GA4 reports in Customer Journey Analytics

Realtime

GA4’s Realtime report shows activity from the last 30 minutes — active users, the events firing, where users are, what’s driving traffic, and which pages they’re on.

Customer Journey Analytics has no separate real-time report area. Instead, build a panel in Analysis Workspace and enable the Real-time refresh toggle (part of the Ultimate package) so its visualizations update every minute:

1. Build a Freeform panel (the toggle also works on Blank, Attribution, and Next or previous item panels) with the dimensions and metrics you want to monitor. To mirror GA4’s real-time cards, use Page, Event type, Referring Domain, or Countries as the dimension, with Sessions as the metric.
2. Enable the Real-time refresh toggle and choose a period from Last 15 minutes to Last 24 hours. Data is limited to a rolling 24-hour window, and the panel refreshes every minute for up to 30 minutes.

Real-time reporting favors event- and session-level data and can’t use stitching, so prefer Sessions over People. See Use real-time reporting for the full procedure and Real-time reporting overview for entitlement and latency details.

User acquisition (first-touch)

GA4’s User acquisition report attributes each user to the channel, source, and medium that brought them to your site for the first time, using first-touch attribution.

In Analysis Workspace, apply a First Touch attribution model to the Marketing Channel dimension. Marketing Channels must be configured before use. See Create a marketing channel derived field.

1. Drag the Marketing Channel dimension into a Freeform table.
2. Right-click a metric column header and select Use non-default attribution model.
3. Select First Touch with a lookback window appropriate for your analysis.

Alternatively, use the Attribution panel for a side-by-side comparison of first-touch and last-touch channel performance.

Traffic acquisition (session-based)

GA4’s Traffic acquisition report attributes each session to the channel, source, and medium that initiated it, using session-based attribution. You can break it down by default channel group, source / medium, referrer, or campaign.

In Analysis Workspace, the Marketing Channel dimension with the default Last Touch attribution model provides session-based channel reporting:

1. Drag the Marketing Channel dimension into a Freeform table.
2. Drag desired metrics alongside the default Events metric.

GA4’s breakdowns map to these Customer Journey Analytics dimensions:

• Channel: Marketing Channel. Customer Journey Analytics has no built-in channel groupings — define them as a derived field using the Marketing channels function template, or carry over rules from Adobe Analytics when using the Analytics source connector (see Use marketing channel dimensions).
• Source / medium and referrals: Referring Domain and Referrer Type.
• Campaign: GA4’s utm_* parameters are not collected automatically — each must be mapped to an XDM field during implementation before it appears as a dimension. If campaign values arrive as a tracking code, use the Tracking Code dimension.

Attribution and conversion paths

GA4’s Attribution reports (under Advertising) show how different channels contribute to conversions and allow model comparison and conversion path analysis.

In Analysis Workspace, use the Attribution panel:

1. Select the Panels icon and drag an Attribution panel onto the canvas.
2. Drag the Marketing Channel dimension to the Add Dimension box.
3. Drag your conversion metric (for example, a purchase event) to the Add Metric box.
4. Select Build.

The Attribution panel produces a model comparison table and a Channel Flow visualization showing the top paths visitors took prior to converting. Select Add Model to compare multiple attribution models simultaneously.

Pages and screens

GA4’s Pages and screens report shows performance metrics for individual pages and app screens.

In Analysis Workspace, drag the Page dimension into a Freeform table and add your desired metrics. Common metrics include Sessions, People, Bounce Rate, and Time Spent per Session.

To group pages by URL path structure (for example, /blog/ or /products/), use the Site Section dimension if your implementation defines it, or create a derived field that parses the page URL with the URL Parse function. If you maintain an explicit page-to-section mapping, a lookup dataset can supply the grouping instead.

Landing pages

GA4’s Landing page report shows which pages users arrive on when they begin a session.

In Analysis Workspace, drag the Entry Page dimension into a Freeform table. Sessions is the most relevant metric for this dimension.

Events

GA4’s Events report shows how many times each event fired, with event-level metrics.

In GA4, events have a name and optional parameters (for example, event video_play with parameter video_title). In Customer Journey Analytics, the standard dimension for the event name is Event type (sourced from xdm.eventType). Event parameters map to other XDM fields, whose names depend on your implementation.

