The Product Analytics table provides detailed insights into product, variant, and collection performance, including sales, orders, customer behavior, and ad-driven metrics like clicks, impressions, and spend. Analyzing this table helps uncover sales drivers, understand purchasing trends, and evaluate how marketing efforts impact performance across different levels of your catalog.

🚧
Key Concepts When Using Product Analytics Table Function
Data Structure

The Product Analytics table function provides insights at the product, variant, and collection levels. Data is structured to allow users to analyze performance metrics for individual variants (e.g., specific sizes or colors), aggregate data at the product level (e.g., all sizes and colors of a product), and group performance at the collection level (e.g., curated product groups or merchandising themes).

The id field represents product_id, variant_id, or collection_id depending on the row, ensuring seamless identification across different levels of granularity.

Metrics and Attribution

Metrics such as spend, clicks, impressions, and visits are proportionally distributed (based on quantity, not price) to products, variants, and collections based on their contribution to completed orders, using the Triple Attribution model and lifetime attribution window by default.

📘
Note
event_date is a required field for queries on this table.
The Product Analytics table reflects data from your primary sales platform. It does not include sales data from Amazon or TikTok Shop.

Parameters

Parameters can be used to customize and filter the data in the table, and are applied before aggregation.

Title	ID	Description
Include Free Products	`include_free_products`	Includes products considered "free" based on multi-item discounts. Possible values: `true`, `false` Note: Some discounts are spread across multiple items in an order; if the discount fully covers the price of some of the items, those items are counted as “free".
Include Non-Active Products	`include_non_active_products`	Includes non-active (e.g. draft or pending) products. Possible values: `true`, `false`

Title

Description

Include Free Products

include_free_products

Includes products considered "free" based on multi-item discounts.

Possible values: true, false

Note: Some discounts are spread across multiple items in an order; if the discount fully covers the price of some of the items, those items are counted as “free".

Include Non-Active Products

include_non_active_products

Includes non-active (e.g. draft or pending) products.

Possible values: true, false

Dimensions

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

Title	ID	Type	Description
Event Date	`event_date`	date	The date the order was placed. 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`.
Collection ID	`collection_id`	string	The unique ID of the collection as defined in the sales platform. Example value: `123456789`
Collection Name	`collection_name`	string	The name of the collection as defined in the sales platform. Example values: `Summer Gift Guide`, `Long-Sleeve Packs`, `Christmas Collection`
Entity Type	`entity`	string	The entity type of the item. Example values: `product`, `variant`, `product_collection`
ID	`id`	string	The unique ID of the item for the current row. The value depends on the granularity level of the query (variant-level granularity → `variant_id`; product-level granularity → `product_id`; collection-level granularity → `collection_id`). Example value: `3891505496131`
Inventory Quantity	`inventory_quantity`	string	The current inventory quantity of the product or variant. Example values: `21749`, `57`, `332`
Name	`name`	string	The name of the item for the current row. The value depends on the granularity level of the query (variant-level granularity → `variant_name`; product-level granularity → `product_name`; collection-level granularity → `collection_name`). Example values: `Paring Knife Travel Case`, `Forest Green`, `Christmas Collection`
Product ID	`product_id`	string	The unique ID of the product as defined in the sales platform. Example value: `3891505496131`
Product Image URL	`product_image_url`	string	The URL of the product image.
Product Name	`product_name`	string	The name of the product as defined in the sales platform. This value is always product-level (e.g., “T-Shirt”, “Hoodie”) even when querying variant-level granularity, ensuring each variant row also shows the product it belongs to. Example values: `Green Soft Socks 3-Pack`, `Paring Knife Travel Case`, `Gift Subscription`
Product Tags	`product_tags`	repeated string	Tags associated with the product, assigned by the seller in the sales platform. Example values: `3-pack`, `Sale`, `discount_eligible`
Shop ID	`shop_id`	string	The unique ID of the shop (often corresponds to the shop domain). Can be used to group or filter data by shop in multi-store reports. Example values: `example-US.myshopify.com`, `example-EU.myshopify.com`
Shop Name	`shop_name`	string	The name of the shop. Can be used to group or filter data by shop in multi-store reports. Example values: `example-US`, `example-EU`
SKU	`sku`	string	The SKU (Stock Keeping Unit) for the product or variant as set within the main sales platform. Example values: `GP-BACK-02`, `A02630`, `POP200NAVY`
Variant ID	`variant_id`	string	The unique ID of the variant as set within the main sales platform. Example value: `33193425920151`
Variant Name	`variant_name`	string	The name of the variant as defined in the main sales platform. Example values: `Forest Green`, `M`, `iPhone 14 Pro`
Vendor	`vendor`	string	The vendor of the product or variant. Example values: `Route`, `Canon`, `Corso`, `MyShop`

