Graphed LogoGraphed
Login

How to Make a Combo Chart in Tableau with AI

Cody Schneider•

Creating a combo chart is a fantastic way to compare two different types of data on a single visualization, like sales volume in bars and profit margin as a line. This article will walk you through exactly how to build a dual-axis combination chart in Tableau, step-by-step. We will also look at how newer AI-powered tools are changing the game and making this process much faster.

What is a Combo Chart, and When Should You Use One?

A combo chart, officially known in Tableau as a "dual-axis combination chart," combines two different chart types into one. The most common combination is a bar chart and a line chart. The real power here lies in the dual-axis feature, which means your chart has two separate Y-axes — one on the left and one on the right. This allows you to plot two measures that have completely different scales.

So, when is this useful? Imagine you want to see if your monthly ad spend is leading to more website traffic. Ad spend is measured in dollars (e.g., $10,000), while traffic is measured in sessions (e.g., 50,000). If you put these on a single axis, the $10,000 ad spend would barely be visible next to the towering 50,000 sessions. A combo chart solves this by giving each measure its own axis to scale properly, letting you see the relationship between the two clearly.

Here are a few classic examples where a combo chart shines:

  • Sales and Profit Margin: Show total sales with bars and the profit percentage with a line. This helps you spot if high-selling months also have healthy profit margins.

  • Website Sessions and Conversion Rate: Track your monthly website traffic using bars and overlay your conversion rate as a line. You can quickly see if a dip in traffic also led to a lower conversion rate.

  • Units Sold and Average Discount: Analyze the number of products sold (bars) against the average discount percentage (line) to understand how discounts are impacting sales volume.

Essentially, if you need to compare two different measures with different units (like dollars vs. percentages or counts vs. ratios) over a period of time, a combo chart is your best friend.

The Traditional Way: Building a Combo Chart in Tableau Step-by-Step

Tableau is incredibly powerful, but its interface can be a little intimidating if you're just starting out. Let's break down the process of creating a standard combo chart - sales by bars and profit ratio by line - into manageable steps. For this example, we’ll use Tableau's "Sample - Superstore" dataset that comes with the software.

Step 1: Get Your First Measure and Dimension on the View

First, connect to the Sample - Superstore data. In the Data pane on the left, you'll see your Dimensions and Measures.

  • Drag Order Date from Dimensions onto the Columns shelf. By default, it will show up as YEAR(Order Date). Right-click on it and choose Month (the second month option, displayed as "May 2020," to get a continuous time series).

  • Drag Sales from Measures onto the Rows shelf.

Tableau will automatically create a line chart showing total sales over time. Good start!

Step 2: Add Your Second Measure

Now, we need to add our second measure, the Profit Ratio. You won’t see "Profit Ratio" in the measures list by default, so we'll have to create it.

  • Right-click in a blank space in the Data pane and select Create Calculated Field.

  • Name the field "Profit Ratio".

  • Enter the formula: SUM([Profit]) / SUM([Sales])

  • Click OK. You've just created a new measure!

  • Now drag your new Profit Ratio measure from Measures onto the Rows shelf, placing it to the right of the SUM(Sales) pill.

You’ll now see two separate line charts, one stacked on top of the other.

Step 3: Create the Dual Axis

This is where the magic happens. We need to tell Tableau to combine these two charts using a second vertical axis.

  • On the Rows shelf, right-click the Profit Ratio pill.

  • In the dropdown menu, select Dual Axis.

Your charts will now be merged into a single view. The Marks card on the left will have changed, showing tabs for "All," "SUM(Sales)," and "Profit Ratio," which allows you to edit each part of the chart independently. Don't worry if it looks a bit messy right now, we'll fix that next.

Step 4: Change the Mark Types

Right now, both measures are being displayed as a line (or maybe circles). We need to change one to bars and keep the other as a line.

  • In the Marks Card, click on the tab for SUM(Sales).

  • Click the dropdown menu that currently says "Automatic" and select Bar. Your sales data will now be displayed as vertical bars.

  • Next, click on the tab for Profit Ratio in the Marks card. Your profit ratio data should still be a line by default, but if it changed, just set the Mark Type specifically to Line here.

You're almost there! You now have a combo chart with bars for sales and a line for profit ratio.