Drag the Event type dimension into a Freeform table to list all event types, alongside the Events metric.

Key events (conversions)

GA4’s Key events report (formerly Conversions) lists each key event by name with its count — events flagged as business-critical in the GA4 property configuration.

Customer Journey Analytics has no “key event” flag; every interaction is an event, so there is no preset list of conversions to open.

To recreate GA4’s list of conversions by name, use segments as rows. A Freeform table can’t place a metric in the row position, but it can place a segment there:

1. For each conversion, create a segment that isolates its events — for example, an event-scoped segment where xdm.eventType equals commerce.purchases. Name each segment after the conversion it represents (for example, Purchases).
2. Drag each conversion segment into the row area of a Freeform table, one per row.
3. Add the Events metric as the column. Each row shows that conversion’s count, mirroring GA4’s key-events list. Use People instead to count unique converters.

To add a conversion rate, create a calculated metric (select the + icon near the metrics list) defined as a conversion metric divided by Sessions or People.

Each conversion you isolate here can also be defined as a reusable metric in your data view. See the Key events → Custom event metrics entry under Common metrics for how to set that up.

Ecommerce purchases

GA4’s Ecommerce purchases report shows product-level purchase data including items, revenue, and quantity.

In Customer Journey Analytics, ecommerce reporting uses the Product dimension alongside purchase metrics. This report requires that your implementation sends XDM commerce data (such as xdm.commerce.purchases, xdm.commerce.order, and xdm.productListItems).

1. Drag the Product dimension into a Freeform table.
2. Drag ecommerce metrics such as Orders, Revenue, and Units alongside the default Events metric.

Purchase journey (funnel)

GA4’s Purchase journey report shows how users move through your shopping funnel — for example, from add to cart to begin checkout to purchase — and where they drop off.

In Analysis Workspace, use the Fallout visualization:

1. Select the Visualizations icon and drag a Fallout visualization onto the canvas.
2. Locate the Page dimension and expand it to reveal individual page values.
3. Drag the first funnel step (for example, a product page) into the first Add Touchpoint slot.
4. Continue adding touchpoints for each step.

The Fallout visualization accepts any dimension, metric, or segment as a touchpoint, not just pages, so it matches GA4’s event-based funnels and extends to sequences that mix events, pages, and segments.

Promotions

GA4’s Promotions report shows how internal promotions (banners, featured placements) drive product interactions.

In Customer Journey Analytics, promotion data requires that you capture promotion impressions and clicks in XDM schema fields. Once collected, create a Freeform table that includes the promotion name dimension with impression and click metrics. Work with your Customer Journey Analytics administrator to confirm what promotion data is available in your data view.

Publisher ads

GA4’s Publisher ads report shows ad revenue from Google Ad Manager or AdMob for publisher-monetized properties.

Customer Journey Analytics has no native publisher ad-revenue integration. To report this data, ingest the revenue figures from your ad-monetization platform (such as Google Ad Manager or AdMob) into Adobe Experience Platform as a dataset, using a source connector or direct data ingestion. Once ingested, the data is available for reporting in Customer Journey Analytics.

Retention overview

GA4’s Retention overview report combines several retention views — new versus returning users, and a cohort chart showing how many users return over time.

New vs. returning users: use the First Session and Return Sessions segments as rows in a Freeform table:

1. Drag the First Session segment from the Components panel into the table’s row area, then drag the Return Sessions segment below it.
2. Add your desired metrics alongside the default Events metric.
3. To trend over time, drag a Line visualization above the table, then ctrl+click (Windows) or cmd+click (Mac) each row to highlight both segments.

Retention over time: use the Cohort Table visualization:

1. Select the Visualizations icon and drag a Cohort Table onto the canvas.
2. Drag the People metric into both the Inclusion and Return Criteria fields, then select Build.

The Cohort Table groups people by their initial period and tracks return behavior over subsequent periods; the inclusion, return, and granularity criteria are all configurable.

Demographic details

GA4’s Demographic details report covers user characteristics — age, gender, and interests (powered by Google Signals, which requires users to be signed into a Google account with personalization enabled) — along with location (country, region, city) and language.

Location maps directly to Customer Journey Analytics dimensions: use Countries, Regions, or Cities in a Freeform table, or the Map visualization for a geographic overview (drag the People metric into the Add Metric slot and select Build).

