How to Create a Mobile App Dashboard in Google Analytics with AI

Building a successful mobile app is one thing, but understanding how people actually use it is a completely different challenge. A well-designed mobile app dashboard is your command center, giving you a real-time view of user acquisition, engagement, and stability. You can build this in Google Analytics 4, but it often involves a lot of clicking, dragging, and navigating complex menus. This guide will walk you through the essential metrics for a great mobile app dashboard and introduce a much faster way to create one using AI.

Why Bother With a Dedicated Mobile App Dashboard?

Jumping directly into the deep end of Google Analytics can feel overwhelming. A dedicated dashboard simplifies this by bringing your most important metrics to the surface. Instead of hunting for data across dozens of different reports, a dashboard gives you a single, scannable view of your app's health and performance.

Here’s what a good dashboard helps you do:

Make Quicker Decisions: See a sudden drop in daily active users or an increase in app crashes? A dashboard helps you spot these trends instantly, not a week later when you finally have time to dig into the data.
Understand User Behavior: A dashboard can immediately tell you which screens are most popular, how users are finding your app, and which features are driving the most engagement.
Track Toward Your Goals: Whether your goal is to grow your user base, increase in-app purchases, or improve retention, a dashboard visualizes your progress and keeps your team aligned on what matters most.
Stop Wasting Time: A solid dashboard automates the boring parts of reporting. All your key performance indicators (KPIs) are updated and available in real-time, freeing you from manually pulling numbers every Monday morning.

First Things First: Is Your App Data Flowing into GA4?

Before you can report on anything, your app's data needs to get into Google Analytics. For mobile apps, GA4 relies on Google Firebase to do the heavy lifting. Firebase is a platform designed for building and growing apps, and its software development kit (SDK) is what captures user interactions and sends them to GA4.

Linking Firebase to Google Analytics

If you haven't already connected your app to GA4, the process is straightforward. When you set up a new project in Firebase for your iOS or Android app, you'll be prompted to set up Google Analytics. If you have an existing Firebase project, you can link it to GA4 from your project settings.

Your journey looks like this:

Your app's code includes the Firebase SDK.
A user opens your app, views a screen, or makes a purchase.
The Firebase SDK logs this interaction as an event (e.g., screen_view, in_app_purchase).
Firebase sends this event data to your connected Google Analytics 4 property.
You now have the raw data needed to build your dashboard.

Once your data is flowing, you can start thinking about which metrics to display on your dashboard.

Building Your Dashboard: The Must-Have Mobile App Metrics

A great dashboard is organized into logical sections that tell a story about your app's performance. Think about it in terms of the user journey: acquisition, engagement, stability, and monetization.

User Acquisition

This section answers the question: "Where are my users coming from?" It’s all about understanding which channels and campaigns are driving new downloads and first-time users. Look for these metrics:

New Users: The total number of people who have opened your app for the first time. This is a top-line metric for growth.
Installs / First Opens: GA4 automatically tracks the first_open event, giving you a clear count of initial app installs.
Acquisition Channels: Break down your new users by source, medium, and campaign to see what's working. Are users coming from paid ads (Google Ads, Facebook Ads), organic search in the app store, website referrals, or social media?

User Engagement & Retention

Once you acquire a user, the work has just begun. This section answers: "Are users finding value in my app and coming back for more?" These metrics show how sticky your app is.

Daily & Monthly Active Users (DAU/MAU): The bread and butter of engagement tracking. DAU shows how many unique users engage with your app each day, while MAU shows the same over a 30-day period. The ratio between them (DAU/MAU) is a great health-check for stickiness.
User Engagement & Session Duration: An "engaged session" in GA4 is one that lasts for a minimum amount of time, includes a conversion event, or has at least two screen views. It’s a much better indicator of quality traffic than old metrics like bounce rate.
User Retention: Found in the Cohort Exploration report, retention shows you how many users who installed your app on a specific day or week come back in subsequent periods. High retention is a strong signal of product-market fit.
Top Screens: Track views of specific screens (e.g., 'home screen', 'settings page', 'product detail page') to understand which parts of your app are the most popular and where users spend their time.

App Stability & Performance

Bugs and crashes can ruin the user experience and drive people away for good. This section answers: "Is my app providing a stable, reliable experience?"

