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How to Make a Scatter Plot in Google Sheets with ChatGPT

Cody Schneider•

A scatter plot is one of the most effective ways to see if a relationship exists between two different things, like whether your ad spending actually leads to more sales. Creating one in Google Sheets is fairly straightforward, but you can get stuck figuring out what data to use or what the finished chart actually tells you. This guide will walk you through building a scatter plot in Google Sheets from start to finish and show you how to use ChatGPT as a brainstorming partner to speed up the process and uncover more meaningful insights.

What is a Scatter Plot? (And Why You Should Use One)

At its core, a scatter plot uses dots to represent the values for two different variables. One variable determines the dot’s position on the horizontal axis (the x-axis), and the other determines its position on the vertical axis (the y-axis). By plotting all your data points this way, you can visually inspect the pattern of the dots to see if there's a connection between the two variables.

It's a fantastic tool for answering questions like:

  • Does increasing our ad spend lead to more revenue?

  • Do sales reps who make more calls also close more deals?

  • Is there a relationship between a blog post’s length and how much traffic it gets?

  • Do customers who buy one product tend to buy another specific product?

The pattern the dots form can reveal different types of relationships:

  • Positive Correlation: The dots slope upwards from left to right. As one variable increases, the other variable also tends to increase. (Example: More study time is associated with higher test scores).

  • Negative Correlation: The dots slope downwards from left to right. As one variable increases, the other variable tends to decrease. (Example: Higher product price is associated with lower sales volume).

  • No Correlation: The dots are scattered randomly with no clear pattern. The two variables don’t seem to be related at all. (Example: The daily temperature and the number of website visitors).

Scatter plots are also excellent for spotting outliers - data points that fall far outside the main cluster of dots. These outliers often represent something unusual that’s worth investigating.

Getting Your Data Ready for a Scatter Plot

Before you can make a chart, you need clean, well-structured data. For a scatter plot in Google Sheets, all you need are two columns of numerical data. Each row should represent a single instance or observation where you have a value for both variables.

Let's use a common marketing scenario. Imagine you want to see if there's a connection between your monthly Facebook Ads spending and the number of conversions (e.g., sign-ups or purchases) you get from your website. Your data should be organized in two columns, like this:

Month,Facebook Ads Spend ($),Website Conversions

Jan, 2500, 150 Feb, 3200, 185 Mar, 1800, 110 Apr, 4000, 240 May, 4500, 260 Jun, 3800, 215 Jul, 5000, 310 Aug, 2200, 140 Sep, 4800, 290 Oct, 6000, 350 Nov, 7500, 420 Dec, 7000, 390

Here, the “Facebook Ads Spend” will be our x-axis variable (called the independent variable), and “Website Conversions” will be our y-axis variable (the dependent variable), as we hypothesize that conversions depend on ad spend. Make sure your columns contain only numbers, without extra symbols or text that could confuse Google Sheets.

How to Create a Scatter Plot in Google Sheets (The Manual Way)

Once your data is set up, building the chart takes just a few clicks. Follow these steps:

1. Select Your Data

Click and drag your mouse to highlight the two columns containing your numerical data. In our example, you would highlight the "Facebook Ads Spend" and "Website Conversions" columns, including the headers.

2. Insert the Chart

With your data selected, navigate to the menu bar at the top and click Insert > Chart. Google Sheets will automatically analyze your data and suggest a chart type. Sometimes it guesses right, but often it might default to a line or bar chart.

3. Choose the Scatter Chart Type

If Google Sheets didn’t automatically create a scatter plot, don’t worry. The Chart editor pane will appear on the right side of your screen. Under the "Setup" tab, find the "Chart type" dropdown menu. Scroll down until you find the Scatter chart option and select it.

Voila! You now have a basic scatter plot visualizing your data.

4. Customize Your Chart a Little

A barebones chart isn't very useful. It's crucial to add titles and labels so anyone looking at it understands what they're seeing. In the Chart editor, switch from the "Setup" tab to the "Customize" tab.

  • Chart & axis titles: Click this section to give your chart a descriptive title, like "Relationship Between Ad Spend and Conversions." You can also add titles for your Horizontal axis ("Monthly Facebook Ads Spend") and Vertical axis ("Website Conversions").

  • Series: Here, you can change the color and size of the dots to match your branding or make them easier to see.

Proper labels turn a confusing cloud of dots into a clear, professional visual that tells a story.

Speeding Up the Process with ChatGPT

This is where things get interesting. While ChatGPT can't log into your Google Sheets and click buttons for you, it can act as a data assistant to help you prepare, analyze, and interpret your work - often saving you a ton of time and mental energy.

