Amazon Real-time Scraper

Scrape Amazon products, prices, offers, sellers, bestsellers, deals, influencer storefronts and customer reviews - all from one actor. Feed it ASINs, search keywords, seller IDs, influencer usernames or raw Amazon URLs, tick the data types you want, and export clean structured rows across 8 marketplaces. Cached responses come back fast (competitors scrape live at 3+ seconds); you pay only per result, no subscription.

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Why this Actor?

One Data Forge actor covers seven Amazon surfaces that most tools split across seven separate scrapers.

Capability	Data Forge Amazon Scraper	Typical Amazon actors
Data types in one actor	7 - products, reviews, offers, sellers, bestsellers, deals, influencers	1 surface per actor
Product 360 in a single run	Detail + reviews + offers together	Separate runs or actors
Search filters + price sorting	Sort, brand, price, rating, Prime, condition	Keyword only
Marketplaces	8 - US, UK, DE, FR, IT, ES, CA, JP	US only
Offers per ASIN	Every listed seller, incl. used / renewed resale	Buy Box only
Billing	Pay per result, error rows free	Monthly subscription

What this actor does

Feed it any mix of ASINs, search keywords, seller IDs, influencer usernames, or Amazon URLs, tick the data types you want, and it pulls up to seven verticals in one run:

• 📦 Products - search any keyword (paginated to your cap) or fetch a full product page by ASIN: title, price, list price, rating, review count, brand, variations, all images, bullet points, description, bestseller rank
• 📝 Reviews - hundreds of real customer reviews per product across all five star ratings (deduped, newest-first): rating, title, text, author, date, verified-purchase flag, Vine flag, helpful votes, country, photos
• 🏷 Offers - every seller offer for an ASIN: price, condition, seller, seller rating, Buy Box flag, ships-from, delivery
• 🏪 Sellers - merchant profiles: rating, rating count, positive-feedback %, business name and address, ships-from (plus the full feedback breakdown in the data payload)
• 🏆 Bestsellers / new releases - ranked category lists
• 🔥 Deals - lightning deals, coupons, premium-brand and Amazon-brand deals, filtered by department, discount % and Prime
• 🌟 Influencer storefronts - creator profiles and their recommended products

Flip on Fan out search results to full product detail and every search / category / seller-products result is enriched with its full product page. Flip on Also harvest reviews for every product and reviews are pulled for every ASIN you supply AND every product your searches return.

Already have specific pages? Paste them into Start URLs - a product, search, bestseller, new-releases, seller, offer-listing or reviews URL is auto-detected and parsed directly.

Input modes and examples

Pick the mix that matches your job. Each recipe below is ready to run - paste it into the input, or save it as a task.

1. Product 360 - detail + reviews + offers

For a brand, reseller or analyst auditing a single ASIN end to end: full spec sheet, hundreds of reviews, and every live seller offer in one run.

{
  "asins": ["B0DGHMNQ5Z"],
  "dataTypes": ["products", "reviews", "offers"],
  "includeReviews": true,
  "maxResultsPerType": 100
}

2. Market snapshot - search + full details

For a category researcher mapping a keyword's top listings with the full product page attached to each result.

{
  "searchQueries": ["air fryer"],
  "dataTypes": ["products"],
  "includeProductDetails": true,
  "maxResultsPerType": 40
}

3. Best sellers + new releases

For a trend spotter tracking what is ranking and what is newly launched in a category.

{
  "dataTypes": ["bestsellers"],
  "bestsellersCategory": "electronics",
  "includeNewReleases": true,
  "maxResultsPerType": 50
}

4. Lightning deals

For a deal hunter or repricer pulling live, time-limited discounts.

{
  "dataTypes": ["deals"],
  "dealsCategory": "lightning-deals",
  "maxResultsPerType": 100
}

Input

{
  "asins": ["B0FQFB8FMG"],
  "searchQueries": ["wireless earbuds"],
  "dataTypes": ["products", "reviews"],
  "country": "us",
  "maxResultsPerType": 20,
  "includeReviews": true,
  "reviewStarFilter": "all_stars",
  "reviewSort": "recent"
}

Field	What it does
ASINs	Product IDs to pull as full detail (and reviews, if requested).
Search queries	Keyword searches, paginated to the per-type cap.
Start URLs	Paste any Amazon URL (product / search / bestseller / seller / reviews) to parse directly.
Seller IDs	Merchant IDs to pull as seller profiles (+ their catalog, optionally).
Influencer usernames	Creator storefronts to pull as profile + recommended products.
Data types	Multi-select: products, reviews, offers, sellers, bestsellers, deals, influencers (default: all).
Country	Amazon marketplace: us, uk, de, fr, it, es, ca, jp.
Max results per type	Cap per vertical / input item. Search paginates Amazon to reach it.
Fan out to product detail	Enrich every listing result with its full product page. Extra charge per detail.
Also harvest reviews	Pull reviews for every ASIN and every searched product.
Review star filter / sort	all_stars / five_star / positive / critical, recent or helpful.
Search filters	Sort, category, brand, min/max price, min rating, Prime, condition.
Deals filters	Deal type, department, minimum discount %, Prime-exclusive.

