When Xiaohongshu (RedNote / Little Red Book / 小红书) launched RedShop — its US-facing e-commerce platform — in April 2026, I noticed every existing scraper on Apify only covered the social side: posts, profiles, comments, videos. None of them touched product listings, vendor catalogs, or pricing data.
So I built one.
Why a dedicated shop scraper?
Xiaohongshu is unusual among Chinese platforms because product listings live in a separate URL space from social posts. The all-in-one social scrapers handle the /explore/ posts surface. RedShop products live behind /goods-detail/ with completely different structure.
Trying to extract product data from a "social" scraper means hacky workarounds. A dedicated commerce-focused tool gives you:
- Structured product fields (price, sold count, SKU variants, vendor metadata)
- Native support for vendor/store browsing
- Cross-border vs domestic flagging
- Cleaner pricing model: charge per product, not per "result"
What it extracts
For each product:
- itemId, title, productUrl
- salePrice, originalPrice, discountPct, currency (CNY for domestic, USD for cross-border)
- soldCount, wantCount (popularity signals)
- cover, images
- vendor (sellerId, name, rating)
- category path
- skus (variants with prices and stock)
- crossBorder flag and shippingOrigin
Three modes
| Mode | What it does |
|---|---|
product_search |
Search products by keyword, sort by price/sales, filter by price range |
vendor_products |
Full catalog from a specific seller |
product_detail |
Deep dive on specific product URLs (full SKU breakdown) |
Real-world use cases
- DTC brands: monitor your own listings and competitor pricing on China's #1 social commerce platform
- Dropshippers and resellers: discover trending Chinese products before they hit Amazon or Etsy
- Cross-border arbitrage: identify SKUs popular in China that haven't reached Western markets yet
- Investment analysts: track e-commerce activity for Chinese consumer brands
- Sourcing agents: scout Chinese products at scale for clients in cosmetics, fashion, or home goods
Combined with the RedNote All-in-One Scraper (social side), you can map products to the influencers tagging them — extremely valuable for influencer-product correlation studies.
How to use it
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("zhorex/rednote-shop-scraper").call(run_input={
"mode": "product_search",
"searchQuery": "skincare",
"maxResults": 100,
"sortBy": "sales",
"minPrice": 50,
"maxPrice": 500,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(f"{item['title']} — ¥{item['salePrice']} (sold {item['soldCount']})")
Output sample
{
"itemId": "642a1b3c0000000023019f7e",
"title": "Skincare Set - Hydrating Toner + Serum + Moisturizer",
"salePrice": 199.00,
"originalPrice": 299.00,
"discountPct": 33.4,
"currency": "CNY",
"soldCount": 12500,
"wantCount": 5400,
"vendor": {"sellerId": "...", "name": "BeautyBrand Official", "rating": 4.8},
"category": "Beauty / Skincare / Sets",
"skus": [{"spec": "Normal Skin", "price": 199.00, "stock": 1200}],
"crossBorder": false,
"shippingOrigin": "China"
}
Pricing
Pay-per-event:
- $0.0075 per product scraped
- $0.025 per vendor info record
Typical costs:
- Search 100 products: ~$0.75
- Full vendor catalog (200 products): ~$1.53
- 5 competitor vendors with 100 products each: ~$3.88
FAQ
Does it work for cross-border products?
Yes — products are explicitly flagged in the output (crossBorder: true/false) so you can filter domestic vs international listings.
Can I track price changes over time?
Schedule the actor to run daily/weekly via Apify Schedules. The dataset versioning gives you a price history for any product or vendor.
Does it need a proxy?
Residential proxies are recommended for reliable results. The default config uses Apify's residential pool.
Is there an official Xiaohongshu shop API?
No — Xiaohongshu doesn't offer a commerce API for international developers. This actor is the practical alternative.
Try it
RedNote Shop Scraper on Apify — works with Apify's free plan ($5/month credits cover hundreds of products at no cost).
If you build something useful with it, drop a comment — always interested in seeing how people use commerce data.
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