How to Make a Scatter Plot in Google Analytics with AI

Ever wondered if pages with tons of traffic are the ones actually making you money? Or if there's a link between how long people stay on your site and your bounce rate? A scatter plot is the perfect visual for answering these kinds of questions, but Google Analytics doesn't have a built-in option to create one. This tutorial will show you exactly how to visualize the relationship between different GA metrics, from the classic manual method to the faster, more modern AI approach.

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Why Use a Scatter Plot with Your Google Analytics Data?

While standard GA reports like bar charts and tables are great for tracking individual metrics, a scatter plot shines when you need to see the relationship between two different metrics. Each dot on the plot represents a single dimension (like a specific landing page, country, or traffic source) and is positioned based on its value for your two chosen metrics. This quickly reveals patterns, clusters, and outliers you’d otherwise miss by just looking at rows of data.

Think about the types of relationships you can expose:

• Page Performance: Plot Sessions on the X-axis and Conversions or Transactions on the Y-axis. This instantly shows you which high-traffic pages are underperforming (high sessions, low conversions) and which low-traffic pages are surprise winners (low sessions, high conversions).
• Audience Engagement: Compare Average Engagement Time against Bounce Rate for different demographics or traffic sources. You might find that a certain ad campaign brings in visitors who don't bounce but also don’t engage deeply, signaling a targeting issue.
• Channel Effectiveness: Analyze the relationship between Users and Event Count (for a key conversion event) across all your marketing channels. A channel with lots of users but a low event count might be driving awareness but not action.

These visuals stop you from making common mistakes, like assuming your most-visited page is your most valuable one. By plotting relationships, you get a smarter, more nuanced view of what's truly driving your business.

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The Challenge: Google Analytics Doesn't Offer Native Scatter Plots

If scatter plots are so useful, why aren't they a standard report in Google Analytics? The simple truth is that while GA is a beast at data collection and standard reporting, its built-in visualization tools are limited. It excels at showing your core metrics over time or in tables, but for more advanced analysis like correlation and relationship mapping, you have to look outside the GA interface.

This is why the go-to method for years has been the trusty, if tedious, data export. You find the report you need, pull the data out of Google Analytics, and then bring it into a tool that can create a scatter plot, like a spreadsheet program.

The Traditional Workaround: Manual Export

The manual process involves exporting your data to a CSV file or pushing it directly to Google Sheets. It's a fundamental skill for any marketer who needs to dig deeper than standard GA reports allow.

Here’s the basic workflow:

1. Log into your Google Analytics 4 property.
2. Navigate to the report that contains the data you want to analyze. For instance, go to Reports > Engagement > Pages and screens to look at page performance.
3. Adjust the date range for your desired analysis period.
4. In the top right corner of the report, look for the "Share this report" icon (a simple arrow pointing up out of a box) and click it.
5. Select "Download File" and then choose either "Download CSV" or "Download PDF". For building charts, CSV is your best option.

This simple process gives you a static snapshot of your data. While it works, it's also where the real manual labor begins - the data is out of GA, but now you have to clean, format, and visualize it yourself.

Method 1: Manually Forging a Scatter Plot in Google Sheets

Let's walk through the classic way to create a scatter plot. This method gives you complete control over your final chart, and if you're comfortable in spreadsheets, it’s a reliable approach. We'll use the example of analyzing Landing Page performance, looking at Sessions vs. Transactions.

Step 1: Get Your Data from Google Analytics

Follow the steps from the previous section to export your data. We'll start with the "Landing page" report in GA4 (accessible under Reports > Engagement > Acquisition > Landing page). Be sure your report includes the Landing page dimension and the Sessions and Transactions metrics. A CSV download will work perfectly for this.

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Step 2: Clean and Prepare Your Data in Google Sheets

Open Google Sheets and import your downloaded CSV file by going to File > Import > Upload. Once it's loaded, you'll likely need to do a little housekeeping:

• Delete Extra Rows: GA exports often include a summary row at the top and a total row at the bottom. Delete these, as they will skew your chart's axes.
• Simplify Columns: You only need three columns for this chart: Landing Page (for labels), Sessions (X-axis), and Transactions (Y-axis). You can hide or delete the others to make it easier to work with.
• Check Data Types: Make sure your Sessions and Transactions columns are formatted as numbers, not text.

Step 3: Create the Scatter Plot

Now for the fun part. With your data cleaned up, creating the chart is just a few clicks away.

