Amazon Reviews Scraper for France

Amazon Reviews Scraper for France turns known Amazon product identifiers into a review-level dataset for customer-feedback research. Each row keeps the product context beside the review itself, including the product and review ratings, reviewer name, title, written feedback, date, verification marker, helpful-vote text, image links, and the source addresses needed to inspect the original page.

The resulting table brings qualitative comments and visible rating signals together in one place. That makes it useful as a research base when a team needs to understand why shoppers respond positively or negatively, compare feedback themes across products, or retain traceable evidence for a product-quality review without copying individual review pages by hand.

Data notes

Records come from publicly visible customer-review pages on the France marketplace and reflect what those pages displayed when collection took place. Each record represents one collected review for one ASIN, and the individual review address is used to distinguish reviews across retrieved result pages. Product rating and product review count are page-level snapshots repeated beside each review; they can change after collection. Review rating, verification status, helpful-vote count, date, country, and image links are preserved as displayed text rather than normalized values. A blank value means that the public review record did not expose that detail. Deleted, restricted, sign-in-only, or otherwise unavailable reviews are not covered.

What the results look like

Each record represents one public product review:

The output also includes “Product name,” “Brand,” “Product rating,” “Product review count,” “Review content,” “Helpful vote count,” “Review image URLs,” “Reviewer country,” “Review URL,” “Reviews page URL,” and “Collection message.”

Use cases

• For product-quality reviews, group “Review rating” and read “Review title” with “Review content” to identify recurring strengths, defects, and usage problems.
• For trust-signal analysis, compare “Verified purchase” with “Review rating” and “Helpful vote count” to see how source-reported verification and usefulness markers vary across feedback.
• For product comparisons, use “ASIN,” “Product name,” “Product rating,” and “Product review count” to separate review-level opinions from the aggregate product snapshot.
• For evidence review, retain “Review URL” and “Reviews page URL” beside “Review author” and “Review date” so analysts can trace a record back to its public context.