GA4 and Looker Studio: Connection Setup and 5 Dashboards Worth Building.

GA4's built-in reports are adequate for quick checks — total sessions, top channels, recent conversion counts. They fall short the moment you need to combine data sources, apply custom targets, or share a view with someone who does not have GA4 property access. You cannot put GA4 traffic data next to Google Ads spend data in the same chart inside GA4. You cannot compare performance against a budget you have stored in a spreadsheet. You cannot send a client a link to a live, auto-refreshing report without giving them GA4 access first.

Looker Studio (formerly Google Data Studio, rebranded in 2022) solves all three problems. It is free, built by Google, and connects directly to GA4 through a native connector. Reports are shareable as interactive web pages — no login required for the viewer. This guide covers the connection setup, how the GA4 data model works inside Looker Studio, how to blend GA4 with other sources, and the five dashboards most worth building.

Connecting GA4 to Looker Studio

Create a new report

Go to lookerstudio.google.com and sign in with a Google account that has at least Viewer access to the GA4 property you want to connect. Click the blue "Create" button in the top left and select "Report." A blank canvas opens alongside a data source panel on the right.

In the data source panel, scroll down to find "Google Analytics" and click it. You will see two Google Analytics connectors listed — make sure to select the one labelled "Google Analytics" without any "Universal Analytics" qualifier. The Universal Analytics connector is a legacy option for properties that have not migrated and will return no data for GA4 properties. Select your GA4 account from the dropdown, then select the specific property. You do not need to select a data stream — the connector pulls from the property level, which aggregates all streams. Click "Add" and confirm to add it to the report.

Understanding the GA4 connector's data model

Looker Studio exposes your GA4 property as a single flat table. Every metric and dimension available in GA4's reporting API appears as a field in that table. When you insert a chart or table onto the canvas, you pick which fields to use — there is no concept of a pre-structured report layout that constrains your choices the way GA4's standard reports do.

A few things are worth knowing before you build your first chart. The date range dimension in the connector is always the field named "Date." Every chart needs a date range context — either a fixed date range set on the chart itself, or a Date Range Control component on the page that lets report viewers pick their own window. Without a date context, charts default to the last 28 days, which is usually fine but worth making explicit.

Custom dimensions you have registered in GA4 Admin appear in the connector automatically. They show up with a name that matches what you set in the GA4 custom dimensions interface. If a custom dimension is not showing up as an available field in Looker Studio, the most common cause is that it has not been registered yet — registering a custom event parameter as a custom dimension in GA4 Admin (under Admin → Data display → Custom definitions) is a prerequisite for it to appear anywhere outside of raw Explorations queries.

One category of GA4 data is notably absent from the connector: cohort data, user-level attribution paths, and predictive metrics. These live in GA4's Explorations and BigQuery export respectively. If your reporting needs involve user-level joins or predictive audience segments, you will need BigQuery as an intermediate layer rather than the direct Looker Studio connector.

Blending GA4 with other sources

Looker Studio's data blending feature lets you combine the GA4 connector with other data sources in a single chart. The blend uses a join key — a shared field that exists in both sources — to combine rows. For most marketing reporting, the join key is either Date (for daily-level blends) or campaign dimensions like Campaign or Source/Medium.

The most common blend for paid marketing teams is GA4 plus Google Ads. To set this up, add a Google Ads data source to your report in addition to the GA4 source. Then create a blended data source from the Resource menu: select both sources, choose "Campaign" as the join key, and map the fields you want from each. The resulting blended source lets you put GA4's key event counts in the same chart as Google Ads' cost and clicks, which is the foundation for a Cost Per Key Event view that is otherwise impossible inside either platform alone.

Blending GA4 with Google Sheets is useful for performance-against-target reporting. If your team maintains a spreadsheet of monthly session targets or revenue budgets, you can add that sheet as a Looker Studio data source, blend it with GA4 on the Date or Month field, and plot actuals versus targets in the same chart. The sheet becomes the source of truth for targets and the GA4 connector supplies the actuals — updating the sheet automatically updates the report.

