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Guide 47 · Ecommerce · GA4 + Tag Manager

Read the Ecommerce purchases report: items viewed, added to cart, purchased, and item revenue

Checked 11 November 2026 · Verification: reference file checked in Python (figures recomputed from the worked example) · Steps traced to Google's developer docs and Analytics Help, opened 11 November 2026 · 5-minute read

The Ecommerce purchases report is the item-level table: one row per product, with items viewed, items added to cart, items purchased, and item revenue side by side.

Expected signal

After the events flow, Reports, then Life cycle, then Monetization, then Ecommerce purchases shows one row per item. In the worked table below, the tee reads 40 viewed, 9 added, 6 purchased, 60.06 revenue; the grey tee reads 25 viewed, 4 added, 2 purchased, 42.02 revenue.

Download the reference: the ecommerce-purchases-report reference (JSON) (826 bytes, MD5 10b6cf2c49b2ebc30d384f27aeea38cc). It holds the event parameters, the worked example, and the recomputed figures.

What you need

  • Ecommerce events flowing with items arrays. The report is built from the items array in view_item, add_to_cart, and purchase. Without the arrays, there are no rows.
  • The product record behind each item. Rows are item names by default, and the report can switch to item ID, item brand, or item category. The worked table uses Google's two example items.
  • One worked table to read against. The counts below are the worked example's inputs, labelled as such; the rates and the revenue are recomputed from them.

The trace

  1. Open the report in the Life cycle collection. In Analytics, click Reports on the left, then Life cycle, then Monetization, then Ecommerce purchases. The report is a pre-made detail report in the Monetization topic, listed alongside the Monetization overview, the Purchase journey, and the Checkout journey.
  2. Read each row across the four columns. In the worked table, the Stan and Friends Tee was viewed 40 times, added to cart 9 times, and purchased 6 times, for item revenue of 10.01 × 6 = 60.06. The grey tee was viewed 25 times, added 4 times, and purchased 2 times, for item revenue of 21.01 × 2 = 42.02. The two rows together are 60.06 + 42.02 = 102.08 in item revenue, which matches the purchase revenue of the two orders.
  3. Compare the columns as rates, not just counts. The tee's view-to-cart rate is 9 out of 40, or 22.5 percent; its cart-to-purchase rate is 6 out of 9, or 66.7 percent. The grey tee's view-to-cart rate is 4 out of 25, or 16.0 percent; its cart-to-purchase rate is 2 out of 4, or 50.0 percent. The two products fail at different steps: the grey tee is rarely added after being viewed, while the tee is added often and bought often.
  4. Switch the dimension to find the grouping that matters. The report defaults to Item name, and the dimension can change to Item ID, Item brand, or Item category. A store with many variants of one product reads the report by item ID; a store comparing brands reads it by item brand.
  5. Trace an empty or broken row back to its event. Items viewed comes from view_item, items added to cart from add_to_cart, items purchased from purchase. A product with page views in the Pages and screens report but zero items viewed has a page_view firing and no view_item. A row reading (not set) in the item name column means the items array arrived without item_id and item_name.

Dead ends

DEAD END — ITEMS VIEWED AT ZERO WITH PAGE VIEWS PRESENT. Items viewed comes from the items array in view_item, not from page_view. A product page with traffic and no view_item shows page views in the Pages and screens report and zero items viewed here. The fix is the event, not the report.

DEAD END — THE (NOT SET) ROW. A row reading (not set) means the items array arrived without item_id and item_name. There is nothing to group the revenue by, and no fix after the fact can attach a name to it. The ID or the name must be in the push.

DEAD END — ITEM REVENUE READ AS MARGIN. Item revenue is price times quantity sold: 60.06 for the tee, 42.02 for the grey tee. Analytics records price and revenue, not cost, so it cannot calculate margin. Profitability has to come from your own cost data, joined by item ID outside Analytics.

End state

The Ecommerce purchases report reads as one row per item with four numbers: items viewed, items added to cart, items purchased, and item revenue. In the worked table the tee reads 40, 9, 6, and 60.06; the grey tee reads 25, 4, 2, and 42.02; the rows total 102.08. The view-to-cart and cart-to-purchase rates say where each product loses buyers.

Sources

Checked 11 November 2026. The report structure above is the one in Analytics Help and Google's purchase tutorial, both opened 11 November 2026. The worked table's counts are the example's stated inputs; the rates and revenue were recomputed in Python: 10.01 × 6 = 60.06, 21.01 × 2 = 42.02, 60.06 + 42.02 = 102.08, 9 out of 40 is 22.5 percent, 6 out of 9 is 66.7 percent, 4 out of 25 is 16.0 percent, and 2 out of 4 is 50.0 percent. No step was run inside a live Analytics property, because that needs a Google sign-in and this site does not sign in as anyone.