REVIEWS.ai provides an easy to use API, allowing you to import your review and Q&A data to other business intelligence tools such as PowerBI, Tableau or Looker.

To get API tokens and other relevant data, click API from the top navigation menu. This will open the below API page.

If your preferred business tool requires a REVIEWS.ai token, simply click: GENERATE.

Refer to the table for definitions and structure of the various parameters, such as IDs and time periods.

Reviews.ai API Documentation

The Reviews.ai API lets you retrieve product and review data efficiently. You can list the products, locations, and apps you monitor, pull individual reviews with filters, get exact aggregated statistics, track daily ratings, discover review topics, and export filtered review sets to CSV.

General Information

Base URL: https://app.reviews.ai/api/

Authentication: every request requires your API token as a query parameter: ?token={your_token}. Keep your token confidential.

Response envelope: all endpoints return JSON in the form:

json

{ "type": "data", "result": { ... }, "created": 1788530179 }

Errors return "type": "error" with details in result.

Rate limit: maximum 300 requests per minute.

Date filtering: all date filters (period, from/to) apply to the Date field, the date the customer posted the review on the retailer or platform.

Filtering by ids: up to 100 ids per call. For larger groups, omit ids entirely (covers all products) or filter by category, tag, or brands instead of listing ids. Custom sets larger than 100 can be split into batches and merged.

1. Get Products

Lists every product, location, or app your account monitors, with the ids used by all other endpoints.

Endpoint

GET https://app.reviews.ai/api/products.php?token={your_token}

Request parameters: none.

Response fields (per product)

Field	Example	Description
id	"1868239"	Product id, used in all other endpoints
title	"Multifunction Pizza Oven"	Product, location, or app name
brand	"OverMaker"	Brand the product belongs to
sku	"REW1270"	SKU or listing identifier
category	"Home & Kitchen"	Category (for location accounts, often the state or region)
tag	"Pizza Maker"	Tag (for location accounts, often the city)
rating	4.12	Lifetime average rating
totals	388	Lifetime review count

2. Get Ratings (Daily Rating Tracking)

Retrieves daily rating summaries for one or more products, optionally filtered by retailer or platform. Use this endpoint to monitor day-by-day rating changes.

Endpoint

GET https://app.reviews.ai/api/ratings.php?token={your_token}

Request parameters

Parameter	Example	Description
ids (required)	ids=1868239,1868246	One or more product ids, comma-separated
period	period=month	Time window: day, days_7, or month
source	source=walmart	Retailer or platform filter
limit	limit=500	Maximum rows returned

Example call

https://app.reviews.ai/api/ratings.php?token={your_token}&ids=186839&period=month&source=walmart&limit=500

3. Get Reviews

Retrieves individual reviews filtered by products, brands, categories, sources, dates, and star ratings.

Endpoint

GET https://app.reviews.ai/api/reviews.php?token={your_token}

Request parameters

Parameter	Example	Default	Description
ids / brands / category / tag / source	ids=1868329,1868246 or brands=Sony,Microsoft or category=kitchen or tag=food or source=walmart	N/A	Filter reviews by product ids, brands, category, tag, or source. Multiple values comma-separated. Up to 100 ids per call.
period	period=day	day	Time window: day, days_7, or month. Ignored when from/to is set.
from / to	from=2026-06-01&to=2026-06-30	N/A	Custom date range (YYYY-MM-DD, inclusive). Takes precedence over period. Maximum span 366 days.
page	page=1	1	Page number for pagination.
limit	limit=20	10	Reviews per page. Valid values: 10, 20, 30, 50, 100. Other values fall back to 10.
min_rating / max_rating	min_rating=1&max_rating=3	All	Star rating range (1 to 5). Send both bounds together.
status	status=active	All	Filter by review status.

Example call

https://app.reviews.ai/api/reviews.php?token={your_token}&ids=186839&from=2026-06-01&to=2026-06-30&limit=100&page=1&min_rating=1&max_rating=3

Response structure

The result contains the review list plus pagination info:

Field	Description
count	Total number of reviews matching the filters (across all pages)
page	Current page
per_page	Reviews per page
total_pages	Total pages, computed as ceil(count / per_page)
reviews	Array of review objects (fields documented below)

Best practices

Use pagination: set limit (max 100) and page for efficient retrieval.
For total counts, read the count field instead of paging through everything.
For aggregate statistics (averages, distributions, NPS, topics), use the Summary endpoint instead of paginating reviews.
Combine filters (brands, ids, category, dates) for precise results.
Contact your account manager for large data exports. To export data beyond two years, go to Reports > Charts & Graphs and click Download .csv.

4. Get Summary (Exact Aggregated Statistics)

Returns exact statistics computed server-side over all reviews matching the filters: review count, average rating, star distribution, NPS, top positive and negative topics, and a per-product breakdown. One call answers questions like "how did June go" or "which products need attention" without paginating through reviews.

