How to Embed GA4 Data in Your SaaS Product Dashboard

Author's Note

As the founder of an embedded analytics platform, I've spent years wrestling with various data APIs. When Google sunset Universal Analytics, our team had to dive deep into the new GA4 Data API to build our native connector. It was a learning experience, and I want to share the direct, developer-focused insights we gained to help you bypass the frustrating parts and get straight to building.

Disclosure: This article is published by Dashrendr. Where Dashrendr is relevant, I say so directly — including its limitations.

Why Embedding GA4 Data is a Game-Changer for SaaS

Showing your customers how their own users interact with your product is valuable, but what if you could also show them how their marketing efforts drive that interaction? This is the power of embedding a GA4 data dashboard directly into your SaaS platform. You're not just providing product analytics; you're providing a holistic view of their business.

The primary keyword here is embed GA4 dashboard. This refers to the process of using the Google Analytics 4 Data API to pull user-specific data and display it within the UI of your own application, rather than sending your users to the Google Analytics interface. For SaaS companies, this means you can offer powerful, in-context insights without breaking your user's workflow.

According to a 2023 report from Fivetran, over 85% of business leaders believe that data is one of their company's most valuable assets. By embedding analytics, you empower your customers to leverage their own data directly within your tool. This transforms your platform from a simple utility into an indispensable partner for growth.

Defining the Key Concepts

Before we dive into the technical details, let's clarify some terms:

• GA4 Embedded Analytics: This is the practice of integrating Google Analytics 4 data, reports, and visualizations into an external application. The goal is to make GA4 insights feel like a native part of the host application's user experience.
• GA4 SaaS Dashboard: This is a specific application of embedded analytics where the dashboard is built for the customers of a Software-as-a-Service product. These dashboards are often multi-tenant, meaning each of your customers sees only their own GA4 data, securely separated from others.

The key difference from past methods is the shift away from the deprecated Google Analytics Embed API. As noted by developers on Stack Overflow, the old API was limited and designed around embedding Google's own UI. The modern approach uses the much more flexible GA4 Data API, which gives you raw data, not pre-built charts.

Authentication: The First Hurdle

Connecting to the GA4 Data API isn't as simple as plugging in a key. Google uses the robust but complex OAuth 2.0 framework to manage access. You have two primary paths for authentication in a SaaS context: have your customers authenticate their own accounts, or use a service account with granted access.

Method 1: User-Managed OAuth 2.0 Flow

In this model, each of your customers goes through an OAuth consent screen to grant your application permission to access their GA4 data. This is secure and puts the customer in control. However, it requires a more complex setup on your end to handle the OAuth tokens (access tokens, refresh tokens) for every user.

This is the standard approach for applications that need to act on behalf of the user. For a detailed overview of the protocol, the official IETF RFC 6749 is the source of truth, though it's a dense read. Essentially, your app will redirect the user to a Google consent screen, and upon approval, Google will redirect back to your app with a code that you can exchange for an access token.

Method 2: Using a Service Account

A service account is a special type of Google account that belongs to your application instead of an individual user. This method is simpler on the surface. You create a service account in your Google Cloud project, and your customers grant that account's email address read-only access to their GA4 property. Your backend then uses the service account's credentials (a JSON key file) to authenticate all API requests.

This simplifies token management immensely but introduces a manual setup step for your customers. They must be comfortable adding a service account email to their Google Analytics user list. This is often the preferred method for enterprise SaaS, as it centralizes control.

Architectural Takeaway: The choice between user-managed OAuth and a service account is a critical architectural decision. User-managed OAuth offers a smoother user experience but higher development complexity. Service accounts are simpler to code but require manual customer setup. Choose the path that best fits your target customer's technical comfort level.

Querying the GA4 Data API: Metrics and Dimensions

Once authenticated, you can start requesting data. The GA4 Data API works by requesting a combination of metrics and dimensions.

• Metrics are the quantitative measurements. Think of things like sessions, totalUsers, or conversions.
• Dimensions are the attributes you want to segment your metrics by. Common examples include country, pagePath, or sessionSource.

