Google Analytics (GA4) key terms

A user interaction or action tracked in GA4, such as a page view, click, or purchase. Events are the core unit of data collection, replacing the session-based model of earlier versions.

Additional information attached to an event that provides context, like page_location or button_id. Parameters can be automatically collected, enhanced measurement, or custom.

A attribute describing a user, such as language preference or membership tier. These are set once and apply to all future events from that user, enabling segmentation.

An event that you mark as important for your business goals, such as a purchase or form submission. Conversions are used in reports and can be counted once per session or event.

The term for conversion events in GA4. Marking an event as a key event signals that it is a priority action, and it will appear in conversion reports.

A period of user activity on your site or app. In GA4, a session starts when a user first interacts and ends after 30 minutes of inactivity or at midnight.

A session that lasts longer than 10 seconds, has at least one conversion event, or has at least two page views. This metric helps measure meaningful engagement.

The percentage of sessions that were engaged. It is calculated as engaged sessions divided by total sessions, providing insight into content relevance.

A session that is not engaged, meaning it lasts less than 10 seconds, has no conversions, and has only one page view. This replaces the old bounce rate concept.

A person who interacts with your website or app. GA4 distinguishes between total users, active users, and new users, each with specific definitions based on activity.

A user who has had at least one engaged session or conversion event. This is the primary user metric in GA4 reports, replacing the concept of users in Universal Analytics.

A user who has not interacted with your site or app before. GA4 identifies new users by the first_visit or first_open event, depending on the platform.

A unique identifier that you assign to a logged-in user. It enables cross-device and cross-platform analysis, providing a more accurate count of users.

The method GA4 uses to identify users, either by User ID or by device ID. The reporting identity setting determines how sessions are grouped.

A setting that determines how GA4 combines data from different sessions and devices to report on users. Options include blended, observed, and device-based.

The process of assigning credit for a conversion to the marketing touchpoints that preceded it. GA4 offers data-driven attribution as the default model.

A rule or set of rules that determines how credit for conversions is assigned to touchpoints. GA4 includes data-driven, last-click, first-click, and linear models.

The origin of a session, defined by dimensions like source, medium, and campaign. These dimensions help you understand how users arrive at your site.

Tags added to a URL to track the source, medium, campaign, term, and content of a marketing effort. They help GA4 categorize traffic accurately.

A specific marketing initiative identified by UTM parameters or auto-tagging. Campaign dimensions in GA4 show performance across different marketing efforts.

A group of users who share common characteristics, such as behavior or demographics. Audiences can be used for remarketing and analysis in GA4.

A subset of data based on specific criteria, used to isolate and analyze particular user groups or behaviors. Segments are applied in explorations and reports.

A customizable analysis tool in GA4 that allows you to build tables, funnels, and path analyses. Explorations provide deeper insights than standard reports.

A technique to visualize the steps users take toward a conversion and identify where they drop off. In GA4, funnels can be built in Explorations.

A tool that shows the sequence of events or pages users navigate through. It helps understand common user journeys and bottlenecks.

A user-defined dimension that allows you to collect and analyze data specific to your business, such as membership level or app version.

A user-defined metric that quantifies a specific aspect of user behavior, such as revenue per user or time spent. It is created from event parameters.

A source of data flowing into GA4 from a website, Android app, or iOS app. Each stream has a unique measurement ID and is configured separately.

A unique identifier for a data stream, used in the tracking code to send data to the correct GA4 property. It typically starts with 'G-'.

A container for data collected from your websites and apps. In GA4, a property can have multiple data streams and is the top-level reporting unit.

The highest level of organization in GA4, containing one or more properties. Accounts control user access and permissions across properties.

A feature that automatically tracks common interactions like scrolls, outbound clicks, and file downloads. It can be toggled on or off per data stream.

A real-time report that shows events as they are collected, useful for testing and troubleshooting. It displays event parameters and user properties for validation.

A report that shows user activity in the last 30 minutes. It includes metrics like active users, event count, and top pages, helping monitor immediate impact.

A report that shows how users arrive at your site or app, including traffic sources and campaigns. It helps evaluate marketing effectiveness.

A report that provides data on user interaction, such as events, conversions, and page views. It helps understand what users do after arriving.

A report that shows revenue-related data, including ecommerce purchases, in-app purchases, and ad revenue. It helps track financial performance.

A report that shows how often users return to your site or app. It includes metrics like new users, returning users, and retention rate over time.

The tracking of online sales and shopping behavior, including events like view_item, add_to_cart, and purchase. GA4 has dedicated ecommerce reports.

A feature that allows you to export raw GA4 event data to Google BigQuery for advanced analysis. It provides access to unsampled, granular data.