How to Make a Scatter Plot in Google Analytics

Trying to find a scatter plot in Google Analytics can feel like a search for a feature that doesn't exist – because it doesn't. While GA4 offers many standard reports, it lacks a native scatter plot visualization to help you spot relationships between two different metrics. This article will show you exactly why scatter plots are so useful for your GA data and guide you through a simple workaround to create them using Google Sheets.

Why Scatter Plots are a Game-Changer for Google Analytics Data

Before we jump into the "how," let's quickly cover the "why." A table filled with rows of data is useful, but it's terrible at showing relationships. A scatter plot excels at this one specific job: it visualizes the relationship between two separate numerical variables to reveal patterns, clusters, and outliers you would almost certainly miss in a spreadsheet.

In the context of Google Analytics, this lets you answer critical business questions like:

Which landing pages get tons of sessions but generate almost no revenue?
Do traffic sources with a high average session duration also have a low bounce rate?
What is the relationship between ad spend and conversions for different paid campaigns?
Are the articles with the most pageviews also generating the most ad impressions?

Scatter plots move you from looking at isolated metrics to understanding how they influence one another. This is where you find actionable insights - not just data points.

The Easiest Method: Creating a Scatter Plot via Google Sheets

Since Google Analytics doesn’t offer a native scatter plot, the most straightforward approach is to export your data and build one in Google Sheets. This takes a few minutes, but it's a reliable way to get the visualization you need. We'll use the example of analyzing the relationship between sessions and revenue for your website's landing pages.

Step 1: Get Your Data Out of Google Analytics 4

First, you need to pull the right dataset. You’re looking for a report that has one dimension (like "Landing Page") and at least two metrics (like "Sessions" and "Total revenue").

Log in to your Google Analytics 4 property.
Navigate to Reports → Engagement → Landing page in the left-hand menu.
By default, this report shows metrics like Sessions, Users, and Conversions. We need to add revenue. Click the pencil icon (Customize report) in the top-right corner.
In the menu that appears on the right, click Metrics. Click Add metric and search for and select Total revenue. Click Apply to save your changes.
Now, an essential step: make sure you have enough rows of data. At the bottom-right of the report table, click the "Rows per page" dropdown and select the largest number available (e.g., 250 or 500) to get a richer dataset.
Finally, click the Share this report icon (the arrow pointing up from a line) in the top right, then select Download File → Export to Google Sheets. GA will create a new Sheet in a new browser tab.

You've successfully pulled your data. Now it's time to shape it for our chart.

Step 2: Clean and Prepare Your Data in Google Sheets

The raw export from Google Analytics isn't quite ready for a chart. It typically includes several header rows and other summary information that will confuse Google Sheets.

Your goal is to have a simple, clean table with a single header row.

Delete extra rows: Your exported sheet will have about 6-8 header rows with the report name, date range, etc. Select and delete all of these rows so that the first row is just your column titles (Landing page, Sessions, New users, etc.).
Isolate your data: For our example, we only need three columns: Landing page, Sessions, and Total revenue. You can delete the other metric columns (like Users, Conversions, etc.) to keep things clean.
Check formatting: Ensure the Sessions and Total revenue columns are formatted as numbers, not text. Google Sheets is usually smart about this, but if you see numbers aligned to the left side of the cell, select the column, go to Format > Number > Number.

Your data should now look clean and simple: a column for your dimension and one column for each of your metrics.

Step 3: Build the Scatter Plot

With your data prepared, creating the scatter plot takes less than a minute.

Select your data: Click the column header for your first metric (e.g., "B" for Sessions), then hold down Ctrl (or Cmd on a Mac) and click the column header for your second metric (e.g., "C" for Total revenue). This highlights only the numerical data you want to compare.
Insert the chart: Go to the menu and click Insert → Chart.
Change the chart type: Google Sheets will probably guess the wrong chart type, often a Line Chart or Bar Chart. In the Chart editor pane that appears on the right, navigate to the Setup tab. Under Chart type, scroll down to find and select Scatter chart.

Voilà! You have a basic scatter plot. Each dot on the chart represents one of your landing pages, plotted according to its total sessions (on the x-axis) and its total revenue (on the y-axis).

Customizing and Interpreting Your Scatter Plot

A bare-bones chart isn’t very useful. Now it’s time to add context and, most importantly, interpret what the data is telling you. This is where the real value comes from.

Making Your Chart Readable

In the Google Sheets Chart editor, click over to the Customize tab.

Chart & axis titles: This is a must. Give your chart a clear title like "Landing Page Performance: Sessions vs. Revenue." Then, under Horizontal axis, give it the title "Sessions." Under Vertical axis, give it the title "Total Revenue." Without axis labels, the chart is meaningless.
Trendline: This is a powerful feature. Scroll down to the Series section and check the box for Trendline. This adds a line that shows the general correlation in your data. Is it sloping upwards (positive correlation), downwards (negative), or is it flat (no correlation)? For sessions vs. revenue, we hope to see it sloping up!

How to Read the Chart: The Four Quadrants

The best way to analyze a scatter plot is to mentally divide it into four quadrants to categorize your data points.

1. Upper-Right (High Sessions, High Revenue)

These are your stars. The landing pages in this section are doing everything right - they attract a lot of traffic and effectively convert that traffic into money.

Action: Protect these pages. Analyze them to understand what makes them successful and see if you can replicate that success on other parts of your site. Consider promoting them more heavily.

2. Lower-Right (High Sessions, Low Revenue)

These are high-potential pages that are failing to convert. You've done the hard part - getting eyeballs on the page. Now you need to find out why they aren't generating revenue.

Action: These are your primary candidates for CRO (Conversion Rate Optimization). Is the call-to-action unclear? Is the page loading slowly? Is the content not matching user intent? Dig deep here.

3. Upper-Left (Low Sessions, High Revenue)

These are your hidden gems or VIP pages. They don't get much traffic, but the visitors who do arrive are highly motivated and convert very well.

Action: The goal here is traffic generation. How can you get more of the right kind of traffic to these pages? Look for opportunities with targeted SEO, internal linking from your high-traffic pages, or specific paid ad campaigns.

4. Lower-Left (Low Sessions, Low Revenue)

These are your underperformers. They don't get much traffic and don't make much money.

Action: Generally, these aren't a priority unless you believe they have untapped potential. They might be older articles, unimportant pages, or content that simply doesn't resonate with your audience.

Final Thoughts

While Google Analytics doesn’t offer a native scatter plot, you can uncover incredibly valuable insights by exporting your data to Google Sheets. This simple manual process empowers you to see powerful relationships between your marketing and sales metrics, turning a flat data table into a strategic map of opportunities.

We know this manual process - exporting files, cleaning data, and building charts - takes valuable time away from actual analysis. That’s why we built Graphed. After connecting Google Analytics in just a few clicks, you can simply ask, "Create a scatter plot showing sessions vs. total revenue by landing page," and get an interactive, real-time dashboard in seconds, skipping the spreadsheet work entirely.