A Note from the Founder
As a developer building a SaaS, I've spent countless hours navigating the sea of metrics in Google Analytics 4. When we first built the GA4 connector for Dashrendr, the sheer volume of available data was overwhelming. It’s easy to get lost. That experience taught me a crucial lesson: for customer-facing dashboards, the goal isn't to show everything, but to show the *right* thing. This guide is my attempt to share that hard-won clarity with you.
Disclosure: This article is published by Dashrendr. Where Dashrendr is relevant, I say so directly — including its limitations.
Why Your Choice of GA4 Metrics Matters in SaaS
Offering customer-facing analytics is no longer a luxury; it’s a core feature that drives retention. Your users want to see the value they're getting from your product, and often, that value is reflected in their own data. Google Analytics 4 is a powerful source for this, but it's a double-edged sword. With hundreds of metrics and dimensions, it’s incredibly easy to build a cluttered, confusing, and ultimately useless dashboard.
The key is to move from data-puking to providing curated, actionable insights. A well-designed GA4 metrics dashboard helps your customers answer their own business questions. It transforms your product from a simple tool into an indispensable partner in their growth. According to McKinsey, data-driven organizations are not only more efficient but are also 23 times more likely to acquire customers. By providing clear analytics, you empower your users to become a data-driven organization themselves.
Core GA4 Metric Categories Explained
Before we dive into specific KPIs, it's helpful to understand how Google organizes them. Most metrics in GA4 fall into one of four main categories, reflecting the customer lifecycle:
- Acquisition: How users arrive at a website or app.
- Engagement: What users do once they've arrived.
- Monetization: Tracking revenue from purchases, ads, or subscriptions.
- Retention: Measuring how well you maintain users over time.
For a typical B2B SaaS product providing dashboards to its customers, the most relevant metrics will be concentrated in Acquisition and Engagement. You're helping your customers understand *their* users' behavior.
Definition: Key Performance Indicator (KPI)
A Key Performance Indicator is a measurable value that demonstrates how effectively a company is achieving key business objectives. In the context of a customer-facing dashboard, KPIs are the vital few metrics that tell the most important part of the story, as opposed to the trivial many.
What metrics are available on GA4?
This is a common question, and the answer can be daunting: hundreds. Google provides a massive list of dimensions and metrics that can be pulled via its API. They cover everything from high-level user counts to granular details about ad clicks and device models. A complete list is almost impossible to memorize and would be impractical to display.
Instead of thinking about every single metric, it's better to understand the main categories and select a handful that align with the story you want to help your customer understand. For a comprehensive, technical list, the official Google Analytics Dimensions & Metrics Explorer is the authoritative source.
Top 5 User & Acquisition KPIs for Customer Dashboards
This group of metrics helps your customers understand who their audience is and where they come from. It's the foundation of any good analytics dashboard.
- Total Users: The fundamental count of distinct individuals who have visited the site. While simple, it's the primary measure of audience size and reach.
- New Users: This KPI tracks the number of first-time visitors, providing a clear signal of audience growth. It's crucial for your customers to see if their marketing efforts are attracting new people.
- Traffic Source / Medium: This isn't a single metric but a dimension-based report. Showing users a breakdown of traffic from 'google / organic', 'facebook / social', or 'newsletter / email' is incredibly powerful. It tells them which channels are working.
- Session Count: A session is a group of user interactions with a website that take place within a given time frame. A higher session count per user can indicate strong loyalty and repeat usage.
- Views by Country/City: A simple demographic dimension that can provide powerful insights. For your customers, knowing where their users are physically located can influence marketing, content, and even product decisions.
Top 5 Engagement & Conversion KPIs for Customer Dashboards
Once your customers know who is arriving, the next logical question is: what are they doing? Engagement metrics answer this. According to HubSpot, a staggering 80% of customers rate a company's experience as being as important as its products.
Definition: User Engagement
User Engagement measures the extent of a user’s interaction with a website or application. In GA4, an engaged session is one that lasts longer than 10 seconds, has a conversion event, or has at least 2 pageviews. This is a far more nuanced and useful metric than the old 'Bounce Rate'.
