AliExpress Reviews Scraper

Extract customer reviews from any AliExpress product — star ratings, full review text, buyer country, review dates, buyer photos, helpful votes, and a per‑product 1–5★ rating breakdown — as clean, structured JSON. Feed product URLs or IDs and get analysis‑ready data. No login, no cookies, no CAPTCHAs.

Reviews come from AliExpress's public feedback service, the most stable AliExpress data source, so runs finish reliably even for products with tens of thousands of reviews.

Who uses this

• E‑commerce & dropshipping sellers — vet suppliers and products before listing; spot quality complaints and shipping issues early.
• Market & product researchers — build sentiment datasets across products, categories, and countries.
• Brand & QA teams — monitor what real buyers say about a product over time.
• Data scientists / LLM builders — collect multilingual, labeled (star‑rated) review corpora for training and analysis.

Output fields

Each row is a single review with product context attached:

Field	Type	Description
product_id	string	AliExpress product ID
product_url	string	Canonical product URL
review_id	string	Unique review ID
rating	number	Review rating on a 0–5 scale
review_text	string	Buyer's written feedback
buyer_name	string	Buyer display name (may be anonymized)
buyer_country	string	Buyer country code (e.g. US, BR, ES)
review_date	string	Date the review was posted
sku_info	string	Purchased variant (color/size/etc.)
logistics	string	Shipping/carrier note when present
images	array	URLs of buyer‑uploaded photos
images_count	number	Number of buyer photos on the review
thumbnails	array	Thumbnail URLs for the photos
up_votes	number	"Helpful" votes
product_average_rating	number	Product's overall average star rating
product_total_reviews	number	Total number of reviews on the product
product_star_breakdown	object	Count of 5/4/3/2/1‑star reviews
scraped_at	string	ISO‑8601 timestamp of extraction

High‑value use cases

1. Supplier vetting — pull 200 newest reviews for a shortlist of products and rank suppliers by average rating and complaint keywords before you buy.
2. Sentiment datasets — export thousands of star‑labeled reviews across a category for NLP/LLM training.
3. Photo evidence mining — filter to reviews with buyer photos to see how products actually arrive.
4. Cross‑market analysis — group reviews by buyer_country to compare satisfaction by region.
5. Product QA monitoring — schedule weekly runs and track the 1–5★ breakdown drifting over time.

Input parameters

Parameter	Type	Default	Description
productUrls	array	—	AliExpress product URLs or bare numeric IDs (one dataset per product). Required.
maxReviewsPerProduct	integer	100	Stop after this many reviews per product.
sort	string	most_relevant	most_relevant, most_helpful, or newest.
onlyWithPhotos	boolean	false	Return only reviews that include buyer photos.
language	string	en_US	Locale for the request (reviews stay in each buyer's language).
proxyConfiguration	object	Apify Proxy	Optional — the endpoint is open, so a proxy is not required.

Example input

{
  "productUrls": [
    "https://www.aliexpress.com/item/3256806491670200.html",
    "1005006677984952"
  ],
  "maxReviewsPerProduct": 200,
  "sort": "newest",
  "onlyWithPhotos": false
}

Example output row

{
  "product_id": "3256806491670200",
  "product_url": "https://www.aliexpress.com/item/3256806491670200.html",
  "review_id": "1005...889",
  "rating": 5.0,
  "review_text": "Great sound for the price, arrived in 12 days.",
  "buyer_name": "j***a",
  "buyer_country": "BR",
  "review_date": "12 Aug 2026",
  "sku_info": "Color: Black",
  "images": ["https://ae01.alicdn.com/kf/....jpg"],
  "images_count": 1,
  "up_votes": 3,
  "product_average_rating": 4.9,
  "product_total_reviews": 7446,
  "product_star_breakdown": { "five_star": 6800, "four_star": 420, "three_star": 120, "two_star": 60, "one_star": 46 },
  "scraped_at": "2026-08-22T10:14:21.000Z"
}

Scheduling & integrations

• Schedule runs (hourly/daily/weekly) from the Apify Console to monitor review trends.
• Webhooks can push new results to your own endpoint on run completion.
• Export to JSON, CSV, Excel, or Google Sheets, or connect via Make, Zapier, and the Apify API to your CRM/warehouse.

Use from AI assistants (MCP)

This Actor works with the Apify MCP server, so AI assistants (Claude, ChatGPT, and other MCP clients) can call it as a tool — ask your agent to "get the newest reviews for this AliExpress product" and pipe the structured output straight into your workflow.

FAQ

Do I need an AliExpress account or cookies? No. Reviews come from a public endpoint — no login, cookies, or CAPTCHA solving.

How many reviews can I get per product? As many as the product has — popular items expose tens of thousands across pages. Set maxReviewsPerProduct to cap it.

What languages are the reviews in? Each review is returned in the buyer's original language, with a buyer_country code so you can filter or translate.

How fresh is the data? Every run fetches live data at request time; scraped_at records when.

Can I get only reviews with photos? Yes — set onlyWithPhotos to true.

Is scraping this legal? The Actor collects only publicly available review data. You are responsible for using the output in line with AliExpress's terms and applicable laws (e.g. GDPR for any personal data).

A run got interrupted — do I lose progress? No. Progress is checkpointed per product and resumes on a re‑run with the same input.