For example, a basic request might ask for the metric sessions broken down by the dimension country. The API response will be a JSON object containing rows of data, with each row showing a country and the corresponding number of sessions. The official GA4 Data API documentation provides a full list of available metrics and dimensions.

A significant portion of web traffic now comes from mobile devices. StatCounter's 2024 data shows that mobile accounts for over 59% of all web traffic worldwide. Therefore, including dimensions like deviceCategory (desktop, tablet, mobile) is crucial for providing a complete picture in your embedded GA4 SaaS dashboard.

This API-driven approach is a departure from Universal Analytics' Embed API, which primarily involved embedding pre-built iframes. While faster to implement, the old method offered almost no customization. The new API gives you raw data, granting you complete control over visualization and presentation—a necessity for a truly native feel.

Building the Dashboard: From Data to Visualization

You have the data. Now what? You need to turn that JSON response into a user-friendly dashboard. This is where you have the most creative freedom and also where the most work lies. You'll need a charting library (like ECharts, Chart.js, or D3.js) to render the visuals.

This entire process—authentication, data fetching, and visualization—is the core problem that embedded analytics platforms like Dashrendr are built to solve. Instead of you writing the backend code to handle OAuth flows, manage API quotas, and transform data for a charting library, you can use a platform that has already done the heavy lifting.

With Dashrendr, for example, you connect your customer's Google Analytics account (or use our secure agent for service account-style access), and then you can build a full dashboard using a visual, drag-and-drop builder. The platform handles all the API interaction in the background. The output is a simple embeddable component that you place in your SaaS application. This can reduce development time from weeks or months to a single afternoon. If you'd like to see how this works, you can start a 14-day free trial, no credit card required.

A Note on Multi-Tenancy

When building a GA4 SaaS dashboard, security and data isolation are paramount. Each of your tenants (customers) must only see the data from the GA4 property they have authorized. This requires careful management on your backend. You need to map each of your internal user accounts to the correct GA4 Property ID and ensure every API request includes the right identifier.

This is another area where using a dedicated platform helps. Dashrendr is built from the ground up for multi-tenant SaaS, handling the user-to-data-source mapping securely behind the scenes. This is a significant advantage over building from scratch, where a single bug could potentially lead to a data leak between customers.

Limitations and Considerations

While powerful, the GA4 Data API has its limits. Google enforces quotas on the number of API requests you can make per day and per hour. According to Google's documentation, the default is 25,000 requests per day per project. For a SaaS with many customers, you can quickly hit this limit if you're not careful about caching data and optimizing your requests.

This is one reason why many developers choose to build a data pipeline. Instead of querying the API live every time a user loads a dashboard, they periodically pull the data, store it in their own database (like PostgreSQL or BigQuery), and serve the dashboard from there. This adds complexity but gives you more control and performance. Tools like our own BigQuery connector or MySQL integration can be part of such a solution.

It's also important to acknowledge limitations in platforms. For instance, while Dashrendr excels at visualizing data from single sources like GA4 or a PostgreSQL database, it does not yet support cross-connection joins in the dashboard builder. If your goal is to combine GA4 data with your internal product database metrics *in a single chart*, you would first need to unify that data in a warehouse like BigQuery before connecting it to Dashrendr. This is a feature on our roadmap, as we know combining data sources is a powerful use case.

Ultimately, deciding whether to build a custom GA4 integration from scratch or use a platform comes down to a classic build vs. buy calculation. Building gives you ultimate control but requires significant, ongoing developer resources. Buying (or subscribing to a service like Dashrendr, with plans starting at $6/month) accelerates your time to market and lets your team focus on your core product features. Given that a recent survey from Looker found that data professionals spend up to 60% of their time just cleaning and preparing data, offloading this work can be a massive productivity boost.

The journey to embedding GA4 data is a rewarding one. It can deepen your relationship with your customers and make your product stickier. Whether you choose to build it yourself or leverage a platform, you are embracing the future of SaaS: data-driven, insightful, and user-centric.