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Can Tableau Have Multiple Sets in a View?

Cody Schneider••9 min read

The short answer is a resounding yes, you absolutely can use multiple sets in a single Tableau view. In fact, doing so is one of the keys to unlocking deeper, more specific insights from your data. This article will walk you through what sets are, why you’d want to use more than one, and provide practical, step-by-step examples you can follow.

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What Are Tableau Sets? (A Quick Refresher)

Before diving into complex combinations, let’s quickly cover what a set is in Tableau. Think of a set as a custom group or a segment of your data that you define based on certain conditions. It’s like creating a special bucket for a subset of your dimensions.

A set essentially splits all members of a dimension into two categories: IN or OUT. Are they IN the set you defined, or are they OUT?

For example, you could create a set named "Top 10 Customers by Sales." Any customer who is in that top 10 is "IN" the set, and every other customer is "OUT."

Tableau offers two main types of sets:

  • Constant (or Fixed) Sets: The members in this type of set are fixed. You manually select the dimension members you want to include. For instance, you could create a set of specific regions like “West Coast” that always contains California, Oregon, and Washington. This set will not change unless you manually edit it.
  • Dynamic Sets: The members in this type of set change automatically as the underlying data updates. This is where the power lies. A dynamic set is defined by rules and conditions, such as "Top 25 Products by Profit" or "Customers whose last purchase was in the last 30 days." Next month, the members of these sets could be completely different.

Using a single set is powerful for highlighting or filtering. But the real magic happens when you start combining them to answer more nuanced business questions.

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Why Use Multiple Sets in a View?

Using multiple sets lets you move beyond simple, one-dimensional analysis and start performing sophisticated segmentation right inside your dashboard. It helps you ask and answer layered questions that compare different groups, find hidden overlaps, and create very specific cohorts.

Here are a few common scenarios where combining sets is incredibly useful:

  • Comparing Segments: You can directly compare the performance of two distinct groups. For example, how do the buying habits of your "Top Customers by Sales" differ from a set of your "Most Frequent Shoppers"?
  • Finding Intersections: You can identify members that exist in two or more sets simultaneously. Think of it like a Venn diagram. For example, which of your "Customers Acquired from Facebook Ads" are also in the set of "Customers with a High Lifetime Value"? Finding this overlapping group might tell you if your Facebook campaigns are attracting the right audience.
  • Creating Exclusionary Groups: You can find members that are in one set but not another. For example, show me all customers who are in the "Purchased in January" set but are not in the "Purchased in February" set. This gives you a clear list of customers who may have recently churned.
  • Building Complex Cohorts: You can build highly specific audiences for analysis. A classic e-commerce example is identifying customers who bought Product A and who also later bought Product B, a crucial insight for understanding cross-selling opportunities.

Essentially, multiple sets transform your broad analysis into a highly focused investigation, letting you prove or disprove hypotheses with much greater precision.

How to Use Multiple Sets in a Single View: Practical Examples

Let's move from theory to practice. Here are three common business scenarios showing how you can use multiple sets in a single Tableau view to get answers.

For these examples, we'll use Tableau's sample "Superstore" dataset.

Example 1: The Side-by-Side Comparison

Goal: We want to compare the total sales generated by our top 10% of customers against the sales from our bottom 50% of customers.

Our approach will involve creating two dynamic sets and then using a calculated field to group them for comparison in a simple bar chart.

Step 1: Create the "Top 10% Customers" Set

  1. In the Data pane, right-click on the Customer Name dimension and select Create > Set.
  2. Name this set "Top 10% Customers by Sales".
  3. Go to the "Top" tab. Select "By field".
  4. Choose Top 10 by Sales (Sum). Make sure you select the dropdown and change "Top" to "Top %" to analyze by percentage, not count. Click OK.

Step 2: Create the "Bottom 50% Customers" Set

  1. Repeat the process. Right-click Customer Name and select Create > Set.
  2. Name this set "Bottom 50% Customers by Sales".
  3. Go to the "Top" tab again. This time, select "By field" but choose Bottom 50 by Sales (Sum) and specify %. Click OK.

Step 3: Create a Calculated Field to Group Customers

  1. Click the down arrow in the Data pane and select Create Calculated Field.
  2. Name it "Customer Segment (Top vs. Bottom)".
  3. Enter the following formula. This calculation checks if a customer is IN the top set, then checks if they are IN the bottom set. If they're in neither, they’re lumped into an 'Other' category.
  4. Click OK. You now have a custom dimension that dynamically segments your customers into three groups.