Crash-Free Users: This metric shows the percentage of users who didn’t experience a crash. Firebase Crashlytics provides incredibly detailed crash logs, but this top-level metric is perfect for a dashboard.
App Version Adoption: Are users on the latest, most stable version of your app? A high adoption rate for new versions is a great sign.
Device & OS Breakdown: If you see bug reports or stability issues, it’s helpful to know if they’re concentrated on specific devices (e.g., older Android phones) or operating systems.

Revenue & In-App Purchases

If your app has a business model built around purchases or subscriptions, this section is non-negotiable. It answers: "Is my app generating revenue?"

Total Revenue: The big-picture number showing total revenue collected from purchase or in_app_purchase events.
Average Revenue Per User (ARPU): This metric helps you understand the lifetime value of your customers and how it trends over time.
Purchasing Users: How many unique users are making purchases? Tracking this helps you understand the size of your paying customer base.
Top Purchased Items: If you sell multiple items, this shows you which are the most popular, giving you insights for promotions or product development.

The Manual Method: Building Your Dashboard in GA4

With your key metrics identified, you can start building a dashboard directly within the Google Analytics 4 interface. You have two main options for this: the standard Reports and the advanced Explorations.

Using the 'Reports Snapshot'

The ‘Reports Snapshot’ is the default dashboard view in GA4. You can customize this by choosing from a gallery of pre-built "cards," each displaying a specific metric. For example, you can add cards for 'New users by First user default channel grouping,' 'Sessions by device category,' and 'User activity over time.'

While this is quick for a high-level overview, it has limitations. You can’t create highly custom visualizations or combine data in very specific ways, which is often what you need to uncover real insights.

Creating a Custom 'Explore' Report

For more control, you’ll need to head to the ‘Explore’ section of GA4. Here, you can build custom reports from scratch using different visualization techniques like free-form tables, funnel explorations, and cohort analysis.

For example, to create a simple table of new users by traffic source, you would:

Navigate to 'Explore' and start a new 'Free-form' exploration.
In the 'Variables' column, import the dimensions 'First user source / medium' and 'Device category'.
Import the metric 'New users.'
Drag the dimensions onto the 'Rows' and 'Columns' fields in the 'Tab Settings' column.
Drag the 'New users' metric onto the 'Values' field.

Just one simple table requires multiple steps. Building a full dashboard with 10-15 different visualizations like this can quickly consume your entire afternoon. You have to know exactly which dimensions and metrics to combine, and the interface can feel clunky and slow.

The Smarter, Faster Way: Using AI to Build Your Dashboard

The manual process of report-building in traditional BI tools is exactly what modern AI-powered analytics platforms are designed to solve. Instead of learning the intricacies of a complex tool - like where every button is, or the exact name for a metric you want - you can simply describe what you want to see in plain English.

Imagine being able to build that same mobile app dashboard with prompts like these:

"Show me a dashboard of my key mobile app KPIs for the last 90 days, including new users, active users, and total revenue."
"Create a line chart of daily crash-free users for the last month."
"Build a bar chart showing my top 5 most viewed screens and a table view of new users by campaign."
"Compare user retention between users on iOS versus Android for cohorts that started in January."

An AI data analyst can take those natural language prompts and instantly translate them into the charts, graphs, and tables you need. For example, it understands that when you talk about traffic from 'phones,' you mean the 'mobile' device category in GA4. You don't need to know the official technical names of all 42 different data tables in a platform like Facebook Ads, you just describe what you're looking for, and the AI handles the translation.

This approach moves you from being a 'report builder' to someone who can focus solely on the insights in the data. You can drill down into a chart with follow-up questions like, "What campaign drove that spike in new users last week?" and get an immediate answer. This transforms data analysis from a tedious, click-heavy process into a fast-moving conversation.

Final Thoughts

Tracking your mobile app's performance is fundamental to its growth. A clear, well-structured dashboard gives you the insights needed to make smart decisions, but building it manually can be a time-consuming grind. You can spend your time mastering the GA4 interface or jump straight to getting the exact insights you need.

We built Graphed to completely remove this friction. After a few one-click connections to your data sources like Google Analytics, you can use simple, everyday language to build the live, real-time dashboards you need in seconds, not hours. Instead of wrestling with report builders, you can talk to your data, get insights faster, and get back to actually growing your app.