Amazon Reviews
Amazon product reviews are public customer feedback records with written text, ratings, author details, publication times, product references, and attached media. These records support product feedback research, rating comparisons, review monitoring, and source-linked data enrichment.
Features
- Multi-product URL inputSubmit one or more supported Amazon product URLs in a single task and apply one result cap across the normalized reviews that are stored.
- Review content and authorsEach record can preserve public review text, numeric rating, author identity, publication time, and attached images or videos.
- Product-linked recordsNormalized results keep product identifiers and product URLs alongside review identity and source links so records remain tied to the reviewed item.
Parameters
| Parameters | Required | Description |
|---|---|---|
urls | Required | Required list of non-empty Amazon product references. Each parsed hostname must belong to a supported marketplace or subdomain; any scheme with a hostname and protocol-relative references are accepted. Each item becomes one provider input row. |
results_limit | Optional | Maximum normalized reviews stored for the whole task; defaults to 100 and accepts integers from 1 through 2,000. |
How to Use
Submit supported product URLs, track the asynchronous task, and read normalized review records with cursor pagination.
- Prepare one or more supported Amazon product URLs and choose a results_limit from 1 through 2,000.
- POST the request to /v1/amazon/reviews and save the returned task_id.
- Poll GET /v1/tasks/{task_id} until the task succeeds or returns a failure.
- Read data.results.items and request the returned next_cursor while has_more remains true.
curl -X POST "https://api.socq.ai/v1/amazon/reviews" \
-H "Authorization: Bearer $SOCQ_API_KEY" \
-H "Content-Type: application/json" \
-d '{"urls":["https://www.amazon.com/dp/B0CHHSFMRL"],"results_limit":3}'
# Poll GET /v1/tasks/{task_id}
# Read data.results.items and follow next_cursor while has_more is trueBest Use Cases
- Product feedback research: Use review text, ratings, authors, and publication times to examine the public feedback returned for known products.
- Cross-product rating comparison: Submit multiple product URLs and group the returned ratings by subject_id or subject_url to compare the collected review records.
- Review evidence enrichment: Attach source links, product references, author details, timestamps, and review media to existing product datasets or monitoring records.
Pro Tips
- Use product references whose parsed hostname belongs to a supported Amazon marketplace; shortened links on unrelated hosts and unsupported regional hosts fail validation.
- Set results_limit for the total number of reviews you want stored across all submitted URLs, then follow next_cursor until has_more is false to read every stored page.
- Key records by review id when present and retain subject_id or subject_url when grouping reviews by product.
- Treat missing text, author fields, ratings, timestamps, product references, and media as unknown rather than inventing replacement values.
Related APIs
Use these APIs when you need a different type of public Amazon data.
- Amazon Best Sellers API — Collect products from public Amazon Best Sellers category URLs with normalized seller, price, reputation, sold-count, media, source, and timestamp fields.
- Amazon Product Details API — Collect product details from known Amazon URLs with title, description, seller, price, rating, review-count, sold-count, and media fields.
- Amazon Product Search API — Search a supported Amazon storefront by product phrase and return normalized product, seller, price, rating, review, sold-count, media, and source fields when available.
- Amazon Seller Info API — Collect public Amazon seller-profile identity, description, website, rating, feedback, location, source, and collection-time fields from known seller URLs.