Age, gender, and interests require first-party data. If your organization collects demographic data through CRM, registration forms, or consent-based surveys, ingest it as a Profile dataset and join it to event data. This approach produces more reliable data than GA4’s inferred Google Signals model because it uses consented, first-party attributes.

Tech details

GA4’s Tech report shows Browser, Operating System, Screen resolution, and Device category.

In Analysis Workspace, the following dimensions map to GA4’s Tech dimensions, each sourced from a standard XDM field:

table 0-row-3 1-row-3 2-row-3 3-row-3 4-row-3 5-row-3
GA4 Tech dimension	Analysis Workspace dimension	XDM field
Browser	Browser	xdm.environment.browserDetails.name
Operating system	Operating System	xdm.environment.operatingSystem
Screen resolution	Monitor Resolution	xdm.device.screenWidth, xdm.device.screenHeight
Device category (Mobile, Desktop, Tablet)	Mobile Device Type	xdm.device.type
Device model	Mobile Device	xdm.device.model

Drag any of these dimensions from the Components panel into a Freeform table.

note
NOTE
Because modern browsers have reduced the detail in the User-Agent string, complete and accurate values depend on collecting User-Agent Client Hints in your Web SDK configuration.

Free-form exploration

GA4’s Free-form exploration is a blank-canvas table with configurable rows, columns, and optional chart overlays.

Analysis Workspace’s Freeform table is the direct equivalent and the foundation of most Workspace projects. Drag any dimension into the rows, any metric into the columns, and any segment into the segment drop zone above the table.

See Getting started in Analysis Workspace for terminology mapping between GA4 Explore and Workspace.

Funnel exploration

GA4’s Funnel exploration defines a sequence of steps and measures completion and drop-off at each step.

In Analysis Workspace, use the Fallout visualization:

1. Select the Visualizations icon and drag a Fallout visualization onto the canvas.
2. Drag the dimension, metric, or segment that represents your first step into the first Add Touchpoint slot.
3. Continue adding a touchpoint for each subsequent step in the sequence.

Because any dimension, metric, or segment can serve as a touchpoint, Fallout matches GA4’s event-based funnels and extends to cross-channel sequences that mix events, pages, and segments.

Path exploration

GA4’s Path exploration (Universal Analytics called this Users Flow) visualizes the sequences of pages or events that users navigate through.

In Analysis Workspace, use the Flow visualization:

1. Select the Visualizations icon and drag a Flow visualization onto the canvas.
2. Drag a value from the dimension you want to path on (for example, a Page or Event type value) into the center of the flow.
3. The visualization shows what users did before and after that point.

The Flow visualization is interactive — select any node to expand paths further in either direction. Any dimension can be used, so you can path on pages, events, marketing channels, or custom links.

Segment overlap

GA4’s Segment overlap exploration shows how multiple user segments intersect, visualized as a Venn diagram.

In Analysis Workspace, use the Venn visualization:

1. Select the Visualizations icon and drag a Venn visualization onto the canvas.
2. Drag up to three segments from the Components panel into the visualization.

The Venn diagram shows intersection sizes, and the Freeform table below it shows the underlying data.

Cohort exploration

GA4’s Cohort exploration groups users by a shared characteristic (typically acquisition date) and tracks their behavior over time.

In Analysis Workspace, use the Cohort Table visualization:

1. Select the Visualizations icon and drag a Cohort Table onto the canvas.
2. Drag the People metric into both the Inclusion and Return Criteria fields.
3. Select Build.

The Cohort Table groups people by their initial period and tracks return behavior over subsequent periods. By default it cohorts on acquisition date, but the inclusion, return, and granularity criteria are all configurable.

User explorer

GA4’s User explorer shows individual users, their session history, and a timeline of events.

Customer Journey Analytics supports person-level analysis in two ways:

• With stitching enabled: Create a segment scoping to a specific person ID value and apply it to any Workspace project. The Person container isolates that individual’s stitched activity across sessions and channels.
• Raw event data: Use dataset previews in the Adobe Experience Platform UI to inspect raw XDM event records. This view is useful for implementation validation and debugging individual events.

