GA4 Product Analytics Table

ga4_product_analytics_table

The GA4 Product Analytics table tracks GA4-sourced item-level engagement and revenue (views, add-to-carts, checkouts, purchases). One row per item per day.

📋
Table Guide
What You Can Answer With This Table

Which items drive the most GA4-tracked revenue? — group by item_id with item_revenue or gross_item_revenue

Which items are most viewed vs most purchased? — use items_viewed, items_added_to_cart, items_purchased

What's the drop-off from view to cart to checkout to purchase? — compare items_viewed, items_added_to_cart, items_checked_out, items_purchased

How much item revenue was lost to refunds? — compare gross_item_revenue (pre-refund) to item_revenue (post-refund)

Before You Query

Required field: event_date

Data comes from your connected GA4 property. Without a GA4 connection, this table is empty.

item_id typically maps to product or variant SKU as reported by GA4. Mapping depends on how the GA4 integration is configured.

Revenue figures reflect GA4's event-tracked reporting — item counts and revenue may differ from Triple Whale's Product Analytics table, which draws primarily on your sales platform's order records.

When to Use a Different Table

Need Triple Whale's own product performance (sales-platform revenue + Pixel attribution + ad-integration spend/clicks/impressions per product) → Product Analytics table. Product Analytics blends sales platform data with Pixel and ad integrations; this table uses GA4.

Need product catalog attributes (name, vendor, type, status) → Products table. GA4 Product Analytics only exposes item_id, not full product metadata.

Need GA4 session-level context (landing page, device, country for GA4-tracked sessions) → GA4 Web Analytics table.

View the full Triple Whale Data Ontology →

Dimensions

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

Title	ID	Type	Description
Event Hour	`event_hour`	string	The hour of the day on which the purchase event occurred, according to a 24-hour clock. Based on the shop time zone at the moment of the event (or the user time zone, if no sales platform is connected). Example values: `07`, `16`, `21`
Event Date	`event_date`	date	The date the purchase event occurred. 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 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`.
Item ID	`item_id`	string	The unique identifier for the product, as reported by GA4. Typically maps to the product or variant SKU. Example values: `57404707913`, `sku123`

Measures

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

Title	ID	Type	Description
Gross Item Revenue	`gross_item_revenue`	numeric	The total revenue from items only, before any discounts, tax, shipping, or refunds. Gross Item Revenue = Item Price x Item Quantity
Item Revenue	`item_revenue`	numeric	The total revenue from items only, before tax and shipping (but after refunds). Item Revenue = Item Price x Item Quantity - Refunds
Items Added to Cart	`items_added_to_cart`	numeric	The number of items added to a cart. Each unit counts separately.
Items Checked Out	`items_checked_out`	numeric	The number of items in the cart when the checkout process was initiated. Each unit counts separately.
Items Purchased	`items_purchased`	numeric	The number of items included in purchase events. Each unit counts separately.
Items Viewed	`items_viewed`	numeric	The number of items that the customer viewed.

Updated about 8 hours ago