The Monetization overview report is a pre-made overview report that summarizes your revenue data. The report can help you figure out which products you're selling, if promotions and coupons are successfully bringing in new users, and if you're getting revenue from ads displayed on your mobile app.
The Monetization overview report appears on the left only in the Life cycle collection. You won't see the report in the Business objectives collection by default; however, an editor or administrator can add the report to your left navigation.
Learn how your ecommerce business is performing in the monetization reports in Google Analytics 4
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View the report
- Open the Google Analytics mobile app.
- From the top left, tap
.
- In the Reports section, tap Life cycle.
- Open the Monetization tab and select Monetization overview.
.Note: If you don't see the report and you are an Editor or Administrator, you can add the report using a desktop device.
Pre-made summary cards
The Monetization overview report includes the following summary cards by default. Administrators and editors can change the cards so you may see different ones from these.
Total revenue
Total revenue shows the total amount of revenue generated from ecommerce purchases, in-app purchases, subscriptions, and advertisements, minus any refunds given.
The Total revenue tab shows the total revenue made during the time period. The chart plots the total revenue per day. For example, if your total revenue on July 2 was $153.98 and on July 3 was $739.28, the tab would show $893.26.
Purchase revenue
Purchase revenue shows the total amount of revenue generated from ecommerce and in-app purchases.
The Purchase revenue tab shows the purchase revenue made during the time period. The chart plots the purchase revenue per day. For example, if your purchase revenue on July 2 was $39.15 and on July 3 was $91.35, the tab would show $130.50.
Total ad revenue
Total ad revenue shows the sum of the advertising revenue from your users in your mobile app. Total ad revenue comes from Google AdMob, Google Ad Manager, or the ad_impression event when the data comes from a third-party integration.
The Total ad revenue tab shows the total ad revenue made during the time period. The chart plots the total ad revenue per day. For example, if your total ad revenue on July 2 was $7.25 and on July 3 was $1.45, the tab would show $8.70.
Total purchasers
Total purchasers shows the number of unique users who made at least one purchase. Google Analytics uses the number of times the purchase event was collected to calculate the Total purchasers metric.
The Total purchasers tab shows the number of purchasers over the entire time period, while each point in the chart shows the number of purchasers for that day.
First time purchasers
First time purchasers shows the number of unique users who made their first purchase. Google Analytics uses the number of times the purchase event was collected for the first time from a user to calculate the First time purchasers metric.
The First time purchasers tab shows the number of first-time purchasers over the entire time period, while each point in the chart shows the number of first-time purchasers for that day.
Average purchase revenue per active user
Average purchase revenue per active user shows the average amount of revenue generated from purchases per user, where purchase revenue is the total amount of revenue generated from ecommerce and in-app purchases.
How to interpret the chart
The average purchase revenue per active user in the tab may be greater than the individual purchase revenue per user in the chart.
This is because the purchase revenue per active user in the tab shows the sum of purchase revenue per user divided by the number of users in the entire time period. Each point in the chart shows the purchase revenue per active user divided by the number of users for that day.
Example
Two users visited your website in July.
- On July 2, user #1 purchased $57.98 from your store.
- On July 3, user #2 purchased $178.68 from your store.
- On July 4, user #1 purchase $192.98 and user #2 purchased $58.99.
In this example, the average purchase revenue per user in the tab would be XXXXX because the revenue from user #1 was $250.96 and the revenue from user #2 was $237.67. The average of those two amounts is $244.31.
The average purchase revenue per user in the chart would look like the following:
- July 2: $57.98
- July 3: $178.68
- July 4: $125.98
In this example, the average engagement time in the tab would be greater than the average engagement time each day.
Items purchased by Item name
Items purchased by Item name shows the top most purchased items and the number of times the items were purchased.
Google Analytics uses the item_name parameter from the purchase event to update the Item name dimension and the items array from the purchase event to calculate the Items purchased metric.
Items purchased by Item list name
Items purchased by Item list name shows the item lists associated with the most purchased items and the number of times items were purchased from the lists.
Google Analytics uses the item_list_name parameter from the purchase event to update the Item list name dimension and the items array from the purchase event to calculate the Items purchased metric.
Items viewed in promotion by Item promotion name
Items viewed in promotion by Item promotion name shows the item promotions associated with the most viewed items and the number of times items were viewed after seeing a promotion.
Google Analytics uses the item-level promotion_name parameter from the view_promotion or select_promotion event to update the Item promotion name dimension and the items array from the purchase event to calculate the Items viewed in promotion metric.
Purchase revenue by Order coupon
Purchase revenue by Order coupon shows the most frequently used coupons for making purchases and the amount of revenue generated from each coupon.
Product revenue by Product ID
Product revenue by Product ID shows the amount of revenue from each in-app purchase, identified by its product ID. The table is sorted by the in-app purchases with the most amount of revenue generated.