Get Adidas product reviews API

Endpoint facts

Method

GET

API path

/adidas/product/reviews

Auth

apiKey

Credits

4 credits/request

Platform

Adidas

Response schema

#/definitions/adidas.productReviewsResponseDoc

Overview

Returns one page of customer reviews for an Adidas product model, plus the model's rating summary: overall rating, star histogram, percentage of reviewers who recommend it, per-attribute averages (Size, Width, Comfort, Quality with their own scale labels), and Adidas's AI-generated review digest when one exists. Each review carries the rating, headline, body, author nickname, purchased colorway, helpful/not-helpful vote counts, badges, customer photos, and submission time. model_number is the Adidas model number (e.g. SAMBAU2312) -- NOT the SKU: take it from an adidas_search result's products[].model_number field, which is a different value from products[].id. Reviews are returned 10 per page. Reviews are scoped to review text written in the requested locale's language, and most of the US catalog's reviews are English, so a non-English locale commonly returns rating statistics and a localized summary with an empty reviews list. A model with no reviews -- including a well-formed but unrecognized model_number -- returns an empty reviews list rather than an error, because Adidas answers 200 with a zero count rather than 404. Developers commonly use this endpoint for data enrichment, monitoring, research dashboards, internal automation, and agent-native workflows that need repeatable structured public web data. Authentication uses the documented Crawlora headers, and usage is metered with the credit cost shown on this page.

Authentication

Send your scraping API key in the x-api-key header. Use the console API Keys page to rotate or select the active key.

Billing

Endpoint usage is metered in credits. The plan prices, included credits, limits, and overage rates below match the active backend billing configuration.

Credit cost

4 credits/request

Charged response

Successful 2xx responses

Infrastructure behavior

This endpoint is executed through Crawlora's managed scraping infrastructure.

• Proxy strategy: managed automatically where needed
• Browser rendering: enabled for supported targets that require rendered HTML or JavaScript execution
• Browser cluster: supported dynamic workloads can be routed through distributed browser instances
• Retry behavior: automatic retry/fallback may be used depending on endpoint type
• Challenge handling: challenged pages or unusable upstream HTML are detected and surfaced clearly when they cannot be used
• Billing: credits are charged only for successful 2xx responses
• Observability: responses include request context where available

Response behavior

- `total_reviews` counts the reviews matching this request's filters, so it shrinks when `rating` is set. `rating_count` is the model's unfiltered review count from the rating summary and stays constant. - `rating_histogram` is ascending: index 0 is the 1-star count, index 4 the 5-star count. - `secondary_ratings[]` are the per-attribute scales Adidas collects (`Size`, `Width`, `Comfort`, `Quality`), each with its own `min_label`/`mid_label`/`max_label` wording in the requested locale. A scale with no midpoint wording returns an empty `mid_label`. - `summary` is Adidas's AI-generated digest of the model's reviews. It is present only when the upstream has generated one, is localized by `locale`, and carries the upstream's own `disclaimer`, which should be shown alongside the text. - Reviews are scoped to review text written in the requested locale's language. Most of the US catalog's reviews are English, so a non-English `locale` commonly returns the rating statistics and a localized `summary` with an empty `reviews` list. - A model with no reviews — including a well-formed but unrecognized `model_number` — returns an empty `reviews` list with `total_reviews: 0` rather than an error, because Adidas answers `200` with a zero count rather than `404`. - `recommended` is omitted when the upstream did not record a recommendation for that review. `color` (the purchased colorway), `badges`, `photos`, and `responses` (brand replies) are omitted when empty. - `source_url` is the reviews request; `ratings_source_url` is the sibling rating-summary request the same call makes. Example response: ```json {"code":200,"msg":"OK","data":{"model_number":"SAMBAU2312","locale":"en_US","page":1,"page_size":10,"total_pages":338,"total_reviews":3371,"count":1,"rating_count":3371,"overall_rating":4.8,"recommended_percentage":97,"rating_histogram":[62,22,50,223,3014],"secondary_ratings":[{"name":"Size","label":"Size","average_rating":3.06,"value_range":5,"min_label":"Too small","mid_label":"Perfect","max_label":"Too large"}],"summary":{"text":"* Customers consistently praise all-day comfort and lightweight feel","title":"REVIEW_SUMMARY","type":"TEXT","detail":"BULLET_FORMAT_SUMMARY","disclaimer":"This summary is generated by artificial intelligence based on customer reviews."},"source_url":"https://www.adidas.com/api/models/SAMBAU2312/reviews?bazaarVoiceLocale=en_US&includeLocales=en%2A&limit=10&offset=0","ratings_source_url":"https://www.adidas.com/api/models/SAMBAU2312/ratings?bazaarVoiceLocale=en_US","fetched_at":"2026-09-05T13:45:00Z","reviews":[{"id":"184365254","rating":5,"rating_range":5,"headline":"A must for your wardrobe","body":"I love the color and the snakeskin design. I've gotten so many compliments on them.","author":"LizD74","color":"Focus Olive / Off White / Gum","locale":"en_US","recommended":true,"badges":["IncentivizedReview"],"submitted_at":"2026-09-05T03:58:39Z","submitted_date":"September 5, 2026"}]}} ```

Error behavior

Crawlora does not silently return bad data when the upstream page cannot be used.

When possible, Crawlora returns structured error context so your integration can retry, back off, or inspect the request.

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