How to Make a Scatter Plot in Power BI with AI

Trying to understand the relationship between two different business metrics is a core part of data analysis. For instance, how does your ad budget for a campaign affect sales for that campaign? Or how does website traffic influence the number of free trial sign-ups? This article will show you how to visualize these relationships using one of the most effective charts available: the scatter plot in Power BI, covering both the standard creation process and the faster, AI-powered method.

What is a Scatter Plot (and Why Should You Care)?

A scatter plot is a type of chart that displays values for two different variables on a single chart, represented by dots. One variable determines the dot's position on the horizontal axis (X-axis), and the other determines its position on the vertical axis (Y-axis). It's the perfect tool for seeing if one number moves in relation to another.

By mapping these points, you can quickly spot patterns or correlations in your data that would be nearly impossible to see in a spreadsheet. Imagine you run an e-commerce store and want to analyze your marketing efforts. You could use a scatter plot to answer questions like:

Do higher ad expenditures lead to more revenue? (Plot ad spend vs. revenue)
Does offering a bigger discount result in more items sold? (Plot discount percentage vs. units sold per transaction)
Do more website sessions from an ad campaign correlate with a higher number of checkouts? (Plot total sessions vs. total conversions)

Once you plot your data, you'll typically see one of three patterns:

Positive Correlation: As one variable increases, the other tends to increase. Dots will appear to flow from the bottom-left to the top-right. ([Example: more ad spend, more revenue])
Negative Correlation: As one variable increases, the other tends to decrease. Dots will appear to flow from the top-left to the bottom-right. ([Example: higher discounts, lower profit margin per item])
No Correlation: The dots are scattered randomly with no discernible pattern, suggesting the two variables don't affect each other. ([Example: daily temperature vs. number of website visits])

Seeing this pattern visually is much more impactful than staring at rows of numbers.

Creating a Scatter Plot in Power BI: The Standard Way

Building a scatter plot in Power BI is straightforward once you know where to click. It involves preparing your data, selecting the visual, and dragging your metrics into the right places.

Step 1: Get Your Data into Power BI

First things first, your data needs to be in Power BI. Whether you're connecting to an Excel file, a database, or a web service through the "Get Data" option, make sure the table you want to use is loaded into your model. For our example, let's assume we have a simple table of marketing campaign data with columns for Campaign Name, Ad Spend, and Revenue.

Step 2: Add the Scatter Chart Visual

With your Power BI report canvas open, look at the Visualizations pane on the right-hand side. Find the icon that looks like a set of scattered dots - this is the Scatter chart. Click it to add a blank scatter chart placeholder to your report canvas.

Step 3: Drag and Drop Your Fields

This is where the magic happens. With your blank scatter chart selected, look at the Fields pane (which shows your data tables). You now need to tell Power BI what data to show.

The main fields you'll work with are:

X-Axis: This is your independent variable - the metric you believe might be causing a change. In our example, this would be Ad Spend. Drag the Ad Spend field from your data table into this box.
Y-Axis: This is your dependent variable - the metric that you think is affected. For us, this is Revenue. Drag the Revenue field into this box.
Values: This is what determines the individual dots. By default, Power BI will plot a single dot representing the sum of all your ad spend and revenue. To see a dot for each campaign, drag your Campaign Name field into the "Values" box.

Once you do this, your chart will instantly transform from a single dot into a full scatter plot, with each dot representing a single marketing campaign. Now you can visually check for that positive or negative correlation we talked about earlier.

Taking Your Scatter Plot to the Next Level

A basic scatter plot is great, but Power BI offers additional features to uncover deeper insights from the same chart.

Using the 'Size' Field for a Third Dimension

Want to represent three data points at once? This is where the Size field comes in. It turns your scatter plot into what's often called a "bubble chart." The size of each dot is determined by the metric you drop here.

For example, you could drag a Conversions metric into the Size field. Now, you'll not only see the relationship between Ad Spend and Revenue, but you'll also see which campaigns generated the most individual conversions by how large their bubble is. A campaign with a big bubble and high revenue is a clear winner.

Using the 'Play Axis' for Animation

If your data includes a time element, like a date or month, you can use the Play axis to see how the relationship between your metrics has changed over time. Drag a date field into this box, and Power BI will add a timeline with a play button below your chart. Clicking play will animate the dots, showing you their positions month by month, helping you spot trends in an entirely new way.

Using AI to Create Scatter Plots in Power BI

The drag-and-drop method works well, but it requires you to know exactly which field goes into which box. Over the past few years, Microsoft has embedded powerful AI and natural language features into Power BI to speed up this process, letting you create visuals just by typing what you want to see.

Meet the Power BI Q&A Visual

The primary AI tool for this is the Q&A (Questions & Answers) visual. Instead of clicking and dragging, you give it a prompt in plain English, and it generates the corresponding chart for you. For people who don't want to dig through menus and field wells, this is a game-changer.

How to Use the Q&A Visual

Add the Q&A Visual: In the Visualizations pane, find the icon with a speech bubble and a cog, or simply double-click on any empty space on your report canvas. This will bring up a Q&A input box.
Ask Your Question: Start typing your analytics question into the box. Power BI will suggest terms from your data model to help you complete your prompt.

Start by typing: revenue by ad spend
Power BI will likely default to a bar or column chart. To change it, just add the chart type to your prompt: revenue by ad spend as a scatter chart
To break it down by campaign, just specify the level of detail: show total revenue by sum of ad spend by campaign as a scatter plot

Turn it into a Standard Visual: Once the Q&A visual displays the chart you want, you can click the icon in the top-right corner to convert it into a standard scatter chart visual. From there, you can customize it further using the formatting pane just like you would any other chart.

The Catch: When Does the AI Misunderstand?

While Power BI's Q&A feature is incredibly powerful, it's not foolproof. Its performance depends heavily on how clean and well-named your data is. For example, if you have columns named "Cost1" and "Sales_Final," the AI might struggle to understand that you mean "Ad Spend" and "Revenue." It can also get confused with very complex requests or messy data models.

Sometimes you need to guide it with synonyms or more detailed phrasing, which still involves a bit of a learning curve. For the average business user who hasn't been formally trained as a data analyst, hitting these roadblocks can be frustrating.

Final Thoughts

In this post, you learned not just what a scatter plot is and why it's so valuable for finding correlations, but also how to build one in Power BI using both the traditional drag-and-drop interface and the more modern, conversational Q&A feature. It's a fundamental chart for any serious data analysis.

We built Graphed because we believe the power of AI-driven analysis shouldn't be trapped behind the steep learning curve of complex tools like Power BI. If you loved the idea of creating charts just by asking questions but found yourself wishing it were even simpler and worked across all your marketing and sales tools - not just one report - then you'll feel right at home with us. We connect directly to tools like Google Analytics, Shopify, Facebook Ads, and Salesforce, allowing you to go from asking "show me my Facebook spend vs Shopify revenue" to seeing a live, interactive dashboard in about 30 seconds.