AliExpress Reviews Scraper

Extract public AliExpress product reviews from product URLs or product IDs. Get one clean dataset row per review with ratings, text, buyer country, masked buyer name, variant details, images, helpful votes, seller replies when available, and product-level review stats.

Use this Actor for product research, dropshipping due diligence, competitor monitoring, quality tracking, sentiment analysis, and recurring review exports.

Who is it for?

• Ecommerce sellers checking buyer complaints, variant quality, and product-market fit.
• Dropshippers and product researchers comparing competitor products before sourcing.
• Review intelligence teams building recurring dashboards from public AliExpress feedback.
• Analysts and developers exporting structured review data to CSV, JSON, APIs, BI tools, or AI workflows.

Input recipes

• Small smoke test: keep the default product URL and maxReviewsPerProduct: 20.
• Bulk product monitoring: add many productUrls and schedule the Actor weekly.
• Photo review audit: enable includeMedia to export only reviews with customer images.
• Newest feedback first: set sort to recent to inspect the latest buyer issues.

Example input

{
  "productUrls": [
    "https://www.aliexpress.com/item/1005001388303149.html"
  ],
  "maxReviewsPerProduct": 20,
  "sort": "default",
  "countries": ["US"],
  "includeMedia": false,
  "proxyConfiguration": { "useApifyProxy": false }
}

You can also use product IDs directly:

{
  "productIds": ["1005001388303149"],
  "maxReviewsPerProduct": 50,
  "sort": "recent"
}

Example output

{
  "productId": "1005001388303149",
  "productUrl": "https://www.aliexpress.com/item/1005001388303149.html",
  "reviewId": "50208122799602247",
  "rating": 5,
  "buyerEval": 100,
  "reviewText": "The child really liked it! It arrived faster than expected, everything works, and it's not very noisy. I recommend it 👍",
  "originalReviewText": "очень понравился ребенку! пришел быстрее, чем ожидали, все работает, не очень шумный. рекомендую👍",
  "translatedReviewText": "The child really liked it! It arrived faster than expected, everything works, and it's not very noisy. I recommend it 👍",
  "reviewDate": "27 Feb 2026",
  "buyerCountry": "RU",
  "buyerNameMasked": "Б***а",
  "anonymous": false,
  "variant": "Color:With 2pcs Battery",
  "mediaUrls": ["https://ae-pic-a1.aliexpress-media.com/kf/example.jpg"],
  "thumbnailUrls": ["https://ae-pic-a1.aliexpress-media.com/kf/example.jpg_220x220.jpg"],
  "helpfulCount": 0,
  "notHelpfulCount": 0,
  "sellerReply": null,
  "additionalFeedback": null,
  "reviewType": "REVIEW",
  "selectedReview": true,
  "samePurchaseSuggestion": "Buy the same",
  "sourceLanguage": "en",
  "translated": true,
  "totalReviews": 33,
  "averageRating": 4.6,
  "positiveRate": 81.8,
  "scrapedAt": "2026-07-09T18:07:01.014Z"
}

What data can you extract?

Tips for best results

• Start with maxReviewsPerProduct: 20 until you confirm the product has the reviews you need.
• Use productIds for automated workflows when your system already stores AliExpress IDs.
• Use includeMedia: true for photo review analysis, but expect fewer results.
• Split very large product lists into scheduled batches so each run is easy to retry and inspect.

API usage

Node.js:

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor("fetch_cat/aliexpress-reviews-scraper").call({
  productUrls: ["https://www.aliexpress.com/item/1005001388303149.html"],
  maxReviewsPerProduct: 20
});
console.log(run.defaultDatasetId);

Python:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("fetch_cat/aliexpress-reviews-scraper").call(run_input={
    "productIds": ["1005001388303149"],
    "maxReviewsPerProduct": 20,
})
print(run["defaultDatasetId"])

cURL:

curl -X POST "https://api.apify.com/v2/acts/fetch_cat~aliexpress-reviews-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"productIds":["1005001388303149"],"maxReviewsPerProduct":20}'

MCP and AI agents

Use this Actor from MCP-compatible tools through the official Apify MCP Server.

claude mcp add --transport http apify "https://mcp.apify.com?tools=fetch_cat/aliexpress-reviews-scraper"

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/aliexpress-reviews-scraper"
    }
  }
}

Example prompt: "Run AliExpress Reviews Scraper for these product URLs and summarize the most common complaints by variant."

Limits and caveats

• The Actor extracts public review data only. It does not log in, use buyer accounts, or access private buyer information.
• AliExpress may return translated text, original text, or both depending on the product and review.
• Some products return few or no reviews, or expose fewer optional fields.
• Very large recurring jobs may need proxy configuration if AliExpress throttles requests.

Legality and responsible use

This Actor is designed for public AliExpress review pages and ordinary ecommerce research workflows. Use it only for lawful purposes, respect AliExpress terms and applicable privacy rules, and avoid collecting or combining data in ways that identify private individuals.

Support

Open an issue from the Actor page if a run fails or output looks wrong. Include the run ID or run URL, input JSON, expected output, actual output, and one reproducible public URL.