How to Create an Alerting Dashboard in Looker Studio with GA4 Data

Have you ever found yourself lost in the new GA4 reporting UI, struggling to find critical metrics that have dropped? Trust me, I've been there too. Clicking through countless reports to discover an issue, only to realize it's too late to take action... it's a nightmare!

But what if I told you there's a way to create an alerting dashboard in Looker Studio that will help you stay on top of your metrics and impress your boss? In this post, I'll walk you through the process step-by-step, using the alert dashboard example from my latest video tutorial.

If you want to see the full, step-by-step tutorial, check out my video:

Step 1: Set Up Your Dashboard with Key Metrics

To get started, we'll use the GA4 demo account data for a gaming app. We want to monitor the crash-free user rate, so let's drag that metric onto the canvas. This will serve as the foundation for our alerting dashboard.

[Insert screenshot of adding crash-free user rate metric to the dashboard]

Step 2: Set Alert Benchmark with Comparison

While the crash-free user rate alone doesn't provide much context, we can compare it to the previous period to spot potential issues. Click "Add Comparison" and select "Previous period." Now, we see that the crash-free user rate is up 0.1%. But don't celebrate just yet – an increase in crash-free user rate isn't always a good thing!

Next, let's create a time series chart to dig deeper and identify specific dates or periods that might be causing issues. This will help us pinpoint when alerts may be needed.

Side note: Sparklines are a great way to visualize trends in a compact format. They can help you quickly spot patterns and anomalies without taking up too much space on your dashboard. In the context of an alerting dashboard, sparklines can give you a quick overview of how your metrics are trending over time.

However, keep in mind that while sparklines are useful for spotting overall trends, they may not always provide enough detail for in-depth analysis. In our case, the sparkline shows a general trend in the crash-free user rate, but it's difficult to identify specific dates or periods that may require further investigation.

Step 3: Set Benchmarks with Reference Lines

To make the data even clearer and establish alert thresholds, let's add a reference line to serve as a benchmark. Choose "Median" as the reference type and select a color that stands out, like orange. Now, any points below the orange line are worth investigating and may trigger an alert.

Step 4: Identify High-Risk Areas with a Heatmap

Want to know which countries are experiencing the most crashes? A heatmap using the "crash-affected users" metric will quickly identify high-risk areas that may require immediate attention and targeted alerts.

Step 5: Highlight Issues with Conditional Formatting

To make important data stand out and visually alert us to potential problems, we can use conditional formatting in a table. Create a table with the crash-free user rate for each day in the last 28 days, and apply conditional formatting to highlight cells below the 50th percentile in red.

Now, you can easily spot the dates that require further investigation at a glance and set up alerts accordingly.

Step 6: Automate Alerts with Scheduled Email Delivery

Finally, to ensure that your team is always aware of important changes in your metrics, set up scheduled email delivery for your dashboard. Looker Studio allows you to schedule your dashboards to be sent via email on a daily, weekly, or monthly basis, effectively automating your alerting process.

By having your alerting dashboard delivered straight to your inbox, you can quickly review your key metrics each morning and take action if needed.