The Reviews table provides detailed data on customer reviews, including the content, sentiment, and associated metadata such as reviewer attributes and product details. By querying this table, you can analyze review trends, assess customer sentiment, and identify areas for improvement in your products or services.

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Note
event_date is a required field for queries on this table.

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Table Guide
What This Table Represents
Post-purchase product and service reviews and sentiment data from review platforms (e.g., Okendo, Yotpo). One row per review. Includes review content, rating, sentiment analysis, reviewer attributes, and the associated product.
What You Can Answer With This Table

What are customers saying about our products? — use content, title, sentiment

What is our average product rating? — use average_rating or aggregate rating

Which products get the best or worst reviews? — group by product_id with average_rating

What percentage of reviews recommend the product? — use recommended_rate

Where are our reviewers located? — use reviewer_country_code, reviewer_country_name

Key Relationships
Table Join Key What the Join Enables
Orders order_id Link reviews to purchase details (revenue, customer, fulfillment)
Products product_id Link reviews to product catalog attributes (name, type, vendor)

When to Use a Different Table

Need customer support tickets or agent performance → CS Tickets table. Reviews capture post-purchase sentiment; CS Tickets track support cases and resolution.

Need customer identity or profile data → Customers table. Reviews includes reviewer attributes but has no customer_id for direct customer joins.

Need post-purchase survey responses → Post-Purchase Survey table. Surveys capture attribution and source data; reviews capture product sentiment.

View the full Triple Whale Data Ontology →

Table	Join Key	What the Join Enables
Orders	`order_id`	Link reviews to purchase details (revenue, customer, fulfillment)
Products	`product_id`	Link reviews to product catalog attributes (name, type, vendor)

Dimensions

Dimensions are immutable properties that can be used for grouping data.

Title	ID	Type	Description
Event Date	`event_date`	date	The date the review was submitted. Based on the shop time zone at the moment of the event (or the user time zone, if no sales platform is connected).
Event Day	`event_date.day`	date	The day on which the event occurred. Derived from `event_date`.
Event Week	`event_date.week`	date	The Sunday of the week during which the event occurred. Derived from `event_date`.
Event Month	`event_date.month`	date	The month during which the event occurred. Derived from `event_date`.
Event Quarter	`event_date.quarter`	date	The first month of the quarter during which the event occurred. Derived from `event_date`.
Event Year	`event_date.year`	date	The year during which the event occurred. Derived from `event_date`.
Attributes with Rating	`attributes_with_rating`	record repeated	A list of rating attributes within the review. Set in the reviews platform.
Minimum Rating Label	`attributes_with_rating.min_label`	string	The label for the minimum rating value. Example values: `Runs small`, `Disappointing`
Mid Label Rating	`attributes_with_rating.mid_label`	string	The label for the midpoint rating value. Example values: `True to size`, `As expected`
Title	`attributes_with_rating.title`	string	The title of the rating attribute. Example values: `Size Range`, `Quality`
Type	`attributes_with_rating.type`	string	The type of the rating attribute. Example values: `range`, `multi-select`, `single-select`
Value	`attributes_with_rating.value`	string	The rating value for the attribute. Example values: `-1`, `0`, `0.5`, `2`
Maximum Rating Label	`attributes_with_rating.max_label`	string	The label for the maximum rating value. Example values: `Runs large`, `Exceeds expectations`
Contains Profanity	`contains_profanity`	boolean	True if the review contains profanity. Possible values: `true`, `false`
Content	`content`	string	The text content of the review. Example values: `Fits nicely`, `Better quality than it looked in the pictures`
Review ID	`id`	string	The unique identifier for the review. Example value: `948f450e-5b38-4a2e-ace6-470b7b5535cf`
Is Recommended	`is_recommended`	boolean	True if the product is recommended by the reviewer. Possible values: `true`, `false`
Marketplace	`marketplace`	string	The marketplace where the review was submitted. Example value: `shopify`
Order ID	`order_id`	string	The unique identifier for the order associated with the review. Example value: `4930225799243`
Platform	`platform`	string	The platform through which the review was submitted. Example values: `okendo`, `yotpo`
Product ID	`product_id`	string	The unique identifier of the reviewed product. Example value: `3891505496131`
Product Name	`product_name`	string	The name of the reviewed product. Example values: `Green Soft Socks 3-Pack`, `Paring Knife Travel Case`, `Gift Subscription`
Review Type	`review_type`	string	The type of review submitted. Example value: `product`
Reviewer Attributes	`reviewer_attributes`	record repeated	Attributes associated with the reviewer.
Reviewer Title	`reviewer_attributes.title`	string	The title of the reviewer.
Reviewer Type	`reviewer_attributes.type`	string	The type of the reviewer.
Reviewer Value	`reviewer_attributes.value`	string	The value of the reviewer.
Reviewer Country Code	`reviewer_country_code`	string	The country code of the reviewer. See list of countries. Example values: `US`, `CA`, `GB`
Reviewer Country Name	`reviewer_country_name`	string	The full name of the reviewer's country. See list of countries. Example values: `United States`, `Canada`, `United Kingdom`
Reviewer Display Name	`reviewer_display_name`	string	The display name of the reviewer.
Reviewer Email	`reviewer_email`	string	The email address of the reviewer.
Reviewer Is Verified	`reviewer_is_verified`	boolean	True if the reviewer is a verified customer. Possible values: `true`, `false`
Reviewer Name	`reviewer_name`	string	The name of the reviewer.
Reviewer Verified Status	`reviewer_verified_status`	string	The verification status of the reviewer.
Sentiment	`sentiment`	string	The sentiment analysis result for the review content. Example values: `positive`, `mixed`, `negative`
Status	`status`	string	The status of the review. Example values: `approved`, `published`, `unpublished`
Title	`title`	string	The title of the review. Example values: `Almost perfect`, `Would not recommend`, `Absolutely beautiful!`
Variant ID	`variant_id`	string	The unique identifier of the reviewed product variant. Example value: `29275946877001`

Measures

Measures are numeric fields that can be aggregated and/or combined to calculate new metrics.

Title	ID	Type	Description
Helpful Count	`helpful_count`	numeric	The number of helpful votes the review has received.
Rating	`rating`	numeric	The rating score assigned by the reviewer.
Unhelpful Count	`unhelpful_count`	numeric	The number of unhelpful votes the review has received.