Most GA4 dashboards die the same death: someone spends hours building one, the team glances at it once, and then everyone goes back to asking "can you pull the numbers for me?" in Slack.
The problem isn't the tool. It's that most GA4 dashboards are built around data availability ("here's everything GA4 tracks") instead of decision-making ("here's what you need to act on today"). This guide walks through how to build GA4 dashboards that people actually open, across four different platforms — from GA4's native interface to AI-powered alternatives.
Before opening any dashboard tool, answer these three questions. They determine whether your dashboard gets bookmarked or forgotten.
Different audiences need different dashboards:
Every metric on the dashboard should tie to an action:
If a metric doesn't trigger an action, remove it. Dashboard clutter is the #1 reason people stop checking.
Match the refresh frequency to the check-in cadence. A monthly dashboard doesn't need real-time data.
GA4 doesn't have a traditional "dashboard builder" like Universal Analytics did. Instead, it offers three ways to create dashboard-like views.
GA4 lets you customize the left-hand navigation with your own report collection.
Your custom collection now appears in the Reports sidebar for everyone with access to the property.
Best for: Creating a curated set of standard reports that your team can navigate without building explorations from scratch.
GA4 Explorations are more flexible than standard reports and can serve as lightweight dashboards.
Verdict: GA4's native tools work for quick ad-hoc analysis but fall short for team-facing dashboards that need to look polished, update automatically, and serve multiple audiences.
Looker Studio (formerly Google Data Studio) is Google's free dashboard tool and the most popular way to build GA4 dashboards. It connects natively to GA4 with no configuration.
Place these elements on a single page:
Verdict: Looker Studio is the best free option for GA4 dashboards. If your team uses Google Workspace, it's the default choice. But be prepared to invest 2-4 hours per dashboard for a polished result.
If your organization standardizes on Microsoft tools, you can build GA4 dashboards in Excel (pivot charts + slicers) or Power BI.
For detailed Excel techniques, see our Excel data analysis guide.
For a broader comparison of BI tools, see our Power BI vs Tableau vs QlikView comparison.
Traditional dashboards have a fundamental problem: someone has to decide what goes on them before anyone looks at the data. That means you're pre-selecting which metrics matter, which segments to show, and which time periods to compare. If the interesting insight lives outside those choices, nobody sees it.
AI-powered dashboards flip this. Instead of designing a static layout, you connect your GA4 data and the AI generates dashboards based on what's actually happening in your data — surfacing anomalies, trends, and segment differences automatically.
Regardless of which tool you use, these are the metrics worth tracking in GA4 dashboards, organized by use case.
| Metric | What It Tells You | Action Trigger |
|---|---|---|
| Active users | How many people visited | Sudden drop = investigate traffic source or site issue |
| Sessions by source/medium | Where traffic comes from | Low-performing source = reallocate budget |
| New vs returning users | Audience growth vs retention | All new, no returning = retention problem |
| Metric | What It Tells You | Action Trigger |
|---|---|---|
| Engagement rate | % of sessions that engaged (>10s, 2+ pages, or conversion) | Below 50% = landing page or content problem |
| Avg. engagement time | How long people actively spend on pages | Very low on long-form pages = content isn't resonating |
| Views per session | How deep users go | Close to 1 = poor internal linking or irrelevant traffic |
| Metric | What It Tells You | Action Trigger |
|---|---|---|
| Key events (conversions) | Total goal completions | Declining trend = funnel or traffic quality issue |
| Session conversion rate | What % of sessions convert | Source with high traffic but 0% rate = wrong audience |
| Revenue (if e-commerce) | Bottom line impact | Revenue per user trending down = pricing or AOV problem |
If your dashboard has more than 10-12 widgets on a single page, people won't read any of them. Ruthlessly cut to the metrics that drive decisions. Everything else goes on a separate deep-dive page.
A number without context is meaningless. "10,000 sessions" — is that good? Bad? Always show a comparison: previous period, same period last year, or a target/benchmark. Scorecards with green/red trend arrows communicate instantly.
GA4 renamed many metrics (bounce rate → engagement rate, goals → key events). If your audience is used to Universal Analytics terms, add labels or a legend. Better yet, use calculated fields with business-friendly names ("Signup Rate" instead of "key_event_rate").
Your dashboard is only as good as the data feeding it. If key events aren't configured correctly in GA4, your conversion metrics will be wrong. Before building a dashboard, audit your GA4 event tracking to ensure all critical actions (sign-ups, purchases, form fills) are captured.
An exec and a campaign manager need completely different views. Build separate dashboards (or separate pages within one report) for each audience. A 15-page dashboard that tries to serve everyone serves nobody.
→ GA4 native (Custom Reports + Explorations). Zero setup, always up to date.
→ Looker Studio. Free, connects natively to GA4, supports scheduled email delivery.
→ Power BI or Excel. Connect via BigQuery or API. See our GA4 to Excel guide for connection methods.
→ Anomaly AI. Connect GA4, ask for a dashboard in plain English, get charts with explanations and SQL transparency.
Yes. Universal Analytics had a built-in "Dashboards" section where you could place widgets on a canvas. GA4 replaced this with custom report collections and explorations, which are more powerful but require a different workflow. For traditional dashboard layouts, use Looker Studio.
GA4's native Realtime report shows the last 30 minutes of activity, but it can't be customized or shared as a dashboard. Looker Studio with GA4 has a 15-30 minute data lag. For near-real-time, enable BigQuery streaming export and build dashboards on top of BigQuery.
Start with 2-3: an executive overview (5 KPIs), an acquisition/marketing dashboard, and a content/product dashboard. Add more only when a specific team needs a dedicated view. Fewer dashboards that get used regularly beat 20 dashboards that nobody opens.
Yes, depending on the tool. Looker Studio supports blended data sources (GA4 + Search Console + Sheets). Power BI can combine GA4 (via BigQuery) with any other data source. Anomaly AI connects GA4 alongside BigQuery, MySQL, Snowflake, and Excel in one analysis.
Ready to build GA4 dashboards without the manual work? Get started with Anomaly AI — connect your GA4 property and have an AI analyst build your first dashboard in minutes.
Experience AI-driven data analysis with your own spreadsheets and datasets. Generate insights and dashboards in minutes with our AI data analyst.
Founder, Anomaly AI (ex-CTO & Head of Engineering)
Abhinav Pandey is the founder of Anomaly AI, an AI data analysis platform built for large, messy datasets. Before Anomaly, he led engineering teams as CTO and Head of Engineering.
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