Best Buy

Best Buy Reviews API

Customer reviews of one bestbuy.com (US) product by SKU or URL, 20 per page, sorted most relevant (default), most helpful, newest, oldest, highest or lowest rated, optionally only one star rating. Returns the review summary (average rating, review count, recommended percent, star histogram, and the most mentioned pros and cons with mention counts), total results for the filter, page count and has_more. Each review has id, title, text, rating, author, date, recommended flag, verified-purchase and incentivized flags, days of ownership, helpful and not-helpful votes, badges, photos, the site it was syndicated from and the brand's response. An unknown SKU is a 404 and is not charged. Costs 2 credits per request.

POST/api/v1/bestbuy/reviews

Authorizations

Authorizationstringheaderrequired

Bearer authentication header of the form Bearer <token>, where <token> is your Scavio API key (e.g. Bearer sk_live_your_key).

Body

application/json

skustring

Best Buy SKU (a search result's sku). Pass sku or url.

Example: 6607832

urlstring

A bestbuy.com product URL that names a SKU (/sku/<sku> or <sku>.p?skuId=<sku>). Used when sku is not given.

pageinteger

Reviews page, 1-based, 20 reviews per page, up to 500. Defaults to 1.

Example: 1

sortstring

most_relevant (default), most_helpful, newest, oldest, highest_rated or lowest_rated.

ratinginteger

Only reviews with this many stars, 1-5.

Example: 1

Request

from scavio import ScavioClient

client = ScavioClient(api_key="sk_live_your_key")

res = client.best_buy.reviews(sku="6607832", sort="lowest_rated")["data"]

print(res["average_rating"], res["review_count"], res["recommended_percent"])
print([(c["feature"], c["mentions"]) for c in res["cons"]])
for r in res["reviews"]:
    print(r["rating"], r["title"], r["days_of_ownership"], r["text"][:80])

Response

"sku": "6607832",

"name": "Insignia™ - 55" Class F50 Series LED 4K UHD Smart Fire TV",

"url": "https://www.bestbuy.com/product/insignia-55-class-f50-series-led-4k-uhd-smart-fire-tv/J2FPJKSV76/sku/6607832",

"page": 1,

"page_size": 20,

"sort": "newest",

"rating_filter": null,

"average_rating": 4.6,

"review_count": 4031,

"recommended_percent": 93,

"total_results": 4029,

"total_pages": 202,

"has_more": true,

"count": 20,

"response_time": 1871

}

from scavio import ScavioClient client = ScavioClient(api_key="sk_live_your_key") res = client.best_buy.reviews(sku="6607832", sort="lowest_rated")["data"] print(res["average_rating"], res["review_count"], res["recommended_percent"]) print([(c["feature"], c["mentions"]) for c in res["cons"]]) for r in res["reviews"]: print(r["rating"], r["title"], r["days_of_ownership"], r["text"][:80])