User lifetime

GA4’s User lifetime exploration measures each user’s accumulated value and engagement across their entire relationship with your business, rather than within a fixed date range. It combines historical lifetime metrics with Google’s machine-learning predictions for purchase probability, churn probability, and predicted revenue.

These map to Customer Journey Analytics in two parts:

Historical lifetime value is achievable natively. Because Customer Journey Analytics reports across your full data retention window, you can set a long date range and aggregate each person’s accumulated revenue and engagement across that lookback. With stitching or a persistent person ID, the Person container ties that activity to one individual, and calculated metrics express per-person value. The result is not an unbounded lifetime, but a long, configurable lookback that approximates one.

Predictive lifetime value is not built in. Customer Journey Analytics has no in-product purchase-probability, churn, or predicted-revenue model. To use predictive scores, calculate them externally (for example, in a CRM or data-science workflow) and bring them into Customer Journey Analytics as a Profile dataset, then surface them as dimensions or metrics. Adobe recommends working with an implementation consultant to design this approach.

Active users → People

GA4’s Active users counts users who had at least one engaged session in the date range.

In Customer Journey Analytics, the closest equivalent is People, a count of unique person IDs in the date range. People includes all identified persons regardless of engagement level, so it is typically higher than GA4’s Active users for sites with significant passive traffic.

For a closer behavioral comparison, apply an engaged-sessions segment to scope the People metric to users who meet your engagement criteria.

Engaged sessions → Calculated metric

GA4’s Engaged sessions counts sessions that lasted 10 or more seconds, had 2 or more page views, or included at least one key event.

Customer Journey Analytics has no built-in engaged-sessions metric — you define it as a segment that captures your engagement criteria, then use it alongside the Sessions metric. See Engaged sessions for the recommended approach and how to derive an engagement rate from it.

Engagement rate → Calculated metric

GA4’s Engagement rate is the percentage of sessions that were engaged: engaged sessions divided by total sessions.

In Customer Journey Analytics, build it as a calculated metric from your engaged-sessions definition. See Engaged sessions for step-by-step instructions.

Average engagement time → Time Spent per Session

GA4’s Average engagement time measures the average time the browser or app was in the foreground during engaged sessions.

In Customer Journey Analytics, use Session Duration (seconds), which measures the elapsed time from the first event to the last event in a session. This component includes periods when the user might not have been actively engaging, so values can differ from GA4’s measurement. It is the closest built-in equivalent.

Event count → Events

GA4’s Event count is the total number of times any event was recorded.

In Customer Journey Analytics, the equivalent metric is Events — the total number of event records in the dataset for the selected date range and applied segments.

Sessions → Sessions

GA4’s Sessions and Customer Journey Analytics’s Sessions both measure the number of sessions in a date range. Counts can differ due to different session definition rules. See Why GA4 and Customer Journey Analytics data differs for details.

New users → First Session segment applied to People

GA4’s New users counts users who had their first-ever session in the selected date range.

In Analysis Workspace:

1. Locate the First Session segment in the Components panel.
2. Drag it into the segment drop zone above your Freeform table.
3. Use the People metric to count unique new persons.

Bounce rate → Bounce Rate (with caveats)

GA4’s Bounce rate is the percentage of sessions that were not engaged (under 10 seconds, no key event, fewer than 2 page views). It is the inverse of Engagement Rate.

Customer Journey Analytics’s Bounce Rate metric uses a different definition by default and is configurable per data view. These differences produce materially different numbers that measure different behaviors.

To approximate GA4’s bounce rate in Customer Journey Analytics, build an Engagement Rate metric and invert it with a second calculated metric defined as 1 - Engagement Rate. See Engaged sessions for the step-by-step build.

See Why GA4 and Customer Journey Analytics data differs for a detailed explanation of the definitional difference.

Key events → Custom event metrics

GA4’s Key events (formerly called Conversions) are events designated as important business outcomes in GA4 property configuration.

In Customer Journey Analytics, a conversion is a custom event metric configured in the data view. Any XDM event can be exposed as a metric, and a metric can be set to increment conditionally on an XDM field value — for example, a Purchases metric that increments when xdm.eventType equals commerce.purchases. Locate the relevant metric by its label in the Components panel of Analysis Workspace; the name reflects how your administrator configured it.

To reproduce GA4’s Key events report (a list of every conversion with its count), see the Key events (conversions) entry under Engagement on this page.