What Other Kinds of Visualizations Could You Create in Tableau?

Your team knows Tableau is great for making standard bar graphs and line charts, but using it only for the basics is like owning a sports car and never taking it out of first gear. To tell a compelling story with your data, you need to go beyond the defaults. This guide introduces six powerful, less-common visualizations you can create in Tableau to unlock deeper insights and make your dashboards more effective.

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Beyond the Pie: Creating a Donut Chart

A donut chart is essentially a pie chart with a hole in the middle. Why bother? That center space is perfect for displaying a key total or KPI, adding important context without taking up extra dashboard real estate. It's cleaner, more modern, and presents data in a more focused way by framing a single, important number with its component parts.

Building Your Donut Chart in Tableau

Creating a donut chart requires a clever little trick using a dual-axis chart. Let's imagine you want to visualize website traffic by source (e.g., Organic, Paid, Direct).

1. Drag the "Number of Records" field to the Rows shelf twice. This creates two distinct Marks cards on the left panel, one for each instance.
2. In the Marks panel, change the chart type for the first "Number of Records" Marks card to Pie.
3. Drag your category dimension (in this case, "Traffic Source") onto the Color tile and your measure ("Sessions") onto the Angle tile for this same Marks card. You'll now have a standard pie chart.
4. Next, go to the second "Number of Records" Marks card. Change its chart type to Circle and remove any fields from its Color and Angle tiles. You should just have a grey circle.
5. On the Rows shelf, right-click the second "Number of Records" pill and select Dual Axis.
6. You'll see the grey circle overlaid on your pie chart. Now, simply use the color formatting to make the circle white (or match your dashboard background) and use the Size slider to adjust its size, creating the donut "hole."
7. Finally, to add the total number of sessions in the middle, drag your "Sessions" measure to the Label tile on the "Circle" Marks card. Your donut chart is complete!

Visualizing Hierarchy with Treemaps

When you have hierarchical data - like product categories and sub-categories - a treemap is far more insightful than a series of bar charts. Treemaps use a series of nested rectangles where the size of each rectangle represents its value, making it instantly clear which categories are the most significant. They are brilliant for seeing the relative contribution of different parts to a whole.

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Building Your Treemap in Tableau

Suppose you're an e-commerce manager and want to see your total sales broken down by product category and then by individual product.

1. Drag your primary dimension ("Product Category") and your secondary dimension ("Product Name") to the Label tile on the Marks card.
2. Drag your measure ("Sales") to the Size tile. Tableau will likely default to a packed bubble chart.
3. In the drop-down menu on the Marks card, change the chart type from Automatic to Treemap.
4. Tableau automatically creates the treemap structure. To make it easier to read, drag your primary dimension ("Product Category") to the Color tile. This will color-code the boxes by their main category, making it simple to distinguish "Apparel" from "Electronics" at a glance.

You can now immediately see not only which categories drive the most revenue but also which specific products within those categories are your top performers.

Tracking Financials and Funnels with Waterfall Charts

A waterfall chart is the best way to show how a starting value is increased or decreased by a series of sequential events. It's commonly used in financial reporting to visualize a profit and loss statement, but it’s also incredibly effective for analyzing marketing funnels or changes in your customer base over time.

Building Your Waterfall Chart in Tableau

Building a waterfall chart involves a bit more setup but is well worth the effort. Let's see how your subscriber count changed over a quarter.

1. First, organize your data. You'll need a column for the categories of change ("Starting Subscribers," "New Signups," "Upgrades," "Churn") and another for their values (make sure churn is a negative number, like -500).
2. Drag your categories of change to the Columns shelf.
3. Create a calculated field for the negative values of your measure. For a measure called "Subscriber Change," the formula would be - [Subscriber Change]. Let's name this "Negative Subscriber Change."
4. Drag this new calculated field to the Size tile on the Marks card.
5. Change the chart type on the Marks card to Gantt Bar.
6. Right-click your "Subscriber Change" measure on the Data pane and select Create > Calculated Field.... Create a running total calculation, like RUNNING_SUM(SUM([Subscriber Change])).
7. Drag this new running total calculated field onto the Rows shelf.
8. Finally, drag your original "Subscriber Change" measure to the Color tile. Edit the colors so that positive changes (New Signups) are green and negative changes (Churn) are red. Now you have a clear, step-by-step visual of your subscriber journey.