Step 5: Clean Up and Formatting

This last step is all about making your chart easy to read. Let's adjust the colors and axis labels.

  • Adjust Axis Names: Your Y-axes are currently labeled "Sales" and "Profit Ratio." Those are clear, but you can right-click any axis and select "Edit Axis" to change the title if you wish.

  • Adjust Colors: On the Profit Ratio Marks card, click "Color" to change the line's color to make it stand out. You can do the same for the bars on the SUM(Sales) Marks card. Pick contrasting colors that are easy to distinguish.

  • A Note on Synchronizing Axes: You might see an option to "Synchronize Axis." For this chart, do not synchronize them. Your sales are in thousands of dollars, and your profit ratio is a small percentage. Synchronizing would flatten your profit ratio line completely. This option is only useful when both measures share a very similar scale and unit of measurement.

With a little formatting, you’ll have a clean, professional-looking combo chart that clearly shows the relationship between your monthly sales and profit ratio.

The AI-Powered Alternative: Is There an Easier Way?

The step-by-step process in Tableau is logical, but it involves quite a few clicks, menu navigation, and knowing what a "Dual Axis" or "Mark Type" is. For many marketers, founders, or sales managers, becoming a Tableau expert isn't realistic. The learning curve is substantial, and people often spend hours on courses just to build foundational visualizations.

This is where AI data analysis tools are fundamentally changing how we approach reporting. Instead of manually building charts through a visual interface, you can simply ask for what you need using plain English. Think about it: rather than performing the five steps we just walked through, you could type a prompt like this:

“Create a combo chart showing total sales as bars and profit ratio as a line, broken down by month over the past two years.”

An AI-powered tool can interpret this request, perform the necessary calculations (including creating the profit ratio on the fly), and generate the final visualization for you in seconds. This isn't just about saving a few minutes, it's about making data accessible to everyone on your team, regardless of their technical skill level.

Why an AI Approach Works Better

Relying on natural language commands to build charts offers several powerful advantages over the traditional method.

1. It Practically Eliminates the Learning Curve

Business intelligence used to be locked away, accessible only to those who spent the requisite 80 hours mastering a tool like Power BI or Tableau. An AI layer removes that dependency. If you can ask a question, you can analyze data. You no longer need to know the specific technical jargon or where to click. Even your most junior team member can start digging into sales performance or campaign data, fostering a more data-driven culture across the entire organization.

2. Frees Up Time from Manual Reporting

Consider the typical analytics workflow for marketing teams: on Monday, you download several CSV files. Then you spend hours cleaning them up in Excel to build some basic charts for a meeting on Tuesday. Inevitably, follow-up questions come up, sending you back to a spreadsheet to answer them on Wednesday. Half the week is gone just managing basic reporting.

With data sources connected and an AI interface on top, that entire process disappears. Reports and dashboards update in real-time, and those follow-up questions can be answered live during the meeting — just by asking a question.

3. Encourages Deeper Data Exploration

When you look at a chart, it naturally sparks new questions. In our combo chart example, you might see a month where sales were high but profit ratio plummeted. In Tableau, investigating this would mean more dragging, dropping, and filtering. You might apply a "Sub-Category" filter to see what's driving the drop.

With an AI tool, this drill-down becomes a simple conversation. You just ask, “Show me the profit ratio for December by product sub-category.” An answer appears instantly. This back-and-forth makes data analysis feel less like a chore and more like a fluid brainstorming session with a data analyst, allowing you to follow your curiosity and uncover insights you might have otherwise missed.

Final Thoughts

Combo charts are a powerful tool for comparing different measures on a single visualization, and mastering how to build them in Tableau is a valuable data analysis skill. The method involves combining measures on a dual-axis, adjusting mark types, and a bit of formatting to make it all clear and understandable.

At Graphed, we felt this manual process was a huge time-sink that kept teams from focusing on the actual insights. We've built an AI data analyst that allows you to connect all your sources — from Google Analytics and Shopify to Salesforce and Facebook Ads — and simply ask for the reports you need in plain English. Instead of learning a complex new software, you just chat with your data and get real-time dashboards and answers in seconds, empowering your entire team to make smarter decisions without the reporting busywork.