Use case

Product research with AliExpress reviews

Before choosing a product or a supplier, read what thousands of buyers have already said. The API turns reviews into data you can compare.

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Reviews say more than the star rating

Two listings of the same product can both show 4.7 stars and be very different: one with 5% of 1-star reviews complaining about sizing, the other with almost none. The average hides it; the distribution and the content of the reviews don't.

With the API you can get, for any AliExpress product, the rating distribution, the number of reviews with photos and the reviews themselves filtered by stars, and automate it for dozens of products.

What you can analyse

Compare suppliers of the same product by average, volume of reviews and percentage of negative reviews.
Detect recurring problems: read only the 1 and 2-star reviews and look for patterns (sizing, materials, shipping, defects).
Check a market: the reviews from a specific country (filter=local) tell you how the product does with buyers like yours.
Feed your tools: sentiment analysis, dashboards or an LLM that summarises the pros and cons.

Example: choose the best supplier

The first script compares several listings using only the rating summary (one request each, with pageSize=1). The second reads the 1-star reviews of the chosen one to see what goes wrong.

Python — compare suppliers

# Compare several AliExpress listings of the same product before choosing a supplier.
import os
import requests

API = "https://api.aliexpress-reviews.com"
HEADERS = {"x-api-key": os.environ["REVIEWS_API_KEY"]}

def summary(product_id):
    res = requests.get(f"{API}/v1/reviews/{product_id}", headers=HEADERS, params={"pageSize": 1}, timeout=30)
    res.raise_for_status()
    return res.json()["summary"]

for product_id in ["1005006123456789", "1005007654321098"]:
    s = summary(product_id)
    dist = s["ratingDistribution"]
    total = sum(dist.values()) or 1
    negative = (dist["1"] + dist["2"]) / total
    print(f"{product_id}: {s['averageRating']}★ · {s['totalReviews']} reviews · {negative:.0%} negative")

Python — read the complaints

# Read the 1-star reviews to find recurring problems (sizing, shipping, quality…).
res = requests.get(
    f"{API}/v1/reviews/1005006123456789",
    headers=HEADERS,
    params={"filter": "1", "pageSize": 20},
    timeout=30,
)
for review in res.json()["data"]:
    print(review["country"], review["date"], review["content"])

Data you get in each response

summary: averageRating, totalReviews, ratingDistribution (reviews per star) and filterCounts (with photos, with additional feedback, local).
data: each review with its rating, text (translated and original), country, date, the variant bought (sku) and helpful votes.
Pagination: total and totalPages to go through all the reviews of a product.

Questions

Can I analyse many products at once?

Yes. Each product is one request, and the summary comes in every response, so comparing 100 products costs 100 requests (the Pro plan includes 1,000 a day).

Do I see which variant each buyer bought?

Yes. The sku field shows the variant (colour, size…), useful for detecting that, for example, one size runs small.

Can I use it with Python, Google Sheets or no-code tools?

Yes. It is a REST API with an x-api-key header, so it works from any language and from tools like Make, Zapier or n8n.

Try it with your own products

100 requests a day for free, no card required. Paste a product ID into the tester in your dashboard and see the JSON.

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