Measures

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

Title	ID	Type	Description
Added to Cart Events	`added_to_cart_events`	numeric	Number of times the product or variant was added to a cart. Adding multiple units in a single action counts as one event.
Added to Cart Items	`added_to_cart_items`	numeric	Total quantity of the product or variant added to carts. Each unit counts individually, even when multiple units are added in a single action.
Clicks	`clicks`	numeric	Total number of ad clicks attributed to the product or variant, based on its share of units sold per ad. Clicks for Product = (Units Sold for Product / Units Sold for Ad) × Clicks for Ad, summed across all relevant ads and campaigns.
Customers	`customers`	numeric	Total number of unique customers who purchased the product or variant.
Fulfillment Costs	`fulfillment_costs`	numeric	Total costs associated with fulfilling orders that include the product or variant.
Impressions	`impressions`	numeric	Total number of ad impressions attributed to the product or variant, based on its share of units sold per ad. Impressions for Product = (Units Sold for Product / Units Sold for Ad) × Impressions for Ad, summed across all relevant ads and campaigns.
New Customer Fulfillment Costs	`new_customer_fulfillment_costs`	numeric	Total costs associated with fulfilling orders that include the product or variant placed by new customers. Learn how Triple Whale classifies new/returning customers.
New Customer Orders	`new_customer_orders`	numeric	The total number of orders by new customers that contain the product or variant. Learn how Triple Whale classifies new/returning customers.
New Customer Revenue	`new_customer_revenue`	numeric	The total revenue derived from orders by new customers that contain the product or variant. Learn how Triple Whale classifies new/returning customers.
New Customer Units Sold	`new_customer_total_items_sold`	numeric	Total quantity of the product or variant ordered by new customers. Learn how Triple Whale classifies new/returning customers.
New Customer Total Order Value	`new_customer_total_order_value`	numeric	The total revenue of orders by new customers that contain the product or variant, before shipping, taxes, discounts, or refunds. Learn how Triple Whale classifies new/returning customers.
Ads	`number_of_ads`	numeric	Total number of ads contributing to orders containing the product or variant.
Orders	`orders`	numeric	The total number of orders that contain the product or variant.
Repeat Customers	`repeat_customer`	numeric	Total number of unique customers who purchased the product or variant more than once.
Returns	`returns`	numeric	The total number of product or variant units returned.
Order Revenue	`revenue`	numeric	The total revenue from orders that contain the product or variant.
Ad Spend	`spend`	numeric	Total ad spend attributed to the product or variant based on its proportional share of units sold in each ad. This does not include custom ad spend or adjustments for returns. Ad Spend for Product = (Units Sold for Product / Units Sold for Ad) × Ad Spend for Ad, summed across all relevant ads and campaigns.
Units Sold	`total_items_sold`	numeric	The total number of individual units sold for the product or variant.
Total Order Value	`total_order_value`	numeric	The total revenue of orders that contain the product or variant, before shipping, taxes, discounts, or refunds.
Visits	`visits`	numeric	Total number of sessions attributed to the product or variant, based on its share of units sold per ad. Visits for Product = (Units Sold for Product / Units Sold for Ad) × Sessions for Ad, summed across all relevant ads and campaigns.

Derived

Derived fields are metrics that are pre-calculated using multiple measures or advanced formulas.

Title	ID	Type	Description
Average Purchase Price	`avg_purchase_price`	formula	The average price per item sold. Average Purchase Price = Order Revenue / Units Sold
Contribution Margin	`contribution_margin`	formula	The total profit contribution after subtracting fulfillment costs and ad spend from total revenue. Contribution Margin = Order Revenue - Fulfillment Costs - Ad Spend
Contribution Margin Per Item	`contribution_margin_per_item`	formula	The profit contribution for each item sold. Contribution Margin Per Item = (Order Revenue - Fulfillment Costs - Ad Spend) / Units Sold
Cost Per Acquisition (CPA)	`cpa`	formula	The cost to acquire a single order. CPA = Total Ad Spend / Total Orders
Cost Per Click (CPC)	`cpc`	formula	The average cost for each click on an ad. CPC = Total Ad Spend / Total Clicks
Cost Per Thousand Impressions (CPM)	`cpm`	formula	The cost to reach 1,000 ad impressions. CPM = Total Ad Spend / (Total Impressions / 1,000)
Click-Through Rate (CTR)	`ctr`	formula	The percentage of ad impressions that resulted in clicks. CTR = Total Clicks / Total Impressions
Gross Profit	`gross_profit`	formula	The total profit excluding fulfillment costs. Gross Profit = Revenue - Fulfillment Costs
New Customer AOV	`new_customer_aov`	formula	The average order value for new customers, indicating the average spend per order by new customers. New Customer AOV = New Customer Total Order Value / New Customer Orders Learn how Triple Whale classifies new/returning customers.
New Customer CPA	`new_customer_cpa`	formula	The cost to acquire a single new paying customer. New Customer CPA = Total Ad Spend / New Customer Orders Learn how Triple Whale classifies new/returning customers.
New Customer Gross Profit	`new_customer_gross_profit`	formula	The gross profit generated from new customers. New Customer Gross Profit = New Customer Revenue - New Customer Fulfillment Costs Learn how Triple Whale classifies new/returning customers.
New Customer ROAS	`new_customer_roas`	formula	Revenue generated from new customers relative to ad spend. New Customer ROAS = New Customer Revenue / Ad Spend Learn how Triple Whale classifies new/returning customers.
Pixel Conversion Rate	`pixel_conversion_rate`	formula	The percentage of visits who made a purchase. Pixel Conversion Rate = Total Orders / Total Visits
Product AOV	`product_aov`	formula	The average order value for products, representing the average amount spent per order. Product AOV = Total Order Value / Total Orders
Return Rate	`return_rate`	formula	The percentage of purchased items that customers return. Return Rate = Returns / Units Sold
Return on Ad Spend (ROAS)	`roas`	formula	The total revenue generated relative to ad spend. ROAS = Order Revenue / Ad Spend
Repeat Purchase Rate	`rpr`	formula	The percent of purchases made by returning customers. RPR = Repeat Customers / Total Orders