How to Find Exit Rate in Google Analytics 4

If you've recently moved over to Google Analytics 4, you might be scratching your head trying to find a familiar, crucial metric: Exit Rate. Don't worry, you aren't missing something obvious - it's gone. But that doesn't mean you can no longer track which pages are causing visitors to leave your site. This article will show you exactly how to find and calculate the Exit Rate for any page on your website using GA4's built-in tools.

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Why Did Google Analytics 4 Remove the Exit Rate Report?

The disappearance of the standard Exit Rate report stems from GA4's fundamental redesign. The previous version, Universal Analytics (UA), was a session-based model. It thought about user behavior in terms of visits (sessions), pageviews within those visits, and how those sessions ended (with an exit or a bounce).

GA4, on the other hand, is an event-based model. Everything a user does - from scrolling down a page to clicking a link or playing a video - is tracked as a distinct "event." In this new model, a session is simply a collection of events that happened in a specific timeframe. The concept of an "exit" doesn't fit as neatly into this structure because GA4 is more focused on the actions users take rather than the container (the session) they take them in.

While the standard report is gone, the raw data to calculate exit rate still exists. The metric for Exits is still tracked, you just have to do a little more work to combine it with page views to find your rate.

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Exit Rate vs. Bounce Rate in GA4: What’s the Difference?

Before we go further, it's important to clarify the difference between two often-confused metrics: exit rate and bounce rate. They may seem similar, but they tell you two very different things about user behavior.

• Exit Rate: This is the percentage of sessions that ended on a specific page. For all the pageviews a page received, Exit Rate tells you what percentage of them were the last pageview of the session. A high exit rate could mean that a page isn't compelling users to explore further, or it could mean the page successfully gave the user what they were looking for (like a "Thank You" page after a purchase).
• Bounce Rate: This is a session-level metric. A "bounce" is a session where a visitor came to your website, viewed only one page, and then left without taking any other action (like clicking a link or signing up). So, Bounce Rate is the percentage of all sessions that consisted of only a single pageview.

To put it simply: all bounces are exits, but not all exits are bounces. A person could visit your homepage, click to your services page, then click to your contact page, and then exit. That's not a bounce, because they viewed three pages. But an exit was recorded for the contact page.

How to Manually Calculate Exit Rate

Since GA4 doesn't give you Exit Rate as a pre-built metric, you need to calculate it yourself. Fortunately, the formula is straightforward. In Universal Analytics, it was (Exits) / (Pageviews). In GA4, the terminology has changed slightly, but the logic is the same:

The GA4 Exit Rate Formula: Exit Rate = Exits / Views

Here, Views is the GA4 equivalent of "Pageviews." So, if your pricing page received 1,000 views and recorded 300 exits, your Exit Rate for that page would be 30% (300/1000).

Creating an "Exit Rate" Report in Google Analytics 4

The real question is, where do you find the Exits and Views data to plug into that formula? The answer lies within the Explore section of GA4, which allows you to build custom reports. Let’s walk through it step-by-step.

Step 1: Navigate to the Explore Section

In the left-hand navigation menu of your GA4 property, click on the Explore icon. This is where you can build custom reports from scratch instead of relying on the standard ones.

Step 2: Create a New Blank Report

In the Exploration workspace, click on the large plus sign labeled "Blank" to start building a new exploration report.

Step 3: Define Your Variables (Dimensions & Metrics)

A blank report has two main columns on the left: Variables and Tab Settings. To start, you need to import the dimensions and metrics you want to use into the Variables column.

1. Click the plus icon (+) next to DIMENSIONS.
2. In the search box, type "Page path" and select the dimension called Page path and screen class. This will show you the URL path for each page (e.g., /blog/my-post-name). Click the blue Import button.
3. Now, click the plus icon (+) next to METRICS.
4. In the search box, type "Exits" and select it.
5. Without closing the window, search for "Views" and select that as well.
6. Click the blue Import button.

You should now see Page path and screen class, Exits, and Views listed under the Variables column.

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Step 4: Build Your Report

Now that your building blocks are ready, you can drag them from the Variables column into the Tab Settings column to create your report.