Endpoint

GET https://app.reviews.ai/api/summary.php?token={your_token}

Request parameters

Parameter	Example	Description
ids / brands / category / tag / source	ids=1868329	Same filtering as Get Reviews. Up to 100 ids per call.
period	period=month	Time window: day, days_7, or month.
from / to	from=2026-06-01&to=2026-06-30	Custom date range (YYYY-MM-DD, inclusive). Takes precedence over period.

Example call

https://app.reviews.ai/api/summary.php?token={your_token}&brands=OvenMaker&from=2026-08-01&to=2026-08-31

Response structure

json

{   "type": "data",   "result": {     "reviews": {       "count": "546",       "rate": 4.0036,       "stars": { "5": 342, "4": 46, "3": 48, "2": 38, "1": 72 },       "nsp": "33.69"     },     "topics": {       "positive": { "Ease of Use": 53, "Satisfaction": 52 },       "negative": { "Durability": 17, "Size": 12 }     },     "ids": {       "186846": { "count": "76", "rate": "4.11", "nsp": "40.78" },       "186302": { "count": "56", "rate": "4.25", "nsp": "46.42" }     }   },   "created": 1788530179 }

Field	Description
reviews.count	Exact number of reviews matching the filters
reviews.rate	Average rating
reviews.stars	Review count per star level (5 down to 1)
reviews.nsp	Net Promoter Score: (5-star reviews minus 1-to-3-star reviews) / total, as a percentage
topics.positive / topics.negative	Topic labels with the number of reviews mentioning each
ids	Per-product breakdown: every product with reviews in the window, each with its own count, rate, and nsp. Use it to rank products and decide which ids to analyze further.

5. Get Topics

Returns the positive and negative topic labels found in reviews matching the filters, with the number of reviews mentioning each.

Endpoint

GET https://app.reviews.ai/api/topics.php?token={your_token}

Request parameters

Parameter	Example	Description
ids / brands / category	ids=1868329	Filter by product ids, brands, or category. Up to 100 ids per call.
from / to	from=2026-06-01&to=2026-06-30	Date range (YYYY-MM-DD, inclusive). Always pass a range; without one, only the most recent day is covered.

Example call

https://app.reviews.ai/api/topics.php?token={your_token}&ids=186839&from=2026-06-01&to=2026-06-30

6. Export Reviews (CSV)

Generates a CSV file of all reviews matching the filters and returns a download link. Use this for full data exports instead of paginating Get Reviews.

Endpoint

GET https://app.reviews.ai/api/export.php?token={your_token}

Request parameters

Accepts the same filters as Get Reviews: ids, brands, category, tag, source, from, to, min_rating, max_rating, status. No page or limit; the export covers the full matching set, up to 5,000 rows.

Example call

https://app.reviews.ai/api/export.php?token={your_token}&brands=OvenMaker&from=2026-08-01&to=2026-08-31&min_rating=1&max_rating=2

Response structure

json

{   "type": "data",   "result": {     "download_url": "https://app.reviews.ai/exports/rev_a1b2c3...csv",     "row_count": 127,     "truncated": false,     "expires_at": "2026-09-05T14:31:00+00:00"   },   "created": 1788530179 }

Field	Description
download_url	Direct link to the CSV file. The unguessable URL is the access control; share it only with people who may see the data.
row_count	Number of review rows in the file
truncated	true if the matching set exceeded 5,000 rows and the file was cut off
expires_at	Link expiry; files are removed after 24 hours

The CSV is UTF-8 with BOM, so it opens correctly in Excel including special characters.

Review Response Fields

Fields returned per review by Get Reviews and included in CSV exports:

Field	Example	Description
Id	"443467335"	Unique identifier for the review
Product Id	"74756"	Unique identifier for the reviewed product
Date	"02/17/2025"	The date the customer posted the review on the retailer or platform. All date filters apply to this field.
Brand	"Iams Store"	Brand associated with the product
Product	"IAMS Adult Minichunks Small Kibble..."	Full product name
Rating	"5"	Star rating (1 to 5)
Source	"amazon"	Platform where the review was posted
Review Status	"Active"	Whether the review is currently active, inactive, or filtered
Review Status Date	"02/18/2025"	System date when the review status was last updated in Reviews.ai
Review Posted Date	"02/18/2025"	System date when the review was recorded by Reviews.ai

Note: use Date for all time-based analysis. Review Posted Date and Review Status Date are internal system timestamps and may lag the true review date by ingestion time.

Best Practices

Prefer aggregates: for counts, averages, distributions, and themes, one Summary call replaces many paginated Reviews calls.
Use the per-product breakdown: the ids block in Summary ranks every product by review volume with its rating and NPS, ideal for finding what needs attention before drilling into review text.
Filter smart: for large groups of products, use category, tag, or brands instead of long id lists.
Rate limits: maximum 300 requests per minute.
Secure your token: keep it confidential; anyone holding it can read your review data. Rotate it from your dashboard if it is ever exposed.