Blending with BigQuery is the right approach when you need user-level joins, more than 14 months of history, or query logic that the Looker Studio connector cannot express. GA4's BigQuery daily export writes raw event data to a BigQuery dataset, which you can query with SQL and surface in Looker Studio via the BigQuery connector. This path has higher setup complexity but removes the sampling and field-availability constraints of the direct connector.

The 5 Most Useful GA4 Dashboards to Build in Looker Studio

1. Acquisition overview

An acquisition overview dashboard answers the question most stakeholders ask first: where is the traffic coming from and is it growing? The core of this dashboard is a bar or line chart with Sessions broken down by Default Channel Group over time. Add Engaged sessions and Key events alongside Sessions to show not just volume but quality — a channel that drives high sessions with low engagement and zero key events tells a different story than one with half the sessions and three times the conversions.

Add four Scorecard components at the top of the page showing Sessions, Engaged sessions, Key events, and Key event rate for the selected period, each with a comparison to the prior period. Scorecards give stakeholders the headline numbers before they read any chart. Include a Date Range Control component so viewers can adjust the window. Keep it set to last 28 days by default — short enough to be recent, long enough to smooth day-of-week variation.

A secondary table below the chart with one row per channel and columns for Sessions, Engaged session rate, Key events, and Key event rate lets viewers drill into which channels are performing on quality metrics, not just volume. Sort by Sessions descending so the dominant channels appear first.

2. Landing page performance

The landing page report in GA4 is one of the most looked-at reports in any property, but GA4's native version does not show conversion data by default and does not let you filter out the homepage without building an exploration. Looker Studio makes both of those easy.

Build a table with Landing page as the dimension and columns for Sessions, Engaged session rate, Key events, and a calculated field for Key event rate (Key events divided by Sessions, formatted as a percentage). Sort by Sessions descending. Add a filter control that lets the viewer exclude specific paths — filtering out the homepage (/) is the most common use, since it typically dominates session counts and obscures the performance of destination pages.

Add a fixed filter to the data source on the chart (not the report-level filter control) to exclude sessions where Landing page contains "?" — this removes URL query string variants from appearing as separate rows, which pollutes the landing page breakdown when UTM parameters are appended to destination URLs. This is one of those small data hygiene steps that makes the report genuinely usable rather than requiring manual cleanup every time someone reads it.

3. Conversion funnel

GA4's native funnel exploration is powerful but locked inside the Explore section, which means non-analyst stakeholders rarely see it. Building a funnel view in Looker Studio creates a persistent, shareable version that updates automatically.

The GA4 Looker Studio connector does not include a native Funnel chart type, so the practical approach is a step-by-step table. Create one row per funnel stage by using separate Scorecard components or a summary table: each stage is a filter on a specific event or page. For a checkout funnel, the stages might be Users who triggered view_item, then add_to_cart, then begin_checkout, then purchase. Each metric is a filtered version of the "Total users" or "Event count" metric. Place them side by side with percentage completion between each step.

This approach requires creating a separate chart for each step or using Looker Studio's calculated fields to derive step completion. It is more setup work than GA4's native funnel exploration, but the result is a dashboard page that any stakeholder can open and read without needing to configure an exploration themselves. If your funnel is stable enough to be worth formalizing into a Looker Studio page, this investment pays for itself quickly.

4. Content performance

For blogs, content sites, and any property where editorial output is a meaningful traffic driver, a content performance dashboard that breaks down engagement by article or topic is more actionable than the generic Pages and Screens report in GA4.

If you have set up a content_group or article_category custom dimension in GA4, use that as the primary dimension in your Looker Studio table. If not, use Page path as a proxy. Columns: Sessions, Average engagement time per session, Key events, and Key event rate. Average engagement time per session is the metric that separates genuinely read content from pages users land on and immediately leave — it is GA4's replacement for time on page and is a better quality signal than bounce rate for content sites.

