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 GuideWhat You Can Answer With This Table
- Which items drive the most GA4-tracked revenue or refunds? — group by
item_idwithgross_item_revenue,item_revenue- What's the drop-off from view to cart to purchase? — compare
items_viewed,items_added_to_cart,items_purchasedBefore You Query
- Required field:
event_date- Data comes from your connected GA4 property. Without a GA4 connection, this table is empty.
item_idtypically 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.
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: |
| 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: |
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 24 hours ago