Step 4: Build the View

  1. Drag your new calculated field, Customer Segment (Top vs. Bottom), to the Columns shelf.
  2. Drag the Sales measure to the Rows shelf.
  3. You can add Sales to the Label mark on the Marks card to see the exact figures.
  4. If you want to focus only on the two segments we created, drag Customer Segment (Top vs. Bottom) to the Filters shelf and de-select "Other".

Instantly, you have a view using two different sets to cleanly compare the sales performance of these distinct customer groups.

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Example 2: Finding the Overlap with a Combined Set

Goal: Identify customers who are both high-value (top 20 by sales) and recent purchasers (made a purchase in 2022). This group represents our most valuable, currently active customers.

Here, we will create two sets and then combine them to create a third, derivative set that contains only the members who exist in both.

Step 1: Create the "Top 20 Customers" Set

  1. Right-click on Customer Name and select Create > Set.
  2. Name it "Top 20 Customers by Sales".
  3. On the "Top" tab, select "By field" and configure it to be Top 20 by Sales (Sum).
  4. Click OK.

Step 2: Create the "2022 Purchasers" Set

  1. Right-click on Customer Name again and select Create > Set.
  2. Name it "2022 Purchasers".
  3. Go to the "Condition" tab. Select "By formula".
  4. Enter a formula to check if the maximum order year for a customer is 2022:
  5. Click OK.

Step 3: Create a Combined Set

  1. In the Data pane, you'll see your two new sets listed. Select both of them by holding Ctrl (or Cmd on Mac) and clicking each one.
  2. Right-click on one of the selected sets and choose Create > Combined Set....
  3. Name your new set, for example, "Top AND Recent Customers".
  4. You'll see four options for how to combine the sets. For our goal, select Shared members in both sets. Click OK.

Step 4: Use the Combined Set in a View Now you have a dynamic set identifying your all-star customers. You can use it in several ways:

  • As a Filter: Drag Top AND Recent Customers to the Filters shelf to see only the performance data related to this elite group.
  • As a Highlighter: Build a scatter plot showing Sales vs. Profit for all customers. Then, drag Top AND Recent Customers to the Color mark on the Marks card. Tableau will now use two different colors to visually separate your elite customers from the rest, making them instantly stand out.

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Example 3: Adding Context with a Dual-Axis Chart

Goal: Analyze Product Sales. We want to see total sales for each product, but we also want to visually highlight which products were purchased by our repeat customers.

This method doesn't use a "calculated field" or "combined set" in the same way, but it layers sets onto one view to create a rich, contextual analysis.

Step 1: Create a "Repeat Customers" Set

  1. Right-click on Customer Name and select Create > Set.
  2. Name it "Repeat Customers".
  3. Go to the 'Condition' tab and choose 'By formula'.
  4. Enter a formula to find any customer who has placed more than one distinct order:
  5. Click OK.

Step 2: Create a Sales by Product View

  1. Drag Sub-Category to the Columns shelf.
  2. Drag Sales to the Rows shelf. You'll get a simple bar chart.

Step 3: Add in the "Repeat Customers" data

  1. Drag the Repeat Customers set to the Marks card and drop it onto the Color attribute.
  2. Tableau automatically creates what’s called a 'stacked bar chart'. Now, each bar is segmented into two colors: one part represents sales from 'IN' the set (repeat customers), and the other represents sales from 'OUT' (first-time purchasers).

Now, at a glance, you can see not just which products sell best, but you can also quickly spot which ones are particularly popular with your most loyal customers, or which popular products are driven almost exclusively by one-off purchases.

Final Thoughts

Using multiple sets in a single Tableau view is an essential skill for anyone looking to go beyond surface-level reporting. By creatively combining, comparing, and filtering with sets, you can precisely segment your audience, test hypotheses, and uncover customer behaviors that a simple bar chart of total sales would never reveal.

As you can see, performing this kind of layered analysis in traditional BI tools requires several steps: creating multiple sets, configuring them correctly, writing special calculated fields, and assembling everything in the right order. We built Graphed to automate these kinds of tedious workflows. Instead of manually clicking through menus, you can simply use plain English to ask complex questions like, "Show me a chart comparing sales from repeat customers vs. new customers" or "Find which products my top 10% of customers are buying," and receive a complete, real-time dashboard in seconds.

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