AI-Powered Web Scraping

Rakuten Scraper for Products, Prices, and Points

Turn visible Rakuten products, prices, point offers, shop details, shipping information, ratings, and stock notes into a table with One Click Extract. Adjust the fields in plain English and export the result without code.

Need more ways to scrape at scale?

A quick playground: Try it yourself.

Read Rakuten as a collection of shop offers, not just product cards

Keep the price beside the points, coupon, delivery terms, and shop that give the number meaning.

Separate the numbers that change the deal

A Rakuten card can place price, points, coupons, and delivery signals side by side. One Click Extract recommends columns for the page in front of you; plain-English instructions let you keep each part of the offer distinct.

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Let the item page finish the row

When the listing leaves out the shop, shipping conditions, variation, rating, or stock note, Agent Mode can open the accessible item link and add what is visible. Linked pages are on by default and can be switched off.

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Turn a shortlist of URLs into a comparison sheet

Paste the Rakuten pages already shortlisted by your team and name the evidence the sheet needs. Thunderbit collects the accessible values into matching columns, so each shop offer can be reviewed without a hand-built join.

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Keep the shop, points, and delivery terms beside every Rakuten price

A conventional scraper often returns an isolated number. Thunderbit builds a row around the way Rakuten actually presents an offer.

A price copied without its conditions

The spreadsheet loses the buying context
Points and coupons are folded into notes
Shipping terms sit on another page
The responsible shop is detached from the price
Researchers must reconcile the rows by hand
Agent Mode

A Rakuten offer reconstructed in one row

The comparison keeps its evidence
Offer components occupy separate columns
Item pages can supply missing shop details
Displayed conditions remain attached to the product
The table can be reviewed as soon as it is exported

What data can you extract from Rakuten?

Choose from 30 fields covering products, prices, points, shops, shipping, ratings, stock, and item details shown on Rakuten pages.

  • Product name
  • Product URL
  • Product ID or item code
  • Primary image URL
  • Shop name
  • Shop URL
  • Current displayed price
  • Price currency
  • Reference or original price
  • Discount amount
  • Discount percentage
  • Point amount
  • Point multiplier
  • Coupon label
  • Sale or campaign label
  • Shipping fee
  • Free-shipping label
  • Shipping destination
  • Estimated delivery
  • Availability
  • Stock note
  • Average rating
  • Review count
  • Review page URL
  • Category or breadcrumb
  • Brand or manufacturer
  • Model number
  • Variation
  • Product description
  • Product specifications

How people use Thunderbit in real research workflows

Watch users explain which browser tasks they handed to Thunderbit and what became easier once the information arrived in a usable table.

Questions that matter when collecting Rakuten product data

Rakuten listings can combine marketplace-wide information with details controlled by each shop.

Continue the product comparison beyond Rakuten

Use another marketplace or retail scraper when the same products, brands, or offers also need to be checked elsewhere.

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