null	Public business address
store_language	string or null	Store language code
store_currency	string or null	Store currency code
contact_page_url	string or null	Contact page URL
social_instagram	string or null	Instagram profile URL
social_facebook	string or null	Facebook page URL
social_twitter	string or null	Twitter or X profile URL
social_tiktok	string or null	TikTok profile URL
social_youtube	string or null	YouTube channel URL

Illustrative output record

{
  "record_type": "product",
  "store_url": "https://www.allbirds.com",
  "store_domain": "www.allbirds.com",
  "scraped_at": "2026-04-03T10:30:00.000Z",
  "source_url": "https://www.allbirds.com/products.json?limit=250&page=1",
  "product_id": "7234567890123",
  "product_handle": "mens-wool-runners",
  "product_url": "https://www.allbirds.com/products/mens-wool-runners",
  "title": "Men's Wool Runners",
  "vendor": "Allbirds",
  "product_type": "Shoes",
  "tags": [
    "mens",
    "running",
    "wool"
  ],
  "description": "Lightweight everyday shoes made with merino wool.",
  "price": 120,
  "compare_at_price": null,
  "discount_percentage": null,
  "currency": "USD",
  "available": true,
  "variants_count": 4,
  "variants": [
    {
      "variant_id": "41234567890",
      "title": "8 / Medium Grey",
      "sku": "M-WR-8-MGR",
      "price": 120,
      "available": true,
      "option1": "8",
      "option2": "Medium Grey"
    }
  ],
  "images": [
    "https://cdn.shopify.com/s/files/1/0001/product-main.jpg"
  ],
  "image_url": "https://cdn.shopify.com/s/files/1/0001/product-main.jpg",
  "sku": "M-WR-8-MGR",
  "barcode": "0123456789012",
  "review_platform": "yotpo",
  "review_rating": 4.8,
  "review_count": 2341,
  "created_at": "2023-06-01T00:00:00Z",
  "updated_at": "2026-03-20T14:30:00Z",
  "published_at": "2023-06-01T00:00:00Z"
}

How it works

The actor works from Shopify's public surfaces and store pages, using the implementation facts provided in the contract:

• product data from /products.json
• collection data from /collections.json
• store metadata from public store pages and metadata surfaces
• contact details from public contact and footer pages
• social links from the homepage footer
• review data from detected review platforms such as Judge.me and Yotpo

The output uses a single dataset schema with a record_type field so you can separate products, collections, reviews, and contact records in downstream processing.

Pricing

Startup billing and empty runs

The apify-actor-start event costs $0.00005 per startup unit. Apify charges one startup unit per GB of allocated memory, with a minimum of one unit, so a 2 GB run incurs two units. This startup charge still applies when input is invalid, no results are found, or an upstream request fails. Statements about free, unbilled, or skipped results refer only to the corresponding result event; they do not waive the startup charge. Apify platform usage is included in the event prices and is not passed through as an additional customer charge. Check the live Pricing tab for current events, tiers, and rates. Result limits cap result events, not the entire run cost.

This actor uses Pay per event pricing on Apify. Each extracted record type maps to an event, and Apify platform usage is included in the event price. For the current breakdown and total run cost, open the actor's Pricing tab in Apify Console.

A simple example in words: if you scrape one hundred products, the product event is charged one hundred times; if you also scrape one contact record for that store, the contact event is charged once; if you add twenty reviews, the review event is charged twenty times.

Use with AI agents (MCP)

This Actor is usable through Apify MCP, so an AI agent can call it as a tool to gather Shopify store data before reasoning, enrichment, routing, or follow-up actions.

Tool description: extract Shopify product, collection, review, and merchant contact records from a known store domain or URL, then return structured dataset items for filtering by record_type.

Exact Actor identity: khadinakbar/shopify-all-in-one-scraper

Scrape the Shopify store www.allbirds.com for products and merchant contact info. Return the dataset items, then separate product records from contact records by record_type. Keep the result in structured JSON and include the source URLs for traceability.

Output interpretation: use record_type first, then read the fields that match that record family. For example, product records center on title, price, currency, available, and variants, while contact records center on merchant_email, merchant_phone, merchant_address, and social links.

Provenance: each item includes source_url and scraped_at, which makes it easier to trace where the record came from and when it was extracted.

Scope: use storeUrls for stores you already know. This actor is designed for direct store targets rather than keyword discovery.

Pagination and cost guidance: product and collection extraction is governed by the per-store caps in the input, while review volume is governed by maxReviewsPerProduct. Because pricing is event-based, raising the cap increases the number of billable records.

Apify API example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN || 'YOUR_APIFY_TOKEN',
});

const run = await client.actor('khadinakbar/shopify-all-in-one-scraper').call({
  storeUrls: ['https://www.allbirds.com'],
  scrapeProducts: true,
  scrapeCollections: true,
  scrapeReviews: false,
  scrapeContactInfo: true,
  maxProductsPerStore: 10,
  maxCollectionsPerStore: 10,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
const products = items.filter((item) => item.record_type === 'product');
const contacts = items.filter((item) => item.record_type === 'contact');

console.log(`Products: ${products.length}`);
console.log(`Contacts: ${contacts.length}`);
console.log(items);

Best results and outcome guidance

Start with a known Shopify domain or full store URL, then enable only the record types you need for the current task. Use smaller caps for sampling and larger caps when you want fuller catalog coverage. For lead generation, pair scrapeContactInfo with a small product sample so you have both outreach data and store context. For analysis workflows, filter the dataset by record_type before transforming or exporting the records.

Continue the workflow

• Then use Shopify Products Scraper to extend 🛍️ Shopify Scraper — Products, Collections, Reviews & Emails research with a complementary content contract.
• Then use Target Product Reviews Scraper & Ratings to extend 🛍️ Shopify Scraper — Products, Collections, Reviews & Emails with a neighboring commerce research source when the brief calls for Target data.

Design note

I found that the dataset contract uses a single shared schema with record_type as the discriminator, which makes it practical to mix products, collections, reviews, and contact records in one run and still separate them cleanly downstream.

FAQ

Can I send multiple Shopify stores in one run?
Yes. Add multiple URLs or domains to storeUrls and process them together.

Which input field is the suitable fit for a known store domain?
Use storeUrls for a specific Shopify store you already identified.

How do I get only product rows from the dataset?
Filter results where record_type equals product.

How do I get merchant contact records for outreach?
Enable scrapeContactInfo and filter dataset items where record_type equals contact.

How do I connect this with a product-only Shopify step?
Use Shopify Products Scraper when a later workflow needs a narrower product export.

How do I connect this with Shopify app research?
Use Shopify App Store Scraper when the next step is app discovery or app-store analysis.

Responsible use

Use this actor on stores you are authorized to review and on public pages that are available for access. Review the live Pricing tab before running larger jobs so you can match the input caps to your intended budget and data volume. When exporting contact information, keep outreach aligned with your internal policies and applicable laws.