How to Make a Scatter Plot in Google Sheets

Trying to figure out if your marketing spend is actually leading to more sales, or if there's a connection between your website traffic and user sign-ups? A scatter plot is the perfect tool for the job, and you don’t need complex software to create one. This guide will walk you through exactly how to make a scatter plot in Google Sheets to visualize the relationship between two different variables, customize it for clarity, and understand the story your data is telling.

What is a Scatter Plot (and When Should You Use One)?

A scatter plot, also known as a scatter graph or scatter chart, uses dots to represent the values of two different numeric variables. The position of each dot on the horizontal (X-axis) and vertical (Y-axis) axes indicates the values for an individual data point. Its primary purpose isn’t to track a metric over time like a line chart, but rather to show a relationship or correlation between two things.

Think of it as a way to answer questions like, "Does this affect that?"

Here are a few common scenarios where a scatter plot is your best option:

• Marketing Analysis: Is there a relationship between your daily ad spend on Facebook and the number of conversions you get on your website?

• Sales Performance: Do sales reps who make more calls per week also close more deals?

• E-commerce Strategy: How does changing the price of a product affect the number of units sold each day?

• Website Analytics: Is there a correlation between the time users spend on a page and their bounce rate?

By plotting your data points, you can quickly see patterns emerge. The dots might cluster in a way that suggests a connection, helping you make smarter, more data-informed decisions.

Preparing Your Data for a Scatter Plot

Before you can build your chart, your data needs to be structured in a specific way. The good news is that it’s incredibly simple. All you need are two columns right next to each other, both containing numeric data. A scatter plot cannot be made with text categories, it compares numbers against numbers.

Step 1: Identify Your Independent and Dependent Variables

First, you need to understand which variable is which:

• Independent Variable (X-axis): This is the variable you have some control over or that you believe might be influencing the other one. It goes on the horizontal axis. In our marketing example, "Ad Spend" would be the independent variable because you decide how much to spend.

• Dependent Variable (Y-axis): This is the variable you're observing or measuring to see if it changes in response to the independent variable. It goes on the vertical axis. In the same example, "Website Conversions" would be the dependent variable because you're watching to see how it reacts to changes in ad spend.

Step 2: Set Up Your Columns in Google Sheets

Organize your data in two columns with clear headers. It's conventional to put the independent variable (X-axis) in the left column and the dependent variable (Y-axis) in the right. This often helps Google Sheets guess the chart setup correctly.

Here’s what a sample dataset might look like for analyzing the relationship between the number of tutorials published on a blog and the organic traffic it receives:

Make sure your numbers are formatted as numbers, not text, and that there are no empty cells within your data range.

How to Create a Scatter Plot in Google Sheets: A Step-by-Step Guide

Once your data is properly formatted, creating the chart itself only takes a few clicks.

Step 1: Select Your Data

Click and drag your cursor to highlight the data you want to visualize. Be sure to include the header row, as Google Sheets will use this information to automatically label your axes.

Step 2: Insert the Chart

With your data selected, navigate to the menu at the top of the screen and click Insert > Chart. Google Sheets will insert a chart onto your worksheet. It will try to guess what kind of chart you want, which is often a Line Chart or Bar Chart by default.

Step 3: Choose the Scatter Chart Type

The Chart Editor sidebar should appear on the right side of your screen. If Sheets didn't automatically select a scatter plot, it's easy to change.

1. In the Setup tab of the Chart Editor, find the "Chart type" dropdown menu.

2. Scroll down until you find the "Scatter" section and choose "Scatter chart."

Your chart will instantly update to show your data as a series of dots.

Step 4: Verify Your Axes and Data Range

Still in the 'Setup' tab, double-check that Google Sheets has correctly assigned your X-axis and Y-axis. The independent variable ("Number of Articles Published") should be on the X-axis, and the dependent variable ("Monthly Organic Visitors") should be on the Y-axis. If they're mixed up, you can click on each field and select the correct data range (column) for it.

Customizing Your Scatter Plot for Clarity and Impact

A basic scatter plot is a good start, but a few simple customizations can transform it from a cloud of dots into a compelling insight. Spend a couple of minutes in the "Customize" tab of the Chart Editor to make your chart easier to understand.

Adding a Trendline

This is arguably the most powerful feature for interpreting a scatter plot. A trendline is a single line that best fits the data, showing the general direction and strength of the relationship between your two variables.

1. Click on the Customize tab in the Chart Editor.

2. Click to expand the Series dropdown.

3. Scroll down and check the box labeled Trendline.

A line will appear on your chart, visually representing the correlation. For most business cases, the default "Linear" type is exactly what you need.

Editing Titles and Axis Labels

Never leave your chart with generic titles. Clear labels are essential for anyone trying to understand your data.

1. Expand the Chart & axis titles section in the 'Customize' tab.

2. For "Chart title," give it a descriptive name, like "Relationship Between Blog Articles and Organic Traffic."

3. Under "Horizontal axis title" and "Vertical axis title," make sure the labels from your column headers are present and clear. You can type in new ones if needed.

Adjusting Colors and Point Styles

Under the Series section, you can change the visual style of your data points and trendline. You can adjust the color to match your brand, change the size of the dots to make them more visible, or even modify their shape (from a circle to a star, for instance).

Modifying Axis Scales

Sometimes, your data may be clustered in one small part of the chart, leaving a lot of empty space. You can fix this by adjusting the axis scale.

1. Expand the Horizontal axis or Vertical axis section.

2. Enter new "Min" and "Max" values to zoom in on the range where your data actually lives. This can make the trend easier to see.

How to Interpret Your Scatter Plot: Finding the Story in the Dots

Once your chart is created and customized, it's time to understand what it's telling you. Look at the general direction of the data points and the slope of your trendline.

Positive Correlation

If your trendline slopes upward from left to right, you have a positive correlation. This means that as your independent variable (X-axis) increases, your dependent variable (Y-axis) also tends to increase. In our example, more published articles are associated with more organic visitors. It's a good sign!

Negative Correlation

If your trendline slopes downward from left to right, you have a negative correlation. As the independent variable increases, the dependent variable tends to decrease. For example, a plot might show that as product discount percentage increases, profit margin per sale decreases.

No Correlation

If the dots are scattered all over the chart with no discernible pattern and the trendline is mostly flat, there's likely no correlation between the two variables. This is also a useful insight - it tells you that changing one variable probably won't have any predictable effect on the other.

A Quick Word on Correlation vs. Causation: Something important to remember is that a scatter plot shows a correlation, not necessarily causation. Just because two things move together doesn't mean one is causing the other. For instance, ice cream sales and shark attacks are positively correlated, but that’s because both increase in the summer - ice cream sales don't cause shark attacks. Always use context and business knowledge to interpret your findings.

Final Thoughts

Scatter plots are an incredibly effective visual tool for discovering relationships in your business data. With Google Sheets, you can move from a simple spreadsheet to a powerful analysis in just a few minutes, turning raw numbers into actionable insights about what drives your marketing, sales, and overall business performance.

Manually preparing and formatting a scatter plot in Google Sheets is fairly simple for one-off analyses, but it can quickly become tedious when you need to combine data from multiple platforms, like your ad accounts, CRM, and e-commerce store. We built Graphed to remove this friction entirely. Instead of pulling CSVs and organizing columns, you connect your data sources once and simply ask for what you need in plain English - for example, "show me a scatter plot of my Google Ads spend vs. my HubSpot deal value this quarter." We instantly generate real-time, interactive dashboards so you can get straight to the insights, not the setup.