Amazon Data Scraper — Search, Products, Best Sellers & More
Pricing
Pay per event
Amazon Data Scraper — Search, Products, Best Sellers & More
Scrape Amazon without code: search results, full product details, best sellers, new releases, seller storefronts, and keyword ideas — all in one actor, across 20+ countries. Clean JSON/CSV/Excel. Fast, and you pay only for the results you actually get.
Pricing
Pay per event
Rating
5.0
(3)
Developer
Automation Craft
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
4 days ago
Last modified
Categories
Share
Get Amazon data as a clean spreadsheet or JSON file — no coding needed. Pick what you want (a mode), enter a keyword / product / category, and press start. Works on 20+ Amazon country sites, and you only pay for results you actually get — if Amazon blocks a page, it costs you nothing.
Other tools make you rent a separate scraper for search, another for products, another for best sellers. This is one tool that does all six.
✅ What this can do
Pull Amazon's public catalogue data — the things you can see on Amazon without logging in:
- product listings and prices, ratings and review counts, images, brand, best-seller rank, availability, seller info, keyword ideas, and more.
❌ What this cannot do
- It does not download the text of customer reviews. Amazon hides full reviews behind a login, so no tool can reliably scrape review text. You do get each product's star rating and number of reviews — just not the written review paragraphs. (If you only need ratings + counts, this tool has you covered.)
- It does not access anything private (orders, seller dashboards, buyer info) — only public pages.
Modes (pick one per run)
| Mode | What you get | Give it |
|---|---|---|
| Search | Product cards for a keyword: title, price, list price, rating, review count, image, Prime, sponsored flag, ASIN | Search terms |
| Product detail | Everything for specific products: title, brand, price, rating, review count, availability, Best Sellers Rank, feature bullets, all images, full spec table | ASINs or product URLs |
| Best sellers | A category's Best Sellers ranking (rank, ASIN, title, price, rating, review count) | Category |
| New releases | A category's newest products | Category |
| Seller storefront | Every product a seller lists | Seller IDs |
| Keyword suggestions | Amazon's autocomplete completions for a prefix (great for keyword research / PPC) | Search terms |
Quick examples
Search amazon.com for "wireless headphones" (first 2 pages):
{ "mode": "search", "search": ["wireless headphones"], "marketplace": "com", "maxPagesPerQuery": 2 }
Full detail for two products:
{ "mode": "product", "asins": ["B09XS7JWHH", "https://www.amazon.co.uk/dp/B08N5WRWNW"] }
Top 100 best-selling electronics in India:
{ "mode": "bestsellers", "category": ["electronics"], "marketplace": "in", "maxItems": 100, "maxPagesPerQuery": 4 }
Every product from a seller's storefront:
{ "mode": "seller", "sellerIds": ["A2L77EE7U53NWQ"], "marketplace": "com", "maxPagesPerQuery": 5 }
Keyword ideas for PPC:
{ "mode": "suggestions", "search": ["wireless head", "yoga"], "marketplace": "com" }
Input fields
mode— which data type to scrape (see the table). Each mode uses one input field:- Search / Keyword suggestions →
search(list of keywords) - Product detail →
asins(ASINs or full product URLs; a URL's marketplace wins) - Best sellers / New releases →
category(a slug likeelectronics,books,toys-and-games, or a full best-sellers URL) - Seller storefront →
sellerIds(the value afterseller=/me=in a storefront URL)
- Search / Keyword suggestions →
marketplace— which Amazon site (com,co.uk,de,in, … 20 total). A full product URL overrides it.maxItems— hard cap on total result rows (cost control).maxPagesPerQuery— how many pages to follow for Search / Seller / Best sellers / New releases (each page is ~16–60 items). Ignored by Product detail and Keyword suggestions.maxConcurrency— parallel requests.proxyConfiguration— residential proxy by default (strongly recommended; Amazon blocks datacenter IPs).
Output
One row per result in the dataset, tagged with type (search / product / bestsellers / new-release / seller / suggestion) so you can filter mixed exports. Prices are returned both as a number (price) and with the currency symbol; ratings as a 0–5 number; review counts as integers.
Filter the dataset view by type for a clean per-mode table, or export the whole run as JSON/CSV/Excel.
Reliability
- HTTP-based (no browser) → fast and cheap.
- Every request is isolated — one product failing never corrupts another's result (a common bug in other Amazon actors).
- Amazon occasionally rate-limits or serves a bot check; the actor retries on a fresh proxy session automatically. If a page stays blocked after retries, it's reported as an
errorrow and — because billing is pay-per-result — it costs you nothing. - Residential proxies are the default and give the best success rate. Datacenter IPs get blocked quickly; not recommended.
Pricing (pay-per-result)
| Event | Price |
|---|---|
| Actor start | $0.01 per run |
| Result (Search / Best sellers / New releases / Seller / Suggestions) | $0.002 each |
| Product detail (full record) | $0.0075 each |
You are charged only for results actually returned. A run that gets blocked and returns nothing costs only the actor-start fee.
Notes & limits
- This scrapes public Amazon listing/catalog data. It does not scrape individual review text (Amazon login-walls full reviews) — a product's average rating and review count are included, but not the review bodies.
- Price is returned for the vast majority of products. A small number legitimately have no price (pre-orders, "see buying options", currently-unavailable items), and Amazon occasionally serves a page variant where the price is loaded dynamically — Product mode automatically re-fetches to recover it, but
pricecan still benullin those cases. All other fields are unaffected. - Category slugs vary by marketplace — copy them from the Best Sellers URL on the marketplace you're targeting.
- Respect Amazon's Terms of Service and applicable laws; you are responsible for how you use scraped data.