How to Make an X Y Graph in Looker

An X Y graph is one of the quickest ways to see if two different metrics are related. Instead of guessing whether your increased ad spend is driving more sales, or if more website traffic is leading to higher conversion rates, an X Y graph maps out the relationship for you in a simple visual. This article will walk you through exactly how to build and customize one in Looker (or Looker Studio).

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

We'll cover the basics of choosing your data, the step-by-step process of creating the chart, and a few practical tips for making your visualization clear and insightful.

What is an X Y Graph (Scatter Plot)?

An X Y graph, also known as a scatter plot or scatter chart, visualizes the relationship between two numerical variables. Each dot (or marker) on the chart represents a single data point, with its position determined by its value on the horizontal X-axis and the vertical Y-axis.

By plotting these points, you can instantly spot patterns, correlations, and outliers that you'd almost certainly miss in a spreadsheet. It's the perfect tool for answering questions like:

• Does spending more money on a specific ad campaign result in more sales?
• Is there a relationship between the number of demos a sales rep gives and the number of deals they close?
• Do products with more customer reviews tend to have higher sales volumes?

Essentially, if you're trying to figure out if action "X" influences outcome "Y," a scatter plot is your best starting point.

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

When to Use an X Y Graph

While versatile, scatter plots are built for a specific job: showing correlation.

• Ideal Use-Case: You have two different numerical metrics and want to see how they move together. For instance, plotting Ad Spend (X) against Revenue (Y) for different campaigns can reveal which campaigns are most efficient.
• When Not to Use It: Avoid scatter plots for showing changes over time. For that, a line chart is a much better choice. If you're comparing a single metric across different categories (like sales per country), a bar chart is clearer and easier to read.

Preparing Your Data for a Scatter Plot

Before you jump into Looker, the quality and structure of your data are everything. A chart can only visualize the information it's given, so a little prep work goes a long way.

For a basic X Y graph, your dataset needs at least two numerical columns (known as measures in Looker). Each row in your data will become a single point on the graph.

Let's use a marketing campaign example. Your underlying data might look something like this:

Here, each campaign is a unique data point. Its Ad Spend will determine its horizontal position (X-axis) and its Total Conversions will determine its vertical position (Y-axis).

Step-by-Step Guide: Creating Your X Y Graph in Looker

With your data ready, building the graph in Looker is a straightforward process. Let’s walk through it.

Step 1: Get Started in an Explore

Everything in Looker begins at the Explore level. An Explore is an interactive data view that lets you select fields, apply filters, and build queries. Navigate to the Explore that contains the data you want to analyze (e.g., your Google Ads data, Shopify data, etc.).

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

Step 2: Select Your Measures and Dimensions

In the field picker on the left side of the Explore page, you'll see all your available dimensions (categorical data, like names or dates) and measures (numerical data, like counts or spend).

1. Find the two numerical measures you want to correlate. For our example, we'd select Total Ad Spend and Total Conversions.
2. (Optional but Recommended) Select a dimension to provide context. We would choose Campaign Name so we can see which dot belongs to which campaign. Your selected fields will appear on the right.

Step 3: Run the Query and Open Visualization Options

Click the Run button at the top right. Looker will query your database and return the results as a data table. Once you see the data, navigate to the Visualization pane to start building your chart.

From the visualization options, select the icon with scattered dots, which represents the Scatterplot.

Step 4: Configure the X and Y Axes

This is where you tell Looker which measure goes on which axis.

1. Click the Edit button to open the visualization options.
2. Navigate to the Plot tab.
3. In the X-axis dropdown, select the measure you want to use for the horizontal axis. In our case, this is Total Ad Spend.
4. In the Y-axis dropdown, choose the measure for the vertical axis, which would be Total Conversions.

Looker will automatically generate the scatter plot based on your selections. Each row from your data table will now be a point on your graph.

Step 5: Customize Your Graph

An unformatted chart is hard to read. Use Looker’s customization tabs (Plot, Series, X, Y, and Style) to make it clear and insightful.

Plot and Series Settings

• Point Style: On the Plot tab, you can change the shape and size of the points. Letting the radius of the points be determined by a third metric turns your scatter plot into a bubble chart. For example, you could make the size of each dot represent Return on Ad Spend (ROAS) so you can see cost, volume, and efficiency all in one view.
• Color Customization: Head to the Series tab to change the colors of your points. Looker will often default to a single color, but if you've included a dimension like Campaign Name, you can assign unique colors to different categories for easier comparison.

Axis Customization (X and Y Tabs)

• Axis Names: Go to the X and Y tabs to give your axes clear, descriptive names. Instead of total_ad_spend, use "Total Ad Spend ($)".
• Scale Type: Stick with a "Linear" scale type for most cases. However, if your data points are clustered in one small area but you have a few huge outliers, switching to a "Logarithmic" scale can make the pattern more visible.
• Gridlines: Add gridlines to make it easier for viewers to judge the values of individual points.

Style Tab and Trend Lines

The Style tab is where one of the most powerful features of a scatter plot lives: the trend line.

• Locate the Trend Line dropdown and select a type. "Linear" is almost always the right choice.
• A trend line shows the overarching correlation in your 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

Step 6: Review, Save, and Share Your Visualization

Take one last look at your scatter plot. Does it clearly answer your original question? Are the labels understandable? Once you're happy with it, you can save the chart as a "Look" (a saved report in Looker) or add it directly to a new or existing dashboard to monitor it over time.

Tips for Better Scatter Plots

Building the chart is one thing, making it truly useful is another. Here are a few final tips for leveling up your X Y graphs in Looker:

• Don't Overcrowd the Chart: If you have thousands of data points, a scatter plot can quickly become an unreadable blob. Use filters in your Looker Explore to narrow down the data to a specific time frame, product category, or region.
• Add Context with Reference Lines: Use the "Reference Lines" feature in the Y or X-axis tabs to add lines for averages, medians, or specific goals (like a target conversion rate). This helps you quickly see which points are above or below the benchmark.
• Label Important Outliers: If a few points are far away from the others, they're often the most interesting. Use chart settings to label these outliers so your team knows exactly which sales rep or marketing campaign is over- or under-performing.

Final Thoughts

Building an X Y graph in Looker is a powerful way to move from raw data to real business insights. By mapping two variables against each other, you can quickly discover relationships between your marketing spend, sales activities, and business outcomes without getting lost in endless rows of a spreadsheet.

If you find that navigating Looker's interface still takes more time than you’d like, you might appreciate our approach. We built Graphed because we believe anyone should get answers from their data without a steep learning curve. Instead of manually selecting measures, dimensions, and chart types, you can simply describe what you want in plain English — like "show me a scatter plot of total sales vs. ad spend by campaign" — and get an interactive, real-time chart in seconds.