Finding Trends in a Sea of Numbers with Heat Maps

A heat map is a table that uses color intensity to represent values. It excels at drawing the viewer's eye to high-concentration areas or "hotspots" in a dense dataset. It's perfect for quickly identifying patterns or anomalies that would get lost in a standard spreadsheet.

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Building Your Heat Map in Tableau

Let's say you want to find the best day of the week and hour of the day to send a marketing email based on open rates. A heat map makes the answer obvious.

1. Drag the "Day of the Week" dimension to the Columns shelf.
2. Drag the "Hour of the Day" dimension to the Rows shelf. You'll now have a grid.
3. Next, find your "Email Open Rate" measure and drag it to the Color tile on the Marks card.
4. Tableau will likely default to a highlight table, but to make it a true heat map, change the Marks card dropdown from Automatic to Square. This fills each cell completely with color.
5. To add the specific numbers back in, drag your "Email Open Rate" measure to the Label tile.

You can immediately see the brightly colored cells indicating the day/time combination with the highest open rates, guiding your campaign scheduling instantly.

Seeing the Spread with a Box and Whisker Plot

A box and whisker plot, or box plot, shows the distribution of a dataset. It visualizes the median, quartiles, and outliers all in one compact chart. This is fantastic when you're less interested in a simple average and more interested in the range and consistency of your data - for instance, when comparing the performance of two different ad campaigns.

Building Your Box Plot in Tableau

Imagine you ran two versions of a landing page (A and B) and want to compare daily conversion rates for each.

1. Drag your primary dimension ("Landing Page Version") to the Columns shelf.
2. Drag your measure ("Daily Conversion Rate") to the Rows shelf. You'll likely see two dots representing the averages.
3. For this to work, you need to show the distribution of all your data points. Drag "Landing Page Version" from the Columns shelf to the Marks card.
4. In the toolbar, find the "Show Me" button and select the Box-and-Whisker Plot option.
5. Tableau does the heavy lifting for you, transforming your points into a box plot. Hover over the plot to see the median, upper and lower hinges (quartiles), and the whiskers that show the range. Any dots outside the whiskers are outliers.

This reveals much more than a simple bar chart. Maybe Landing Page B has a higher average conversion rate, but its box plot is much wider, indicating its performance is inconsistent. Landing Page A, while slightly lower on average, might have a much tighter distribution, making it the more reliable choice.

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Tracking Against Quotas with a Bullet Graph

When you need to measure a value against a target, a bullet graph is far better than a simple gauge or bar chart. It packs a lot of context into a small space by showing a primary measure, a target, and performance ranges (like poor, average, good) all in one.

Building Your Bullet Graph in Tableau

Let's use a common example: tracking a sales rep's monthly sales against their quota.

1. Drag your dimension ("Sales Rep") to the Rows shelf.
2. Drag your performance measure ("Monthly Sales") to the Columns shelf. This creates a basic bar chart.
3. From the "Show Me" menu in the toolbar, select the bullet graph option.
4. Tableau helps here by creating placeholders where your target goes. If you have "Sales Quota" as another measure in your data pane, you can drag that into the detail where "Add a reference line, constant..." is noted. You will now see a vertical line representing the quota on each rep's bar.
5. In the same way, Tableau adds bands for different performance tiers (i.e., 'Poor' might be 0-50%, "Satisfactory" might be 50%-75%, and "Good" 75%-100% of the target). You can edit these gray-shaded bands on the axis by right-clicking on it and clicking on "Edit Reference Line… > "Distribution".

This allows anyone viewing the chart to instantly see not just how much a rep sold, but how that performance compares to their goal and the benchmarks for good performance.

Final Thoughts

Mastering Tableau is about picking the right chart for the job to illuminate your data and guide decisions. Getting comfortable with treemaps, waterfall charts, and heat maps moves you from simply showing numbers to telling compelling stories that drive action.

Of course, becoming proficient with these visualizations takes practice. Sometimes you just need the answer to a business question without spending hours tinkering to build the perfect report. That's exactly why we built Graphed. We connect directly to your marketing and sales platforms, allowing you to ask questions in plain English and get back live dashboards and insights in seconds, automatically choosing the best visualization for your data so you can focus on strategy, not chart settings.