1. Select Your Data: Start by selecting the two numeric columns you want to plot. Click the column header for 'Sessions' (e.g., Column B), then hold down Ctrl (or Command on Mac) and click the column header for 'Transactions' (e.g., Column C).
2. Insert the Chart: With the columns selected, go to the Google Sheets menu and click Insert > Chart.
3. Choose the Right Chart Type: Google Sheets will likely guess a column or line chart by default. In the Chart editor pane that appears on the right, find the "Chart type" dropdown and scroll down to the "Scatter" section. Select "Scatter chart."

Just like that, you have a scatter plot! Each dot on the chart represents one of your landing pages, plotted according to its session and transaction count.

Step 4: Customize and Interpret Your Chart

A raw chart is good, but a well-labeled one is great. Use the "Customize" tab in the Chart editor to:

• Add Titles: Give your chart a clear title like "Landing Page Performance: Sessions vs. Transactions."
• Label Your Axes: Label the Horizontal (X) Axis as "Sessions" and the Vertical (Y) Axis as "Transactions."
• Add a Trendline: Under the "Series" section, you can check the "Trendline" box to see the overall correlation in your data. It helps visualize whether, on average, more sessions lead to more transactions.

You can now immediately see outliers. A point way up to the top left? That's a highly efficient page. A point way out to the bottom right? That's a high-traffic page that isn't pulling its weight in conversions. This is a solid, albeit manual, path to a powerful insight.

Method 2: Using AI and Natural Language for Instant Results

The manual method works. But it’s slow, repetitive, and completely static. If your data changes tomorrow, you have to do it all over again. This is where modern AI-powered analytics tools come in. Instead of a multi-step process involving exporting, cleaning, and chart-building, you can simply connect your Google Analytics account and ask a question in plain English.

Think of it as having a data analyst on your team. You don't tell an analyst to "export a CSV, open it, select columns B and C, insert a chart..." You just ask, "Can you show me a scatter plot of sessions versus transactions for our top landing pages?"

AI tools let you do precisely that. By connecting directly to your Google Analytics API, they can pull live data and build visualizations on command.

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How Natural Language Transforms This Workflow

Instead of the 10-20 minute manual process described above, the AI workflow looks like this:

1. Connect your Google Analytics account (usually a one-time, three-click process).
2. Type what you want to see into a prompt box.

That's it. Within seconds, the tool generates the chart for you, pulling the latest data directly from GA.

Example AI Prompts for Google Analytics Scatter Plots:

• Create a scatter plot of sessions vs transactions by landing page for the last 90 days.
• Show me total users vs average engagement time by traffic source as a scatter plot.
• Plot conversions against bounce rate for my top 20 pages using a scatter chart.

The Advantages of an AI-Powered Approach

This shift from manual "doing" to conversational "asking" brings some major benefits:

• Incredible Speed: What used to be a weekly or monthly reporting chore becomes a 30-second task. You get your insights almost as fast as you can think of the questions.
• Live, Real-Time Data: Because the tool is connected directly to your data source, the charts it creates are not static snapshots. They update automatically, so you're always looking at the freshest information without having to re-export.
• Seamless Exploration: Answering a question often leads to more questions. With AI, a follow-up is as easy as typing another message. You can fluidly move from your initial scatter plot to a new visualization by asking things like, "Okay, now show that same data as a bar chart" or "Drill down and only show me pages with more than 500 sessions." This empowers a more natural, curiosity-driven analysis.
• No Technical Skill Needed: You don't have to be a spreadsheet expert or remember where every setting is in the chart editor. If you can describe what you want to see, you can get the insight. This opens up data analysis to everyone on the team, not just the "data person."

Final Thoughts

Generating a scatter plot from your Google Analytics data moves you beyond surface-level metrics to see the important relationships that drive your performance. While GA doesn't build these charts for you, you can get it done either by manually exporting your data to a spreadsheet or by leveraging a modern AI analytics tool to generate them instantly with a simple request.

We built Graphed because we believe your time is better spent acting on insights, not wrestling with CSVs. We've automated the entire reporting process so you can get powerful analysis without the manual work. Just connect your Google Analytics account in a few clicks, then ask for the exact chart you need - like a live scatter plot or a full marketing dashboard - using simple English. Graphed translates your questions into ready-to-use visualizations, freeing you up to focus on growing your business.