Amazon rating monitoring

1. 01Snapshot the rating and distribution

   The reviews endpoint returns the product's rating, ratings count, and distribution as the percentage of ratings at each star. Store it with the date; Amazon shows only the current numbers.

   GET /v1/product/reviews?engine=amazon&asin=B0CF3VGQFL · product

   {
     "asin": "B0CF3VGQFL",
     "title": "Redragon Mechanical Gaming Keyboard",
     "rating": 4.3,
     "ratings_count": 6819,
     "rating_distribution": {
       "1": 8,
       "2": 4,
       "3": 7,
       "4": 12,
       "5": 69
     }
   }

2. 02Read the reviews shown

   reviews holds the reviews Amazon shows signed-out shoppers, usually 8 to 13, with rating, title, text, date, verified purchase, and the variant bought. Flag the 1- and 2-star ones.

   GET /v1/product/reviews?engine=amazon&asin=B0CF3VGQFL · reviews.0

   {
     "id": "R1DKMN88M0OLUC",
     "title": "But should you?",
     "body": "I would highly recommend this keyboard and company.",
     "rating": 5,
     "author": "Trevor H.",
     "date": "2026-06-21",
     "country": "United States",
     "verified_purchase": true,
     "variant": "Color: Black",
     "helpful_votes": 9,
     "url": "https://www.amazon.com/gp/customer-reviews/R1DKMN88M0OLUC"
   }

3. 03Tie ratings to rank

   The product endpoint adds Best Sellers Rank per category. Ratings falling while rank holds is a warning; both falling is a problem.

   GET /v1/product?engine=amazon&asin=B0CF3VGQFL · product.best_sellers_rank

   [
     {
       "rank": 12,
       "category": "PC Gaming Keyboards"
     }
   ]

# Weekly rating snapshot for your products and competitors on Amazon,
# with the share of 1- and 2-star ratings and any new critical reviews.
import csv, datetime, os, requests

API = "https://api.clair.im"
HEADERS = {"Authorization": f"Bearer {os.environ['CLAIR_API_KEY']}"}
ASINS = ["B0CF3VGQFL", "B004YAVF8I"]

def reviews(asin):
    r = requests.get(f"{API}/v1/product/reviews", headers=HEADERS, timeout=90,
                     params={"engine": "amazon", "asin": asin})
    r.raise_for_status()
    return r.json()

today = datetime.date.today().isoformat()
with open("ratings.csv", "a", newline="") as f:
    out = csv.writer(f)
    for asin in ASINS:
        body = reviews(asin)
        p, dist = body["product"], body["product"]["rating_distribution"]
        low = dist.get("1", 0) + dist.get("2", 0)  # percent of ratings
        out.writerow([today, asin, p["rating"], p["ratings_count"], low])
        for review in body["reviews"]:
            if review["rating"] <= 2:
                print(f"{asin} {review['rating']} stars {review['date']}: {review['title']}")

Set CLAIR_API_KEY to a key subscribed to the Amazon Products API. Each call is one request against that API's monthly quota.

• Amazon shows signed-out visitors about 8 to 13 reviews per product and puts the full list behind sign-in. This tracks the rating and distribution over time; it does not collect every review.
• The distribution is in whole percentages, so small shifts on products with few ratings are rounding.
• Ratings and reviews are per marketplace. Check each country separately.