This Amazon Mexico reviews scraping tutorial shows how to collect amazon.com.mx review pages into a structured CSV with the Amazon Mexico Review Scraper template for UScraper. You will import the workflow, replace sample ASIN review URLs, set the export path, run one validation pass, and diagnose the most common blank-row issues.
Before setup
Prerequisites and permission checks
You need UScraper installed as a local desktop app, the free Amazon Mexico review template JSON, one or more amazon.com.mx review-list URLs, and a folder where the CSV can be saved. Start with one ASIN and one or two pages. A small test keeps CAPTCHA, redirect, and empty-page symptoms easy to spot before you add a larger URL list.
Review Amazon's current terms, robots directives, marketplace rules, and your internal data policy before collecting review data. 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, account pages, access controls, or blocked review widgets.
Technical access is not permission. Collect only the fields you need, keep runs modest, and get legal review before using review text in commercial reporting, model training, or redistribution.
Workflow anatomy
What the Amazon Mexico review scraper does
The JSON export is the authoritative workflow definition. It navigates through known amazon.com.mx review URLs, waits for the page, pauses briefly, runs an injected JavaScript block, checks whether normalized review rows exist, and then writes structured rows to CSV.
The important detail is the normalization step. The workflow first wraps any review cards already visible in the page. If none are present, it parses the ASIN and pageNumber from the current URL, requests Amazon's same-origin review-render response from the current browser session, extracts returned review HTML fragments, and places those fragments under #normalized-review-list so Structured Export can read a consistent row selector.
| Stage | What happens | Why it matters |
|---|---|---|
| Navigate | Opens the configured product-reviews URLs | Keeps ASIN and page inputs explicit |
| Wait and sleep | Lets the page state settle before JavaScript runs | Reduces false empty results on slower loads |
| Inject JavaScript | Normalizes visible or returned review fragments into one list | Gives export selectors a stable target |
| Element Exists | Checks for review rows before export | Avoids writing challenge pages as data |
| Structured Export | Appends mapped fields into a local CSV | Produces spreadsheet-ready review rows |
| Loop Continue | Advances to the next URL | Supports controlled multi-page batches |
Use the maintained Amazon Mexico Review Scraper template as the download path instead of rebuilding this graph by hand.
Runbook
How to scrape Amazon Mexico reviews to CSV
Import the template
Open the Amazon Mexico Review Scraper template, download the JSON, and import it into UScraper.
Replace the sample URLs
In the Navigate block, replace the bundled examples with amazon.com.mx product-reviews URLs for your approved ASINs. Keep pageNumber values explicit so every row is traceable.
Keep waits and checks
Leave the page-load wait, short sleep, JavaScript completion wait, and Element Exists check in place for the first run. Shortening these steps can create false blanks.
Set the export folder
In Structured Export, confirm amazon-mexico-review-scraper.csv, headers enabled, append mode, and a project-specific local save folder.
Run one ASIN
Compare the CSV against the browser for ASIN, page number, reviewer, rating, title, body, date, variant, verified purchase badge, helpful votes, and review URL.
Add more pages
Only after the first rows pass QA, add more ASIN and page combinations. Stop the run if Amazon shows verification, redirects, unavailable reviews, or repeated blank results.
Because the file mode is append, rerunning the same URL can duplicate rows. For tests, rename the previous CSV or clear the output file. Keep a simple run log with ASIN, page range, date, template version, export filename, and any selector edits.
Output
What the Amazon reviews to CSV export includes
The bundle does not include a finished CSV sample. Treat the export schema below as the expected shape, then make your first validation run the live sample for that ASIN, browser session, and marketplace state.
amazon-mexico-review-scraper.csvColumn
asin
ASIN parsed from the current amazon.com.mx review URL.
Column
page_number
The review pageNumber parameter for the current run.
Column
review_id
Amazon review row ID when available.
Column
reviewer_name
Reviewer display name from the review card.
Column
reviewer_profile_url
Profile link from the review row when Amazon exposes it.
Column
rating
Individual star-rating text from the review card.
Column
review_title
Review headline cleaned of duplicate icon text.
Column
review_date
Localized review date text as shown by Amazon.
Column
product_variant
Variant or format strip text when present.
Column
verified_purchase
Verified purchase badge text when present.
Column
review_body
Full review body text cleaned into one CSV cell.
Column
helpful_votes
Helpful vote statement from the review row.
Column
review_image_count
Count of visible review image tiles.
Column
review_url
Direct Amazon customer review URL built from the review ID.
Column
source_url
The review page URL that produced the row.
Column
scraped_at
ISO timestamp generated when the row is exported.
{
"fileName": "amazon-mexico-review-scraper.csv",
"rowSelector": "#normalized-review-list [data-hook=\"review\"], #normalized-review-list [id^=\"customer_review-\"], #normalized-review-list .a-section.review",
"fileMode": "append",
"columns": ["asin", "page_number", "review_id", "reviewer_name", "rating", "review_title", "review_date", "verified_purchase", "review_body", "helpful_votes", "review_url", "source_url", "scraped_at"]
}
Alternatives
UScraper, Octoparse, Apify, or Python?
Searches like best Amazon review scraper Mexico, Octoparse Amazon Mexico scraper alternative, and Apify Amazon reviews scraper vs Octoparse usually come from the same decision: do you want a local no-code workflow, a hosted actor, a cloud scraper template, or custom code?
| Approach | Best fit | Trade-off |
|---|---|---|
| UScraper template | Analysts who want a local desktop app workflow and CSV output they can inspect | You still need to validate browser state, selectors, and policy fit |
| Octoparse-style template | Teams that prefer cloud template catalogs and guided parameters | Runtime, data custody, and marketplace-specific maintenance depend on that platform |
| Apify actor | Developers who want hosted runs, actor inputs, and API integration | You manage actor settings, proxy strategy, costs, and compliance review |
| Python or scraping API | Engineering teams that need full control over parsing and pipelines | You own rendering, retries, pagination, anti-bot handling, selector drift, and exports |
UScraper is strongest when you want a supervised, editable workflow that keeps the CSV on your machine by default. Python or a hosted scraper can be better when you need API-first scheduling, large distributed jobs, or deep custom transformation before storage.
Common issues and fixes
Check the browser first. Amazon may have returned CAPTCHA, a robot check, sign-in, a geo redirect, or an empty review page. If the page does not show accessible review cards, the workflow should not export review rows.
Frequently asked questions
Amazon reviews may be publicly visible, but automated collection can still be restricted by Amazon terms, robots directives, copyright, privacy law, marketplace policies, and local regulations. Keep runs modest, do not bypass CAPTCHA or access controls, and get legal review before commercial reuse.