This tutorial shows how to scrape Amazon reviews into CSV with the Amazon Reviews Scraper template for UScraper. You will import the workflow, replace the sample product URL, choose the export path, validate the first rows, and understand when Python or a hosted API is a better fit.
Before you start
Prerequisites and policy checks
You need UScraper installed as a local desktop app, the free template JSON, one Amazon.com product URL or review-list URL, and a folder where the CSV can be saved. Start with one product, not a whole catalog. Amazon review pages vary by marketplace state, delivery context, account state, review availability, browser session, and anti-abuse checks.
Review the current Amazon Conditions of Use, Amazon robots.txt, and any internal data policy before automation. This guide is for controlled research from pages you can inspect in a normal browser. It is not a guide to bypass CAPTCHA, sign-in walls, access controls, rate limits, checkout flows, private pages, or blocked review widgets.
Technical access is not permission. Keep runs modest, collect only the fields you need, and get legal review before commercial reuse.
Workflow
What the Amazon reviews scraper template does
The JSON export is the authoritative workflow definition. It opens the sample Amazon product detail page, waits for the page, scrolls into the customer review area, checks whether review rows exist, expands visible review text inside detected cards, exports rows, then optionally follows the explicit See all reviews link and paginates through enabled review-list Next links that include pageNumber.
Set Window Size -> Navigate -> Wait for Page Load -> Wait for Element
-> Scroll to Reviews -> Check Review Rows -> Expand Text -> Structured Export
-> See All Reviews -> Review Pagination -> End
The important design choice is defensive control flow. The template checks for review cards before clicking expansion controls, and it exits safely when Amazon does not expose a valid review list. That keeps a blocked page or empty widget from becoming a misleading CSV.
Runbook
How to scrape Amazon reviews to CSV
Import the template
Open the Amazon Reviews Scraper template, download the JSON, and import it into UScraper.
Replace the sample URL
In the Navigate block, replace the bundled product page with an Amazon.com product URL or review-list URL you are allowed to process.
Keep waits and checks
Leave the page-load wait, review-section scrolls, review-card existence checks, and read-more expansion script in place for the first run.
Set the export folder
In Structured Export, confirm amazon-reviews-scraper-for-amazon-us.csv, headers enabled, append mode, and a project-specific local save folder.
Run one product
Compare the CSV against the browser for ASIN, product name, rating summary, reviewer, title, body, date, country, verified badge, helpful count, and review URL.
Add more inputs
Only after the first rows pass QA, add more product URLs. Stop the run if Amazon shows verification, sign-in, unavailable content, or repeated blank rows.
Because the file mode is append, rerunning the same product can duplicate rows. For tests, rename the previous CSV or clear the output file. Keep a run log with URL, ASIN, date, template version, export filename, and selector edits.
Output
What the Amazon reviews to CSV export includes
The bundle does not include a finished CSV sample. Treat the JSON export as the workflow sample, then make your first validation run the live sample for the product, browser state, and region you collected.
amazon-reviews-scraper-for-amazon-us.csvColumn
Page_URL
Browser page where the row was collected.
Column
Product_URL
Canonical or detected Amazon product URL.
Column
ASIN
Product identifier parsed from product or review-list URLs.
Column
Brand
Brand or first product-name token when byline data is unavailable.
Column
Product_name
Product title from the product page or review header.
Column
Product_stars
Visible product-level rating summary.
Column
Rating_count
Visible total review count or customer review text.
Column
Review_rating
Star rating parsed from each review card.
Column
Reviewer_name
Reviewer display name.
Column
Review_title
Review headline cleaned from star-rating labels.
Column
Review_content
Review body after expansion where available.
Column
Review_images
Review image URLs joined with a separator.
Column
Is_verified
True when Amazon renders a verified-purchase badge.
Column
Helpful_count
Helpful vote count normalized from the review card.
Column
Date
Review date text as Amazon renders it.
Column
Country
Country parsed from the review-date string.
{
"fileName": "amazon-reviews-scraper-for-amazon-us.csv",
"rowSelector": "[data-hook=\"review\"], div[id^=\"customer_review-\"], div[id*=\"customer_review\"], .a-section.review",
"fileMode": "append",
"columns": ["Page_URL", "Product_URL", "ASIN", "Brand", "Product_name", "Review_rating", "Reviewer_name", "Review_title", "Review_content", "Review_URL", "Review_images", "Is_verified", "Helpful_count", "Date", "Country"]
}
One review card should create one row. If ASIN, Reviewer_name, Review_rating, and Review_content are all blank, stop and inspect the browser before running more products.
Alternatives
No-code template, Python, or hosted Amazon review scraper API?
People search for scrape Amazon reviews Python, amazon review scraper tool, and amazon reviews scraper alternative because each approach solves a different version of the problem. Choose based on custody, scale, maintenance, and compliance review.
Best for analysts who need a visible browser run, editable no-code workflow, and a local CSV. You still need to validate rows and respect source rules.
The official Amazon Product Advertising API can be useful for approved product data and commerce integrations, but it is not a drop-in replacement for exporting every visible customer review. For production ingestion, a contracted data provider may be more appropriate.
Troubleshooting
Common issues when scraping Amazon reviews
| Symptom | Likely cause | Fix |
|---|---|---|
| Zero rows exported | Amazon did not render review cards, showed CAPTCHA, redirected to sign-in, or served an unavailable product page | Stop the run, inspect the browser, and do not bypass access controls. |
| Product-page reviews export but pagination stops | The all-reviews link or enabled Next link was not visible in the current session | Keep the exported rows and verify whether more review pages are available manually. |
| Review body is short or truncated | Expansion controls did not render or the page changed text containers | Rerun one product after confirming the visible browser has expandable review text. |
| Helpful counts are blank | Amazon did not show a helpful-vote statement for that review | Treat the blank as missing display data, not necessarily zero helpful votes. |
| Duplicate rows appear | Append mode reran the same product or pagination returned overlapping rows | Dedupe by ASIN, reviewer, date, title, review URL, and review content. |
Guardrails for reliable Amazon review exports
Keep batches modest
Review pages can be sensitive to rapid navigation. Start small, validate, then increase volume only when the browser keeps returning normal pages.
Expect selector drift
Amazon can change review-card markup, pagination, date text, or product modules. Blank fields usually mean you should inspect selectors before scaling.
Document the collection purpose
Keep the URL list, run date, template version, output file, and allowed use case with the CSV so downstream users understand its limits.
FAQ
Amazon reviews scraper FAQ
Amazon reviews may be publicly visible, but automated collection can still be limited by Amazon terms, robots directives, marketplace rules, copyright, privacy law, and local regulations. Review the current source rules, do not bypass CAPTCHA or access controls, keep runs modest, and get legal review before commercial reuse.
Next step
Download the Amazon Reviews Scraper template
Use the Amazon Reviews Scraper template as the download path, then keep this tutorial open while you validate the first CSV. Browse the full UScraper template library for adjacent ecommerce workflows or return to the UScraper blog for more no-code scraping tutorials.