• Drag Page path and screen class from Dimensions and drop it over the "Drop or select dimension" box under ROWS in the Tab Settings column.
• Drag both Exits and Views from Metrics and drop them over the "Drop or select metric" box under VALUES.

As you do this, your report on the right-hand side will populate instantly. You will now see a table listing all of your website pages (by their URL path), with columns showing the total number of Views and Exits for each.

Step 5: Export and Calculate

Notice that you have the raw numbers, but there's no calculated "Exit Rate" column in the GA4 interface. Annoying, right? To get the final rate, you need to export this data.

1. In the top right corner of the exploration report, click the share icon (a small rectangle with an arrow).
2. Choose your preferred export format. Google Sheets or CSV (Comma-separated values) are the best options for this.

Once you open the file in Google Sheets or Microsoft Excel, simply create a new column called "Exit Rate." In the first cell of that column, enter the formula to divide the Exits cell by the Views cell (e.g., =B2/C2). Format the cell as a percentage, and then drag the formula down for all your pages. You finally have your Exit Rate report!

Limitations of This Method

While this process works, it's far from perfect. The biggest drawback is that it's completely manual and repetitive. The report isn't live, if you want to see updated data tomorrow, next week, or next month, you have to go through the entire process of exporting and recalculating again. This reporting busywork can eat up hours that you could be spending on actual analysis and strategy.

So, What's a Good Exit Rate?

Once you have the data, you need to understand what it's telling you. A high exit rate isn’t inherently a bad thing - in fact, sometimes it's exactly what you want. Context is everything.

• High Exit Rate (Good): Think about pages where the user's journey is supposed to end. A "Thank you for your purchase" page, a contact form submission confirmation, or a support ticket filed page should have a very high exit rate. If they don't, it might mean users are confused about what to do next.
• High Exit Rate (Potentially Bad): Pages in the middle of a conversion funnel should have low exit rates. For example, if your shopping cart page or a key step in your checkout process has a high exit rate, you're losing customers right before they purchase. Similarly, if your product detail pages or pricing page have high exit rates, it could indicate users aren't finding the information they need or aren't convinced to move forward.
• High Exit Rate (It Depends): For informational content like blog posts, a high exit rate can be neutral. A user might arrive from Google, find the answer to their question, and leave satisfied. However, if the goal of your blog is to lead readers to your products or services, a high exit rate is a sign that your calls-to-action or internal linking might need improvement.

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How to Use Exit Rate to Improve Your Website

With correct context, Exit Rate becomes a powerful diagnostic tool for identifying weak points on your site. Here’s how to put it into action:

1. Identify Leaks in Your Conversion Funnel

Map out the key steps a user takes to convert (e.g., Homepage > Product Page > Add to Cart > Checkout > Confirmation). Pull your exit rate report and look for pages in this funnel with unusually high numbers. Those are your biggest leaks and where you should focus your optimization efforts first.

2. Analyze On-Page Content and UX

For pages with a high exit rate where you want users to stay, dive deep into the page itself.

• Is the call-to-action (CTA) clear and compelling?
• Is the copy confusing or does it fail to answer key questions?
• Is the design cluttered or hard to navigate?
• Is there a clear next step for the user to take?

3. Check for Technical Problems

Sometimes, a high exit rate is a symptom of a technical issue. Check high-exit pages for:

• Slow Page Load Speed: Use Google's PageSpeed Insights to test your performance. Users have little patience for slow sites.
• Broken Elements: Are all the buttons, forms, and links working correctly?
• Poor Mobile Experience: Does the page render properly and is it easy to use on a smartphone?

Final Thoughts

While Google Analytics 4 forces you to do a little more work, calculating Exit Rate is still very possible using the Explorations tool. By pulling your Views and Exits data, you can build a custom report and calculate this vital metric to identify where users are abandoning your site and find opportunities for improvement.

Constantly exporting data and wrangling it in spreadsheets to answer basic questions is a time-consuming process. To solve this, we built a tool that connects to your key data sources - like Google Analytics, Shopify, or Salesforce - and automates the entire process. Instead of building manual reports, you can just ask Graphed a question like, "Show me a chart of the top 10 exit pages for last month," and get a real-time visualization instantly, without ever opening a spreadsheet.