🛍️ AliExpress Product Scraper — search & catalog data

Extract structured product data from AliExpress search results — titles, prices, image URLs, promotion badges, and available public listing signals such as ratings, sold-count badges, AliExpress Choice tags, and ship-from country — straight into a clean, queryable dataset.

Built for cross-border e-commerce sourcing, dropshipping research, price monitoring, and competitor catalog mapping. No login required. No account at risk.

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What you can do

• Run batch keyword searches across many product categories at once — phone cases, watches, electronics, fashion, home goods, anything you can search on AliExpress.
• Capture the public product card for every listing on the search results page: title, sale & original price, currency, image, on-card promotion text, and public listing signals when AliExpress shows them.
• Refine the captured listings by minimum star rating, free-shipping promotions, or AliExpress Choice tag — listings that fail the filter are dropped before reaching the dataset, so you only review what matters.
• Export to JSON, CSV, Excel, HTML, RSS through Apify's standard dataset views.

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Input fields

Field	What it does
🔍 Search keywords	One or more keywords. Each keyword runs as a separate batch and is tagged on the output rows so you can split results downstream.
📦 Max products per keyword	Cap how many listings to capture per keyword (10–60).
⭐ Minimum star rating (optional)	Drop listings below this average rating (0–5).
🚚 Free shipping only (optional)	Keep only listings whose on-card badges advertise free shipping.
✅ AliExpress Choice only (optional)	Keep only listings that participate in the AliExpress Choice program (a curated-shipping label used by AliExpress; not a star-rating signal).

Sensible defaults are pre-filled. Most users only fill in the keywords field, hit Start, and let it run.

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Output sample

A single dataset row (34 fields total — abbreviated here):

{
  "product_id": "1005006302901671",
  "product_url": "https://www.aliexpress.com/item/1005006302901671.html",
  "title": "Clear Phone Case For iPhone 11 12 13 14 15 Pro Max",
  "main_image": "https://ae-pic-a1.aliexpress-media.com/kf/Se0a649a4....jpg",
  "currency_code": "USD",
  "currency_symbol": "$",
  "currency_source": "listing",
  "price_original": 2.05,
  "price_sale": 1.95,
  "price_original_display": "$2.05",
  "price_sale_display": "$1.95",
  "discount_percent": 4,
  "star_rating": 4.3,
  "sold_count": 1000,
  "sold_count_display": "1,000+ sold",
  "is_choice": false,
  "ship_from": "CN",
  "category_id": "202192403,202228401,380230",
  "spu_id": "1005006302901671",
  "sku_id": "12000036775043019",
  "is_price_power": false,
  "selling_points": ["Special offer", "Extra 2% off with coins"],
  "search_query": "phone case",
  "search_position": 1,
  "extracted_at": "2026-05-05T13:14:00+00:00"
}

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Use cases

• Dropshipping product research — find listings with strong sold counts and high ratings; surface the AliExpress Choice tag automatically.
• Cross-border catalog mapping — pull a snapshot of search-result inventory across keywords for analysis or ingest into your own product database.
• Price-monitoring snapshots — schedule recurring runs against the same keywords to log how prices, sale flags, and promotion badges shift.
• Market intelligence — measure rough demand signals (sold-count badges) per product category and ship-from country.

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FAQ

Q1 — Do I need an AliExpress account? No. The actor reads public search-result pages. No login, no account, no personal data involved.

Q2 — Why is my run returning fewer items than expected? Public search results can vary by region, page load conditions, keyword popularity, and the filters you choose. If you have Minimum star rating, Free shipping only, or AliExpress Choice only turned on and see zero results, try relaxing those filters before running again.

Q3 — Why are some fields empty (e.g. star_rating, sold_count)? Not every search-result card displays every public signal. Some cards do not show a rating, sold-count badge, Choice label, or ship-from country at capture time. The schema documents which fields are nullable. Note: when you set a Minimum star rating, listings without a visible rating are excluded from the output.

Q4 — How fresh is the data? Each row carries an extracted_at timestamp recording when it was captured. Listing-card values (ratings, sold counts, promotion tags, ship-from country, etc.) reflect the snapshot at that moment and may shift between runs as AliExpress refreshes its catalog. Re-run any row whose freshness matters to your workflow.

Q5 — Which currency and storefront does the data come from? By default the actor uses the AliExpress US storefront. The currency_code field shows the row currency when it is known, and currency_source tells you whether the currency came from the listing, only a visible symbol, or the default storefront. ship_from separately tells you the warehouse country when AliExpress shows it. Group by currency_code before comparing prices across currencies.

Q6 — Can I scrape product detail pages, reviews, or Q&A as well? The current version focuses on search-result cards. Detail-page enrichment can be requested if your workflow needs it.

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Compliance & disclaimer

This actor extracts public product listing data. It does not require a login, does not collect personal data, and does not interact with any logged-in surface.

You — the customer — are responsible for ensuring your use of the extracted data complies with applicable laws, the policies of the source site, and the rights of any third parties (including but not limited to image rights and trademark). The author of this actor provides the tool on an "as-is" basis and accepts no liability for downstream uses.

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Affiliate

If this actor or any other Apify scraper is useful to you, sharing the platform with your colleagues using this link apify.com/futurizerush?fpr=rush helps keep the actor maintained.

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Keywords: AliExpress, scraper, product data, e-commerce, dropshipping, sourcing, price monitoring, catalog, search results, product listing, retail, cross-border, market research, competitor analysis, Apify, Claude Code, OpenClaw, Gemini, Antigravity, Codex, ChatGPT.