Output

One flat row per result, discriminated by row_type, with the full payload under data. The dataset ships with six ready-made table tabs - Overview, Products, Reviews, Offers, Sellers, Influencers - so each vertical reads as a clean spreadsheet you can sort, filter and export to CSV / Excel / JSON in one click.

Every row is tagged with a row_type so you can split the verticals downstream:

row_type	What it is
search_result	One keyword-search listing item
product_detail	Full product page - specs, variations, all images, bestseller rank
review	One customer review - rating, title, text, author, verified-purchase, helpful votes
offer	One seller offer for an ASIN - price, condition, Buy Box flag, ships-from
seller_profile	Merchant profile - rating, feedback %, business name and address
seller_product	One product from a seller's own catalog
bestseller	One item from a category best-sellers list, with rank
new_release	One item from a category new-releases list
deal	One deal (lightning / coupon / brand), with discount %
influencer_profile	An influencer / creator storefront profile
influencer_product	One product a creator recommends

A real review row:

{
  "query": "B0FQFB8FMG",
  "row_type": "review",
  "asin": "B0FQFB8FMG",
  "review_title": "Best earbuds I've owned",
  "review_text": "Battery life is excellent and the noise cancelling is...",
  "review_rating": 5,
  "review_author": "Jordan M.",
  "review_date": "March 14, 2026",
  "verified_purchase": true,
  "vine": false,
  "helpful_count": 12,
  "review_country": "us",
  "data": { "...": "full review object" }
}

Console columns include asin, title, price, rating, review_count, url for products; review_rating, review_title, review_text, review_author, verified_purchase, helpful_count for reviews; price, condition, seller_name, is_buybox for offers; and seller / influencer columns on their tabs. Error rows carry an error_code and are free - you only pay for real results.

A run-summary record (OUTPUT key) reports per-vertical counts and the estimated cost. Live per-event pricing is shown on this actor's Apify Store page.

FAQ

Is scraping Amazon data legal? The actor collects only publicly visible information - product listings, prices, public reviews, seller pages, best-seller lists and deals - the same data any shopper sees in a browser. You decide how the output is used; keep it to public data and respect Amazon's terms and your local regulations.

How fresh is the data? Every run fetches live from Amazon at request time. Identical queries repeated within a short window can return from a fast cache in well under a second; anything not cached is pulled fresh.

What happens if an ASIN is dead or a page fails? You get a free diagnostic row carrying an error_code, and the run keeps going - one bad ASIN, seller or URL never aborts the whole job, and failed rows are never charged. Prefer to stop on the first failure instead? Set stopOnError: true.

Which Amazon marketplaces are supported? Eight: US, UK, DE, FR, IT, ES, CA and JP. Set country to choose one marketplace per run.

How many reviews do I get per product? Hundreds per product - a deep, deduped sample across the five star ratings, newest-first or most-helpful. It is a rich recent sample rather than a complete archive of a product's review history.

Should I use this umbrella actor or a focused one? Use this actor to pull several data types together, or a product 360 (detail + reviews + offers) in a single run. If you only ever need one surface, the focused Amazon Products and Amazon Reviews actors have a leaner input - see Related actors below.

Highlights

• 7 verticals in one run - products, reviews, offers, sellers, bestsellers, deals, influencers.
• Hundreds of reviews per product - across all five star ratings, deduped and newest-first, as structured rows.
• Fast cached responses - repeat queries return in well under a second; competitors scrape live at 3+ seconds.
• 8 marketplaces - us, uk, de, fr, it, es, ca, jp.
• Every search filter - sort, brand, price, rating, Prime, condition. No internal IDs to look up.
• ASINs, keywords or URLs - search a whole catalog, fetch exact products, or paste pages. All in one actor.
• Clean per-vertical tabs - export-ready tables, not a wall of mixed columns.
• You only pay for results - errors and your own misconfigurations are never charged.

Related actors

• Amazon Products Scraper - search + full product detail only, when you don't need the other verticals.
• Amazon Reviews Scraper - hundreds of customer reviews per ASIN, with a simpler review-only input.
• Walmart Intelligence Scraper - the same multi-vertical approach for Walmart product data.

Support

Need help, higher limits, or a custom scraper? I personally support every customer - reach out on any channel.