A GA4 ecommerce dashboard serves a different purpose than a campaign performance dashboard. A campaign dashboard helps you optimize spend. An ecommerce dashboard helps you understand buying behavior — what is selling, where customers are dropping off, which channels are producing revenue, and whether the product mix is shifting.
This post walks through building a GA4-connected ecommerce dashboard that answers those questions without requiring the client to dig through GA4’s interface.
What GA4 Ecommerce Data Is Available in Looker Studio
The GA4 connector in Looker Studio exposes the standard ecommerce dimensions and metrics from your GA4 property, assuming you have ecommerce tracking implemented.
Key metrics available:
- Purchases (number of completed transactions)
- Purchase Revenue (total revenue from completed purchases)
- Add to Carts
- Checkouts
- Cart-to-View Rate
- Purchase-to-View Rate
- Items Purchased
- Item Revenue
Key dimensions available:
- Transaction ID
- Item Name
- Item Category (and subcategories 1-5)
- Item Brand
- Item ID
- Order Coupon
If these fields are not appearing in your data source, it means ecommerce tracking is not fully implemented in GA4. The GA4 connector only surfaces what has been tracked.
Page 1: Revenue Overview
The top row of scorecards should give an immediate revenue snapshot:
- Purchase Revenue (currency formatted, with comparison period)
- Purchases (with comparison period)
- Average Order Value — calculated field:
Purchase Revenue / NULLIF(Purchases, 0) - Add to Carts
- Checkout-to-Purchase Rate — calculated field:
Purchases / NULLIF(Checkouts, 0)
Below the scorecards, add a time series chart showing daily Purchase Revenue and Purchases on dual axes. Revenue fluctuates with order size, so showing both volume and revenue together reveals whether a revenue dip is from fewer orders or smaller orders — two different problems with different fixes.
Add a donut or bar chart showing Purchase Revenue by Session Default Channel Group. This answers the perennial question: which channel is actually driving revenue, not just traffic?
Page 2: Product Performance
This is the page a merchandising team or store owner will use most.
Add a table with:
- Item Name
- Item Category
- Items Purchased (volume sold)
- Item Revenue
- Item Purchase Quantity (if available)
- Cart-to-View Rate
- Purchase-to-View Rate
Sort by Item Revenue descending. Enable heatmap on Item Revenue and Items Purchased. Set row limit to 25 with pagination.
Add a bar chart alongside the table showing top 10 products by revenue. This gives visual context for the long tail in the table — the chart shows the products that matter most, the table lets you explore the rest.
Add a dropdown filter for Item Category so buyers can filter to a specific product category.
One common issue: GA4 ecommerce data in Looker Studio sometimes shows product names with minor variations — capitalization differences, trailing spaces — that cause one product to appear as multiple rows. This is a data quality issue in the ecommerce implementation, not in Looker Studio. If you see this, note it and flag it to the dev team.
Page 3: Purchase Funnel
The funnel view shows where users drop off between browsing and buying.
Looker Studio does not have a native funnel visualization, but you can approximate one with a bar chart.
Create a bar chart with a static dimension and calculated metrics. The simplest approach is a table showing the four funnel stages:
| Stage | Metric |
|---|---|
| Item Views | Item Views |
| Add to Carts | Add to Carts |
| Checkouts | Checkouts |
| Purchases | Purchases |
You can build this as a blended data source using a Google Sheets table with the stage labels on the left, and a separate data source on the right — but for most dashboards, a simple table with the four metrics as columns and a date filter is sufficient.
The step-down percentages tell you where the biggest drop is. If 1000 users view items, 200 add to cart, 150 reach checkout, and 80 purchase, the biggest drop is add-to-cart (80% drop from view to cart). That is where to focus product page and cart experience improvements.
Add conversion rate calculated fields for each stage transition:
- Add to Cart Rate:
Add to Carts / NULLIF(Item Views, 0) - Checkout Rate:
Checkouts / NULLIF(Add to Carts, 0) - Purchase Rate:
Purchases / NULLIF(Checkouts, 0)
Page 4: Revenue by Channel and Source
This page answers the attribution question: where is revenue coming from?
Add a table with Session Default Channel Group and Purchase Revenue, sorted by revenue descending. Add Session Source / Medium as a second table below it for more granular source attribution.
Add a time series chart showing Purchase Revenue trend by channel group using a line chart with one line per channel. This shows whether the channel mix is shifting over time — for example, if paid search revenue is rising while organic is declining.
Add a date comparison control so the client can toggle between this month and last month at the page level.
Calculated Fields Specific to Ecommerce
Average Order Value
Purchase Revenue / NULLIF(Purchases, 0)
Revenue per Session
Purchase Revenue / NULLIF(Sessions, 0)
Checkout Abandonment Rate
1 - (Purchases / NULLIF(Checkouts, 0))
Add to Cart Rate
Add to Carts / NULLIF(Sessions, 0)
Return on Ad Spend (when blending with Google Ads)
Purchase Revenue / NULLIF(Cost, 0)
What to Keep Off the Dashboard
Transaction-level detail — individual order IDs and values — belongs in a CRM or backend report, not a Looker Studio dashboard. GA4 does not expose full transaction history in a way that makes a per-order table useful, and putting order IDs in a shared report creates unnecessary data exposure.
Similarly, keep refund and return data off the default views unless the client specifically needs it. GA4 tracks refunds if you implement the refund measurement, but mixing gross and net revenue in the same dashboard creates confusion without clear labeling.
Build the ecommerce dashboard around trends and aggregates — revenue by day, revenue by channel, product performance by volume. For individual transaction investigation, point the client to the GA4 Ecommerce purchases report or a backend order management system.
Related Posts
Data Blending in Looker Studio: Combine GA4 and Google Ads in One Chart
Connecting Data Sources in Looker Studio: GA4, Google Ads, and Beyond
Building Your First Looker Studio Dashboard: A Step-by-Step Guide
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