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Gio Rich
Gio Rich

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Benchmark a product category on Alibaba before you source it (Python, real numbers)

#webscraping #python #ecommerce #datascience

I built this actor; it's a paid tool on Apify with a free trial credit.

Before contacting a single supplier, it helps to know what "normal" looks like for a category: the usual starting price, the usual minimum order, how long production takes, and whether certified products cost more. Otherwise the first quote you get becomes your anchor.

My earlier post ranked individual suppliers by unit price at a given order size. This one zooms out: it scrapes 75 listings per category with my Alibaba Product Search Scraper and summarises the whole page of results.

The numbers from a real run

I ran four searches (75 listings each) and took medians:

Search Median lowest price Median MOQ Median lead time Verified suppliers Sponsored results
bluetooth earbuds $5.98 10 10 days 32 / 75 1
yoga mat $9.00 20 31 days 60 / 75 23
custom tote bags $0.45 100 10 days 61 / 75 25
led strip lights $1.50 10 10 days 62 / 75 37

A few things stand out straight away:

  • Certification premium is real for electronics. Earbuds listing any certification (FCC, CE, RoHS were the most common) had a median low price of $6.51 versus $5.53 without one. LED strips: $2.00 certified versus $1.20 without. If you're selling into the EU or US you need those certificates anyway, so $5.53 is not your real benchmark.
  • Yoga mats take 3x longer to make. A 31-day median lead time versus 10 for the others changes your reorder planning.
  • Half the LED strip results were ads (37 of 75). Sorting by position alone mostly shows you who paid.

The script 

pip install apify-client
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from statistics import median
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("rel8ble/alibaba-product-search-scraper").call(run_input={
    "searchTerms": ["bluetooth earbuds", "led strip lights"],
    "maxResultsPerSearch": 75,
    "includeAds": True,   # keep sponsored listings so we can count them
})

by_search = {}
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    by_search.setdefault(item["searchTerm"], []).append(item)


def med(values):
    values = [v for v in values if v is not None]
    return median(values) if values else None


for term, items in by_search.items():
    certified = [i for i in items if i.get("productCertifications")]
    plain = [i for i in items if not i.get("productCertifications")]
    print(f"\n{term} ({len(items)} listings)")
    print(f"  median low price   ${med([i['priceMin'] for i in items])}")
    print(f"  certified / not    ${med([i['priceMin'] for i in certified])} ({len(certified)}) "
          f"vs ${med([i['priceMin'] for i in plain])} ({len(plain)})")
    print(f"  median MOQ         {med([i['moq'] for i in items])}")
    print(f"  median lead time   {med([i['leadTimeDays'] for i in items])} days")
    print(f"  verified suppliers {sum(1 for i in items if i.get('verifiedSupplier'))}")
    print(f"  sponsored (ads)    {sum(1 for i in items if i.get('isAd'))}")
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The fields doing the work

Every listing carries the fields this needs, for example (real row, trimmed):

{
  "searchTerm": "bluetooth earbuds",
  "priceMin": 6.5, "priceMax": 9.9, "priceText": "US $6.50-$9.90",
  "priceTiers": [
    { "minQuantity": 10, "maxQuantity": 89, "price": 9.9 },
    { "minQuantity": 5000, "maxQuantity": null, "price": 6.5 }
  ],
  "moq": 10, "leadTimeDays": 14,
  "productCertifications": ["FCC", "UKCA", "CE", "ROHS"],
  "isAd": false,
  "supplierYears": 10, "verifiedSupplier": true, "tradeAssurance": true,
  "supplierRating": 4.5, "responseRate": "98.5%"
}
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priceMin is the price at the biggest quantity tier, so it's the best case. For a benchmark at your own order size, read priceTiers the way the earlier post did.

Limits

  • Medians from 75 listings describe what Alibaba shows for that search, not the whole market. Run a couple of related terms ("wireless earbuds", "tws earbuds") before you trust a number.
  • leadTimeDays and certifications are what suppliers list; they're claims until you see paperwork.
  • Prices exclude shipping and duties.

Cost

$1.50 per 1,000 results (one result = one listing). The four-category snapshot above is 300 results, about $0.45. Apify's free plan includes $5 of monthly credit.

Alibaba Product Search Scraper on Apify · Python examples: alibaba-product-scraper-python on GitHub

This article was drafted with AI and published by me.

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