1. Brainstorming Correlations to Analyze

Sometimes the hardest part is knowing where to start. You might be sitting on a mountain of data from Google Analytics, Salesforce, or your ad platforms, but you're not sure which relationships are worth exploring.

Describe your available data to ChatGPT and ask for suggestions.

Example Prompt:

"I'm a marketing manager with access to the following monthly data points from different platforms: Google Analytics sessions, time on page, bounce rate, Facebook Ads clicks, ad impressions, ad spend, CRM deals created, and email subscribers. Suggest 3 interesting relationships I could investigate with a scatter plot to find valuable business insights."

ChatGPT might come back with ideas like:

  • Ad Spend vs. Deals Created: To see if there's a direct link between marketing budget and sales pipeline growth.

  • Website Sessions vs. Email Subscribers: To learn if higher website traffic correlates with more successful lead generation.

  • Time on Page vs. Bounce Rate: To determine if more engaging content (higher time on page) leads to users abandoning the site less often.

This helps you focus your analysis on questions that are actually relevant to your business goals.

2. Cleaning and Formatting Data Instructions

Raw data exports are often messy. You might have currency symbols, commas, or weird date formats that prevent Google Sheets from treating the values as numbers. Instead of hunting for the right formula on Google, you can just ask ChatGPT.

Example Prompt:

"In my Google Sheet, Column B has values like '$5,430.75' entered as text. What formula can I use in another column to convert these into a simple numerical format like 5430.75 so I can use it in a chart?"

ChatGPT would likely provide a formula like this:

=VALUE(SUBSTITUTE(B2, "$", ""))

It can even explain what the formula does: the SUBSTITUTE function removes the dollar sign, and the VALUE function converts the resulting text string into a number. This turns a frustrating data-cleaning task into a quick copy-and-paste solution.

3. Interpreting Your Scatter Plot

So you've made your chart. You see a pattern of dots. Now what? Describing the visual to ChatGPT can help you put its meaning into words and think about the next steps.

Example Prompt:

"I created a scatter plot showing monthly ad spend on the x-axis and total sales on the y-axis. The dots form a clear line going from the bottom-left to the top-right corner. There's one dot way up at the top, far above the others. It represents a month where we had low ad spend but unusually high sales. How should I interpret this chart?"

ChatGPT can help you frame the interpretation:

  • It would confirm that the primary pattern is a strong positive correlation, suggesting that as you spend more on ads, sales tend to increase.

  • It would flag the stray dot as an outlier and suggest investigating what else happened that month. Did a blog post go viral? Was there a big PR mention? That outlier could hold the secret to a highly efficient growth tactic that isn't related to paid ads.

Crucially, you could also prompt it, "Explain the difference between correlation and causation for this chart." It would remind you that just because ad spend and sales move together doesn't definitively prove that one causes the other, which is a vital concept in data analysis.

Taking It Further: Advanced Scatter Plot Tips

Once you've mastered the basics, you can add more layers to your analysis directly within Google Sheets.

Add a Trendline

A trendline is a single line that best fits the data summary of your scatter plot, making the relationship even clearer. In the Chart editor > Customize > Series section, tick the "Trendline" checkbox. This will draw a line through your dots, visually representing the correlation. If it slopes up, it's a positive trend, if it slopes down, it's negative.

Customize Dot Colors by Category

What if you wanted to compare data from different sources? For instance, you could plot ad spend vs. conversions for both Facebook Ads and Google Ads on the same chart. You would structure your data with three columns: "Ad Channel," "Ad Spend," and "Conversions." When you create the chart, Google Sheets will use a different color for each channel's dots, allowing you to instantly compare the performance of each.

Final Thoughts

Scatter plots turn confusing spreadsheet rows into clear visual stories, revealing relationships that can guide smarter business decisions. The process of building them in Google Sheets is simple, and by using ChatGPT as an analytical partner, you can quickly move from raw data to finding ideas, cleaning your numbers, and understanding what it all means.

While using these tools together streamlines analysis, the reality is that gathering, cleaning, and reporting on data from a dozen different marketing and sales platforms remains a massive chore. As easy as it is to make a single chart, combining data from Google Analytics, Salesforce, Shopify, and various ad platforms to build a comprehensive dashboard can take hours. At Graphed we solve this by making the entire process conversational. You just connect your data sources once, then ask for the charts and dashboards you need in plain English. We turn hours of a manual reporting grind into a 30-second task, allowing you to get real-time answers and insights instantly, without ever having to wrestle a spreadsheet again.