API Response Fields Documentation

The API returns a structured JSON response with detailed review data. Below is a breakdown of the fields included in the response:

Basic Review Details

Field Name	Example Value	Description
Id	`"44346733"`	Unique identifier for the review.
Product Id	`"74756"`	Unique identifier for the reviewed product.
Date	`"02/17/2025"`	Date when the review data was recorded.
Brand	`"Iams Store"`	Name of the brand associated with the product.
Product	`"IAMS Adult Minichunks Small Kibble High Protein Dry Dog Food with Real Chicken, 30 lb. Bag"`	Full product name.
Rating	`"5"`	Star rating given by the reviewer (scale of 1-5).
Source	`"amazon"`	The platform where the review was posted.
Review Status	`"Active"`	Indicates if the review is currently active, inactive, or filtered.
Review Status Date	`"02/18/2025"`	Date when the review status was last updated.
Review Posted Date	`"02/18/2025"`	The original posting date of the review.

Reviewer Details

Field Name	Example Value	Description
Reviewer Name	`"U44346733"`	Anonymized or publicly available name of the reviewer.
Reviewer ID	`"AFGL5GGHTKIYXJFSRM6WJFRSW2CA"`	Unique identifier for the reviewer.

Review Content

Field Name	Example Value	Description
Review	`"My dog has been eating IAMS Minichunks for years, and it’s been a great choice for her!"`	The full text of the review.
Review ID	`"RK9NTYSVJY564"`	Unique identifier for the review entry.
ReviewTranslated	`""`	Translated review content (if applicable).
Title	`"Dog Approved"`	Review title given by the user.

Review Attributes & Metadata

Field Name	Example Value	Description
Syndicated	`"No"`	Indicates if the review was syndicated from another platform.
Incentive Program	`"N/A"`	Specifies if the review was incentivized (e.g., discounts, free products).
Verified Review	`"Yes"`	Confirms whether the review is verified.
Helpful Votes	`0`	Number of users who marked the review as helpful.
Top Contributor	`"No"`	Indicates if the reviewer is recognized as a top contributor.
Media (Picture/Video)	`"No"`	Indicates whether the review includes media attachments.
Displayed Rating	`"N/A"`	The rating displayed to users on the review platform.

Product & Pricing Information

Field Name	Example Value	Description
Price	`"N/A"`	Price of the product at the time of review (if available).
Size	`"N/A"`	Product size specified in the review.
Color	`"N/A"`	Product color specified in the review.
Edition	`"N/A"`	Product edition specified in the review.
Style	`"N/A"`	Product style specified in the review.
Other Attributes	[] 0: "flavor name: Beef" 1:	Reserved for additional attributes that do not match predefined product information categories such as size and color.
Model	`"N/A"`	Product model (if available).
ASIN	`"B00BD741WM"`	Amazon Standard Identification Number (ASIN).
ASIN Reviews Link	`"https://www.amazon.com/product-reviews/B00BD741WM/ref=cm_cr_arp_d_rvw_fmt?ie=UTF8"`	Direct link to Amazon reviews for the product.
SKU	`"B00BD741WM"`	Stock Keeping Unit (SKU) for the product.

Category & Tagging

Field Name	Example Value	Description
Category	`"Pet Supplies"`	The category to which the product belongs.
Tag	`"Dry"`	Relevant tag assigned to the product.
Keyword Tagging	`"N/A"`	Keywords assigned to the review for search and classification.

Sentiment Analysis & NPS

Field Name	Example Value	Description
NPS	`"76.92"`	Net Promoter Score (percentage-based customer loyalty indicator).
Sentiment Score	`0.9`	Score indicating positive or negative sentiment (range: -1 to 1).
Sentiment Magnitude	`4.8`	Strength of the sentiment detected in the review.

Topic Categorization

Field Name	Example Value	Description
Negative Topic Categories	`"N/A"`	Identified negative themes in the review.
Positive Topic Categories	`"Long-term Satisfaction,Kibble Size,Taste,Ingredients,Digestive Health,Coat Health"`	Identified positive themes in the review.
Negative Top Level Topics	`"N/A"`	Broader negative topics identified.
Positive Top Level Topics	`"Satisfaction & Enjoyment: Long-term Satisfaction; Size & Quantity: Kibble Size; Taste & Texture: Taste; Ingredients & Composition: Ingredients; Digestion & Stomach Issues: Digestive Health; Coat Health: Coat Health"`	Higher-level positive topics extracted from the review.

Review Interaction & Response

Field Name	Example Value	Description
Status	`"Open Ticket"`	Internal status of the review (e.g., open, closed).
Replied To	`"No"`	Indicates whether the brand has responded to the review.
Replied User	`"N/A"`	Name of the user who replied (if applicable).
Replied Date	`"N/A"`	Date when the response was posted.
Internal Comments	`"N/A"`	Internal notes added by the support team.

Links & System Identifiers

Field Name	Example Value	Description
Permalink	`"https://www.amazon.com/gp/customer-reviews/RK9NTYSVJY564/ref=cm_cr_othr_d_rvw_ttl?ie=UTF8&ASIN=B00BD741WM"`	Direct link to the original review on Amazon.
System ID	`"44346733"`	Internal system identifier for the review.

Additional Metadata

Field Name	Example Value	Description
Path2Purchase	`"N/A"`	Details about the customer's journey before purchasing the product.
Syndicated From	`"N/A"`	Indicates if the review was syndicated from another source.