Amazon Product Scraper for Prices, Specs, and Variants
Bring the whole Amazon product page into one table
Gather identifiers, specifications, variants, and linked details even when categories arrange them differently.
Begin with the fields this product exposes
One Click Extract recognizes details such as the title, ASIN, images, specifications, rating, and availability. Keep its suggestions or revise the request in plain English.
Cross categories without remapping the page
A book, a laptop, and a shirt do not share one specification layout. Thunderbit reads fields by meaning instead of relying on a selector map for each category.
Continue into the linked product details
Agent Mode can open accessible product links and append visible descriptions, sellers, variations, or ratings. Switch linked pages off when the current page already contains what you need.
Product research breaks when the scraper only knows one layout
Traditional rules encode page structure. Thunderbit AI reads the attributes the page is communicating.
Rules for every product layout
Category differences become maintenance workProduct fields chosen by Thunderbit AI
The workflow follows the informationWhat data can you extract with an Amazon product scraper?
Choose from 30 fields covering product details, prices, sellers, availability, images, specifications, ratings, and variations.
- Product description
- Average rating
- Review count
- ASIN
- Parent ASIN
- Amazon detail-page URL
- Product title
- Brand
- Manufacturer
- Feature bullets
- Item part number
- Model
- Warranty
- Color
- Item height
- Item length
- Item width
- Item weight
- Size
- Unit count
- Browse-node name
- Browse-node ancestry
- Primary image URL
- Current buying price
- Price currency
- Availability message
- Seller name
- Variation attribute name
- Variation attribute value
- Variation count
Watch real users put Thunderbit to work
These videos show how people use an AI web scraper inside practical research, operations, and data-collection workflows.
What to expect from an Amazon product-page scrape
Amazon product pages change by category, marketplace, seller, and selected variation, so the available details are not identical on every URL.
Split product research into the Amazon task you need
Move to a price, ASIN, or review scraper when your next question is narrower than the full product page.
No-Code Amazon Scraper for Products, Prices, and Reviews
Collect visible Amazon product names, ASINs, prices, sellers, availability, ratings, reviews, images, and more with One Click Extract. Thunderbit recommends the fields, follows linked pages when needed, and exports the results without code.
Learn more ->
Amazon Review Scraper
Collect visible Amazon review text, star ratings, dates, reviewer names, helpful votes, variations, and product details with One Click Extract. Customize the fields in plain English and export the reviews without code.
Learn more ->
Amazon Price Scraper
Track the Amazon prices a shopper can actually act on: the current offer, discount, seller, availability, and variation. Extract the page now, or schedule another check for later.
Learn more ->
Amazon ASIN Scraper
Create an Amazon identifier list from the products you are researching. Capture ASINs, parent ASINs, titles, product URLs, brands, and visible variant relationships without opening each listing by hand.
Learn more ->
BestPrice GR Scraper
Thunderbit's AI-powered BestPrice GR Scraper enables you to extract product listings, prices, and detailed information from BestPrice.gr in just a few clicks. Perfect for sales, marketing, and e-commerce teams looking to gather structured data quickly and efficiently.
Learn more ->
HKTVmall Scraper
Extract product names, prices, ratings, and more from HKTVmall listings in 2 clicks — no coding required. Export directly to Excel, Google Sheets, or Notion and turn HKTVmall data into actionable insights.
Learn more ->Ready to supercharge your data extraction?
Join 200,000+ professionals already using Thunderbit to automate their web scraping workflows.
Free trial provides unlimited credits for 8 webpages.