Add a filter control that lets the viewer filter to a specific content category or URL pattern. This lets a content editor focus on their own section without being distracted by traffic from other parts of the site. A secondary chart showing the top ten pieces of content by Key events — rather than by sessions — often surfaces a different list and challenges assumptions about which content is actually driving business value.

5. Google Ads efficiency

This dashboard requires the GA4 plus Google Ads blend described in the connection section above. Once the blend is set up, the core chart is a table with Campaign as the dimension and columns for Impressions, Clicks, Cost, Key events, Cost per key event (a calculated field: Cost divided by Key events), and ROAS if you have revenue tracking (a calculated field: Conversion value divided by Cost).

Sort by Cost descending so the highest-spend campaigns appear first. Add a filter to exclude campaigns with zero spend in the selected period — this keeps the table readable when you have a large account with many paused campaigns. The Cost per key event metric is the column stakeholders should be sorting by when evaluating campaign efficiency — it directly answers "what am I paying per outcome" in a way that Click-through rate and Cost per click do not.

Add a second chart — a scatter plot with Cost on the x-axis and Key events on the y-axis, one point per campaign — to identify outliers: high-cost campaigns delivering few key events and low-cost campaigns delivering many. The scatter plot surfaces these relationships faster than scanning a sorted table.

Common Looker Studio + GA4 Pitfalls

"My Looker Studio data does not match GA4 reports"

This is the most common complaint when teams first connect Looker Studio to GA4, and it has a specific cause: sampling. GA4's standard reports are also sampled above certain thresholds, but Looker Studio and GA4 use different sampling algorithms and different thresholds, so the same date range can return different numbers from each interface.

The practical fix is to use shorter date ranges in Looker Studio. For most properties with under a few million sessions per month, date ranges shorter than 90 days return unsampled or minimally sampled data. If you need to run full-year comparisons without sampling distortion, the proper solution is to connect Looker Studio to the GA4 BigQuery export and query against the raw event tables, which are never sampled. This requires more setup but guarantees that your Looker Studio numbers match the unsampled source data rather than being subject to two independent sampling decisions.

A secondary cause of discrepancies is timezone handling. GA4 processes data in the property's configured timezone; the Looker Studio connector uses UTC for date-level aggregation unless you explicitly set a timezone override on the data source. If your property is in a timezone with a significant UTC offset, you may see day-level data shift by one row between GA4 and Looker Studio. Set the timezone on your Looker Studio data source to match the GA4 property's timezone to resolve this.

Metrics unavailable in the connector

The GA4 Looker Studio connector exposes a large field set but not the complete set of metrics available in the GA4 interface. Cohort analysis metrics, predictive metrics (purchase probability, churn probability), and user-lifetime value fields from the User Acquisition reports are not available through the connector. These metrics are derived from ML models that run on the full event dataset and are not accessible via the Reporting API that Looker Studio uses.

If you need these metrics in Looker Studio, the path is BigQuery. GA4 exports its ML-derived audience signals to BigQuery as part of the daily export, and you can query those tables and connect the results to Looker Studio via the BigQuery connector. This is an advanced setup and is only worth the complexity if the specific metrics you need are locked behind the ML-derived barrier. For most reporting use cases, the direct connector provides everything needed.

Slow dashboards

Looker Studio dashboards that load slowly are almost always the result of too many charts querying too much data simultaneously. Each chart on a Looker Studio page makes a separate API call to the underlying data source. A page with fifteen charts, each pulling data across a 12-month date range with three or four blended sources, can take 30 or more seconds to load — which means nobody looks at it.

