How to Make an X Y Graph in Google Analytics with AI

Ever look at your standard Google Analytics reports and feel like you're missing the real story? You see a list of popular pages, you see overall traffic numbers, but you can't quite connect the dots between two different metrics - like which high-traffic pages are actually good at converting visitors, or which marketing channels bring in the most engaged users. To see those relationships, you need an XY graph (also known as a scatter plot).

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

This article will show you exactly what an XY graph is and why it's a game-changer for analyzing your marketing performance. More importantly, we'll walk through how you can create them in seconds using AI, skipping the time-consuming process of manually exporting and wrestling with spreadsheets.

What Exactly Is an XY Graph (And Why Should Marketers Care)?

Ditching the old-school math class definition, an XY graph is simply a chart that shows the relationship between two different variables. One variable goes on the horizontal X-axis, and the other goes on the vertical Y-axis. Each dot on the graph represents a specific item - like a landing page, a country, or an ad campaign - and its position shows its value for both metrics.

Imagine you want to see the connection between sessions on your landing pages (X-axis) and the conversion rate for those pages (Y-axis). Each dot on the graph would be a landing page. A dot far to the right means the page gets tons of traffic. A dot near the top means it has a high conversion rate.

Suddenly, you can see patterns you'd never spot in a data table:

• The Workhorses: Dots in the top-right corner. These pages get lots of traffic and have high conversion rates. These are your all-stars.
• The Hidden Gems: Dots in the top-left corner. These pages have a great conversion rate but don't get much traffic. This is a huge opportunity - if you can drive more traffic to them, you could see amazing results.
• The "Traffic Traps": Dots in the bottom-right corner. Lots of traffic, but nobody's converting. These pages need attention. Why isn't anyone taking action? Is the call-to-action unclear? Is the page confusing?
• The Underperformers: Dots in the bottom-left corner. Low traffic and low conversions. You can probably ignore these for now and focus your energy elsewhere.

The beauty of an XY graph is that it turns raw data into a visual story, helping you instantly identify outliers, clusters, and opportunities that would otherwise be buried in spreadsheets.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Common Use Cases for an XY Graph with Google Analytics Data

An XY graph can unlock insights across every part of your marketing funnel. Once you know what to look for, you'll start seeing potential use cases everywhere. Here are a few practical examples to get you started:

Analyzing Landing Page Performance

This is the classic example we just walked through. It’s one of a kind because it helps you prioritize your optimization efforts.

• X-axis: Sessions
• Y-axis: Conversions (or Conversion Rate)
• What it tells you: Which popular pages need conversion optimization, and which high-converting pages need more promotion.

Evaluating Channel Efficiency

Are the channels that drive the most new users also the ones bringing in the most engaged users? This graph helps you understand the quality of traffic from your various channels (Organic Search, Paid Search, Social, etc.).

• X-axis: New Users
• Y-axis: Engagement Rate
• What it tells you: You might discover that a channel with fewer users actually delivers far more engaged visitors, prompting you to rethink your budget allocation.

Reviewing Content and Blog Performance

For content marketers, this chart helps separate the vanity metrics from the ones that matter. Is your most-viewed blog post actually keeping people's attention, or are they bouncing right away?

• X-axis: Views
• Y-axis: Average Engagement Time
• What it tells you: You can quickly find popular articles that aren’t engaging readers (and might need revamping) and niche articles that have a dedicated, highly-engaged audience.

Identifying Geographic Opportunities

If you have an e-commerce store or international audience, this can guide your expansion or ad-targeting strategy.

• X-axis: Users by Country
• Y-axis: Revenue by Country
• What it tells you: Find countries that drive a lot of revenue even with a smaller user base - these "hidden gem" markets are prime candidates for increased marketing spend. Conversely, you can identify high-traffic countries that aren’t buying, which may require you to investigate shipping costs, language barriers, or product-market fit.

The Old Way vs. The New AI Way

So, you're sold on the value of an XY graph. Now, how do you actually make one?

The Old-School Manual Method (Inside GA4 and Spreadsheets)

Traditionally, creating a custom XY scatter plot from your Google Analytics data involves a decent amount of manual labor. While GA4's "Explorations" section does offer a scatter plot chart, it can feel clunky and limited.

The more common workflow for most marketers looks like this:

1. Navigate to the right report in Google Analytics.
2. Adjust the date range and apply any necessary filters.
3. Export the data to a CSV file or Google Sheet.
4. Open the file and likely spend 10-20 minutes cleaning and organizing the data.
5. Finally, create a chart, select "scatter plot," assign your X and Y axes, and format everything to make it readable.

This process is not only tedious and takes up a good chunk of your afternoon, but it has a massive downside: the moment you finish, your report is already stale. The data is a static snapshot. If you want to see updated numbers next week, you have to do the whole song and dance all over again.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

The Modern AI Method (Instant Analysis)

Instead of wrestling with CSVs, the new approach uses AI to go from question to visualization in a matter of seconds. It works by connecting your Google Analytics account to an AI-powered analytics tool and then simply describing the chart you want in plain English.

Instead of clicking, exporting, and formatting, you just type a prompt. For the examples we discussed above, your "prompts" might look like this:

Show me an XY chart of GA4 landing pages with sessions on the x-axis and total conversions on the y-axis for the last 60 days.

Or for the channel analysis:

Create a scatter plot comparing new users and engagement rate by channel from Google Analytics this quarter.

Or for the geographic report:

I want to see a scatter plot of total users by country versus total revenue by country from my Google Analytics data.

The AI understands what you're asking for, queries the live data directly from your Google Analytics account, and instantly generates a clean, interactive visualization. No spreadsheets, no manual work, no outdated data. And even better, if that initial chart sparks a follow-up question, you can just ask it. For instance, you could follow up with "which of those pages in the top right quadrant are from organic search?" and get an instant answer.

Tips for Getting More From Your XY Graphs

Creating the chart is only the first step. The real value comes from interpreting it and acting on what you find.

1. Start with a Clear Question

Don't just create charts for the sake of it. Begin with a business question you want to answer. Are you trying to find your best-performing content? Are you looking for underutilized marketing channels? Having a goal in mind helps you focus on creating visualizations that lead to actual insights, not just more data.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

2. Hunt for the Outliers

The most interesting stories in an XY graph are often found in the outliers - the dots that are far away from the main cluster. An outlier could be a landing page that converts ten times better than anything else, or a blog post that got an explosive amount of traffic but had zero engagement. These extremes are where your biggest lessons and opportunities lie.

3. Combine GA4 with Your Other Data Sources

While Google Analytics data is powerful on its own, things get really interesting when you combine it with data from other platforms. Imagine plotting ad spend from Facebook Ads on the X-axis against Shopify sales on the Y-axis, with each dot representing a different campaign. That's how you truly measure ROI and see the entire customer journey, from ad click to final purchase.

Final Thoughts

An XY graph is more than just another chart, it's a powerful tool for discovering hidden relationships and making smarter decisions with your Google Analytics data. By moving away from time-consuming manual exports and towards instant AI-driven analysis, you can spend less time wrangling data and more time acting on the insights that actually grow your business.

We built Graphed to solve this exact problem. Reporting hell is where marketers’ great ideas end up when they have to spend their week manually creating reports just to figure out what happened last week. By securely connecting all of your data sources - like Google Analytics, Shopify, and Facebook Ads - in one place, we allow you to get answers and create live, interactive dashboards just by asking questions in plain English. Now you get back precious time for what truly matters: making meaningful decisions that win more customers over.