- Engagement Rate: The percentage of sessions that were 'engaged sessions'. This is the new hero metric in GA4, replacing the problematic 'Bounce Rate'. A high engagement rate signals that users are finding the content relevant and useful.
- Average Engagement Time: This shows the average length of time the app or website was in the foreground of the user's device. It's a direct measure of attention and a great indicator of content quality.
- Views (formerly Pageviews): The total number of screens or pages users saw. Tracking views for specific pages or sections of your customer's site can show what content is most popular.
- Key Events (formerly Goals): This is arguably the most important KPI. Your customers can define what a 'conversion' means to them (e.g., 'form_submitted', 'demo_requested', 'product_purchased'). Displaying the count and completion rate of these Key Events directly ties their website activity to business outcomes.
- User Stickiness (DAU/MAU Ratio): This is a slightly more advanced, calculated metric (Daily Active Users divided by Monthly Active Users). It’s a powerful indicator of user retention and product value. While not a default GA4 metric, you can calculate it from the base user data, and it provides a fantastic measure of how frequently users return.
The goal of a customer-facing dashboard isn't to mirror the entire GA4 interface. It's to provide curated, actionable insights that help your users succeed with minimal cognitive load. Less is almost always more.
How Dashrendr Simplifies Building a GA4 Metrics Dashboard
Knowing which metrics to show is half the battle. The other half is implementing it. This is where a dedicated embedded analytics platform like Dashrendr comes in. Instead of wrestling with the GA4 API, you can use our native Google Analytics connector to pull data directly and securely.
You can use our drag-and-drop dashboard builder to create a polished, white-label embedded analytics interface for your users in minutes, not weeks. This is the core idea behind Dashrendr: to handle the complexity of data connection, visualization, and embedding, so you can focus on your core product. Check out our guide on how to embed GA4 data in your SaaS dashboard for a step-by-step walkthrough.
An Honest Limitation: While Dashrendr's native GA4 connector is incredibly powerful for visualizing analytics data, we don't currently support cross-source joins within a single dashboard component. For example, if you wanted to combine GA4 user data with subscription data from your PostgreSQL database in one chart, the direct connector approach wouldn't work. For this scenario, we recommend our equally supported REST API ingestion path. You can pre-aggregate the combined data on your backend and push it to a Dashrendr dataset. This gives you ultimate flexibility and control, but it's an important architectural choice to make.
We believe in transparent and affordable pricing. Dashrendr plans start at just $6/month, and every plan comes with a 14-day free trial, no credit card required. You can get started today and have a working GA4 dashboard embedded in your app by this afternoon.
Common Pitfalls to Avoid When Displaying GA4 Metrics
Building the dashboard is just the beginning. To make it truly effective, you need to avoid these common traps:
- Showing Vanity Metrics: Total 'Likes' or other social metrics might feel good, but they rarely lead to actionable decisions. Focus on KPIs that correlate with business success, like Engagement Rate and Key Events.
- Creating a 'Data-Wall': Don't just throw numbers on a screen. Too many charts and figures without hierarchy or context will overwhelm your users. A good dashboard should be scannable in 30 seconds.
- Lack of Context: A number like '500 users' is meaningless on its own. Is that good or bad? Add comparisons ('+10% from last month') or targets to give the data meaning. As you think about this, review some dashboard design best practices.
Ultimately, the choice between building your own analytics from scratch and using a platform is a major one. We've written extensively on the build vs. buy decision for embedded analytics to help you make the right choice for your team.
Tags
What is Cohort Analysis? A Guide for SaaS Teams
A comprehensive guide for SaaS founders and developers on cohort analysis. We break down what cohorts are, why they are essential for tracking SaaS metrics like retention and churn, and provide a step-by-step guide on how to conduct a cohort analysis for your own product.
What Is Data Aggregation? A Dev's Guide for SaaS
A developer-focused guide to data aggregation for SaaS dashboards. This post breaks down what data aggregation means, why it's critical for performance and cost, how it compares to ETL, and practical ways to implement it using direct database connections or a REST API.
What Is a Stacked Area Chart? A Guide for SaaS Teams
A comprehensive guide to stacked area charts for SaaS developers. This post covers what they are, when to use them, how to read them, and key differences from other charts like line charts. Learn how to visualize part-to-whole relationships over time effectively in your analytics dashboards.