The fixes are straightforward. First, one page per audience: put the acquisition overview on one page, the landing page report on another, and the paid media efficiency on a third. Viewers navigate to the page they need rather than loading everything at once. Second, always include a Date Range Control on every page and set a default range of 28 to 90 days rather than a full year. Third, limit blended data sources to charts that specifically need them — a channel breakdown that only uses GA4 data should not be attached to a blended source that also queries Google Ads. Fourth, avoid using the "All time" date range in any default chart configuration; it forces the connector to aggregate the entire property history on every page load.

Frequently Asked Questions

Is Looker Studio free?

Yes. Looker Studio (formerly Google Data Studio) is free for individuals and teams. There is a paid version called Looker Studio Pro that adds team management features, scheduled email delivery of reports, and SLA-backed support, but the core reporting and visualization functionality — including all connectors, blending, and sharing — is available in the free version. Most teams never need to upgrade to Pro.

Can I connect GA4 to Looker Studio?

Yes. There is a native Google Analytics connector in Looker Studio that connects directly to GA4 properties. You need at least Viewer access to the GA4 property in the same Google account you use to sign into Looker Studio. The connection takes about a minute to set up: create a new report, click "Add data," select Google Analytics, choose your account and property, and click Add. No API credentials or developer setup is required.

Why does my Looker Studio data not match GA4?

The two most common causes are sampling and timezone differences. Looker Studio and GA4 apply sampling independently above certain data thresholds, so the same date range can return slightly different numbers from each. Using shorter date ranges (under 90 days for most properties) reduces sampling discrepancy. Timezone mismatch causes day-level rows to shift — check that your Looker Studio data source timezone matches the timezone configured on your GA4 property in Admin → Data Streams.

Can I combine GA4 and Google Ads data in Looker Studio?

Yes. Add both the Google Analytics connector (for your GA4 property) and the Google Ads connector to your Looker Studio report. Then create a blended data source from the Resource menu, join the two on a shared dimension (Campaign is the most common), and map the fields you need from each. The resulting blend lets you place GA4 key event counts and Google Ads cost data in the same chart — which is the standard way to build a Cost Per Key Event or ROAS view.

How do I share a Looker Studio report?

Click the Share button in the top right of the report editor. You can share with specific Google accounts (giving them Viewer or Editor access), or generate a shareable link that gives anyone with the URL view access without requiring a Google login. The "Get shareable link" option is the most practical for external clients — they can view the report in a browser without needing a Google account or GA4 property access. Reports embedded via the link auto-refresh on a default schedule, so viewers always see current data.

What is the difference between Looker Studio and GA4 Explorations?

GA4 Explorations are an analyst workspace inside GA4 for ad-hoc queries — funnel analysis, segment comparison, path analysis. They require the viewer to have GA4 property access and are not designed as shareable dashboards. Looker Studio is a standalone report builder that connects to GA4 (and other sources) and produces interactive reports that anyone can view via a URL, without GA4 access. Explorations are better for analytical investigation; Looker Studio is better for recurring stakeholder reporting. The two complement each other and are not substitutes.

Can I use BigQuery data in Looker Studio?

Yes. Looker Studio includes a BigQuery connector that lets you write a SQL query or point to a BigQuery table and use the results as a data source for charts and tables. If you have GA4's BigQuery daily export set up, this means you can query raw, unsampled event data in Looker Studio — bypassing the sampling and field-availability limitations of the direct GA4 connector. The BigQuery connector requires a Google Cloud project with billing enabled (BigQuery query costs apply) and is the right choice for large properties or reporting needs that exceed what the direct connector can deliver.

Does Looker Studio work with Universal Analytics?

There is a Universal Analytics connector in Looker Studio, but Google shut down UA data processing in July 2023 and deleted UA property data in 2024. If you are using that connector today, it will return no data — the underlying GA3 API is no longer active. Any Looker Studio reports that were built on UA data need to be rebuilt using the GA4 connector with the equivalent GA4 property. There is no automatic migration path for Looker Studio reports from UA to GA4.