We extract product listings, pricing signals, shipping options and costs, seller profiles, coupons, review corpus, and keyword rankings from AliExpress. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from aliexpress.com. All fields typed and schema-versioned.
"item_id": "1005005832741920", "title": "Wireless Earbuds Bluetooth 5.3 HiFi Stereo TWS Headphones", "seller_name": "SoundWave Official Store", "price": 12.49, "original_price": 24.99, "discount_pct": 50, "orders_count": 18742, "rating": 4.7, "free_shipping": true, "aliexpress_choice_badge": true
| # | item_id | title | category | sub_category | seller_id | seller_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from aliexpress.com. All fields typed and schema-versioned.
"item_id": "1005005832741920", "price": 12.49, "original_price": 24.99, "coupon_available": true, "coupon_value": 2.00, "flash_sale_price": 10.99, "flash_sale_end_time": "2026-05-13T00:00:00Z", "price_timestamp": "2026-05-12T09:30:00Z"
| # | item_id | price | original_price | discount_pct | coupon_available | coupon_value |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from aliexpress.com. All fields typed and schema-versioned.
"review_id": "ae_rv_7481920341", "item_id": "1005005832741920", "star_rating": 5, "reviewer_country": "IN", "review_body": "Sound quality is amazing for this price. Fast delivery.", "variation_purchased": "Color: Black | Size: One Size", "review_date": "2026-04-25"
| # | review_id | item_id | reviewer_country | star_rating | review_body | review_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller Profiles objects from aliexpress.com. All fields typed and schema-versioned.
"seller_id": "soundwave_official", "store_name": "SoundWave Official Store", "seller_rating": 97.3, "positive_feedback_pct": 97.3, "followers_count": 142081, "top_brand_flag": false, "active_items_count": 1847
| # | seller_id | store_name | store_url | seller_rating | positive_feedback_pct | followers_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our AliExpress scraper covers every layer of the platform: product listings, shipping intelligence, flash sale and coupon data, seller profiles, review corpus, and keyword rankings.
Title, description, specifications, images, variants, orders count, and every metadata field AliExpress surfaces — scraped at item-ID level.
Capture price, original price, flash sale prices, coupons, bundle discounts, and quantity tiers — timestamped per crawl.
Extract all shipping options, carrier names, costs, and estimated delivery days by destination country — key for dropshipping and logistics analysis.
Full review text, star ratings, buyer country, variation purchased, helpful votes, and image uploads — paginated across all review pages.
Store rating, positive feedback percentage, followers, items sold, response time, active listing count, and Top Brand flag — per seller.
Monitor organic vs sponsored position for any keyword — with AliExpress Choice badge, free shipping, and coupon availability capture.
Track flash sale windows, coupon availability, bundle deals, and order quantity thresholds — useful for repricing and competitor deal monitoring.
AliExpress exposes cumulative orders per listing — one of the most direct product demand signals available on any consumer marketplace.
One-off bulk exports or continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide item IDs, category URLs, keyword sets, or seller store URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for aliexpress.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
AliExpress's dynamic pricing, geo-personalised shipping rates, and bot-detection layers require specialised infrastructure. Here's how we stay resilient.
AliExpress's bot detection operates on TLS fingerprints, browser headers, and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
AliExpress shipping costs and delivery ETAs are highly personalised by destination country. We configure proxy sessions with country-specific geo-targeting so your dataset reflects real shipping options and costs for any target market.
AliExpress product pages, flash sale widgets, and seller profiles are JavaScript-rendered. We run full Playwright sessions with JavaScript execution — capturing coupon stacks, tiered pricing, and shipping data that headless HTTP clients miss.
AliExpress updates its DOM structure frequently. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, text-pattern matching, and structured data extraction — so layout changes don't break your pipeline.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops — and respond before you notice. SLA uptime is contractual, not aspirational.
Dropshippers monitor AliExpress for high-orders-count products, shipping lead times, seller reliability scores, and price trends to identify and source winning products.
Retailers and importers track AliExpress landed costs — price, shipping, and customs estimates — to reprice and protect margin on competing channels.
Brands use orders count, review velocity, and keyword rank signals on AliExpress as early-stage demand indicators before products reach Western retail.
ML teams use AliExpress product titles, descriptions, images, and reviews — often with rich multi-language content — to train product classification and NLP models.
Brand protection teams monitor AliExpress for infringing listings, MAP violations, and unauthorised resellers using brand name and product image matching.
Logistics companies and freight forwarders use AliExpress shipping option data to benchmark carrier pricing, lead times, and service quality across routes.
"AliExpress's orders count is one of the most transparent product demand signals in e-commerce — and its shipping intelligence is unmatched for cross-border logistics analysis. But none of it is queryable unless you build the pipeline."
Reliable AliExpress scraping requires residential proxies, full JavaScript rendering, geo-personalised session handling for shipping data, CAPTCHA bypass, and daily selector maintenance. DataFlirt absorbs that complexity so your team can focus on the product decisions — not the infrastructure.
Everything supported by our aliexpress.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, flash sale widget interaction, and geo-personalised session management.
We maintain pools of residential ISP proxies across US/UK/DE/IN regions with country-level geo-targeting for shipping resolution. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About aliexpress.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from AliExpress is generally permissible under applicable law — reinforced by the hiQ v. LinkedIn ruling and similar precedents. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR. We recommend clients review AliExpress's ToS independently and consult legal counsel for specific use cases.
We use residential ISP proxies that appear as real consumer traffic, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes don't break the pipeline.
Yes. AliExpress shipping costs and delivery ETAs are geo-personalised. We configure proxy sessions with country-specific geo-targeting so your dataset reflects real shipping options and costs for any target market — critical for dropshipping landed cost analysis.
Orders count is scraped directly from product listing pages. This is one of AliExpress's most distinctive and valuable data fields — a direct, publicly visible demand signal that most other platforms do not expose.
Real-time streaming pipelines achieve sub-60-minute latency for price and flash sale signals on a defined item set. Full catalogue refreshes at daily cadence complete within a 6–12 hour window depending on size.
Our smallest packages start at a defined item list (typically 1,000–40,000 items) with weekly delivery. For larger catalogues, ongoing monitoring contracts, or custom schema requirements, we price based on volume and delivery frequency.
Yes — including full pagination, buyer country, variation purchased, image attachments, and helpful vote counts. AliExpress review data is particularly valuable because it contains rich multi-language buyer sentiment from global markets.
Absolutely. We provide a sample run of up to 500 items or 50 search result pages as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off product demand dataset or a continuous price and shipping monitoring feed across 1M items — we scope, build, and operate the pipeline. Tell us what you need.
