Google Analytics 4 glossary

Number of users active during a given period.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Purchase event count.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The ratio of engaged sessions to total sessions.

Calculation: engagedSessions / sessions.

Sessions that meet GA4's engagement criteria.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Total of logged events.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of page and screen views.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The rate of non-engaged sessions.

Calculation: 1 - engagementRate.

Number of ecommerce transactions.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of events marked as key events.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Average time per session.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of sessions started.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The rate of sessions containing at least one key event.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Ad impressions from linked ad accounts.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Cost from linked ad accounts.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Cost per ad click.

Calculation: advertiserAdCost / advertiserAdClicks.

Ad clicks from linked ad accounts.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Return on ad spend.

Calculation: totalRevenue / advertiserAdCost.

Number of products purchased.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Revenue from purchase events.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of products added to cart.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Total purchase, subscription, and ad revenue minus refunds.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Unique users who logged at least one event during a given period.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Total site/app ad revenue.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of product views.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of first-time users.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Product revenue before refunds/discounts.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Number of products that reached checkout.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The number of engaged sessions divided by total sessions; can be thought of as roughly the inverse of UA's bounce rate.

A high engagement rate shows that visitors are spending time with content or completing conversion activity.

A session that lasts at least 10 seconds, includes a conversion event, or has at least two page views.

GA4 bases engagement rate on this instead of UA's bounce rate.

In GA4, every user interaction is recorded as an event — page views, clicks, form submissions, and scrolling are among the most common.

Automatically collected events (page_view, first_visit, session_start) require no setup. Additional events are defined for specific business goals and can be marked as conversions.

User-based conversion rate for a specific key event.

Calculation: property-specific.

Session-based conversion rate for a specific key event.

Calculation: property-specific.

Number of returning users.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Refunded amount.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Shipping revenue/amount.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

GA4's custom analysis tool; it offers views not found in standard reports, like free-form tables, funnel analysis, path analysis, and segment overlap.

Exploration reports are saved at the user level, not the account level. Sharing requires exporting the report or granting edit access.

Ad cost per key event.

Calculation: advertiserAdCost / keyEvents.

Average number of events per user.

Calculation: eventCount / totalUsers.

Average page/screen views per user.

Calculation: screenPageViews / totalUsers.

Average sessions per user.

Calculation: sessions / totalUsers.

Average purchase revenue per user.

Calculation: purchaseRevenue / totalUsers.

The user's active engagement time with the site/app.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The rate of users triggering at least one key event.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The measurement unit created in GA4 for a website or app; all reports are fed by the data streams connected to this property.

Multiple properties can be created under the same account; however, connecting multiple data streams to a single property is the preferred way to combine a brand's web and app data.

Average revenue per purchase.

Calculation: purchaseRevenue / ecommercePurchases.

The full set of interactions a user has on a site within a given period; 30 minutes of inactivity automatically closes a session.

Unlike UA, GA4 counts sessions on an event basis.

Average number of events per session.

Calculation: eventCount / sessions.

Average page/screen views per session.

Calculation: screenPageViews / sessions.

A unique code starting with "G-" that identifies a GA4 data stream; adding it to a site starts measurement.

Found under Admin → Data Streams → the relevant stream → Measurement ID. This value can be public and does not need to be kept secret.

Average of a registered event-scoped custom metric.

Calculation: property-specific.

Occurrence count of a registered event-scoped custom metric.

Calculation: property-specific.

Total of a registered event-scoped custom metric.

Calculation: property-specific.

Number of transactions per purchasing user.

Calculation: transactions / purchasers.

Number of unique users who made a purchase.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

Tags like utm_source, utm_medium, and utm_campaign added to a URL that help GA4 classify traffic source correctly.

Adding a consistent UTM tag to every link for channels like email, social media, and newsletters makes cross-channel comparison reliable.

Revenue generated from products.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

The rule set GA4 uses to automatically classify traffic into groups like Organic Search, Paid Search, Direct, Referral, and Email.

Channel grouping forms the basis of Acquisition reports. Custom channel groups can be created, but should be checked for conflicts with the default grouping.

Tax amount.

Should be read together with the goal, scope, and data volume when comparing across periods and campaigns.

A source sending data to a GA4 property; it can be a website, an iOS app, or an Android app.

A data stream is created for a website, and the measurement ID for that stream is added to the site. Multiple websites or apps can connect to the same property as separate streams.