In today’s data-driven world, the ability to communicate insights visually has become a core competency across industries. Tourism, airlines, retail, hospitality, and e-commerce all rely heavily on visual analytics to track performance, understand market shifts, and make informed decisions. But one of the most universal and powerful use cases in business intelligence is the ability to compare actual performance against a benchmark—whether that benchmark is a target, forecast, budget, or prediction. This article walks you through how to evaluate actual vs target performance using Tableau, focusing on two essential tools: Dual-Axis Charts Dual-Axis Maps By the end, you’ll know exactly how to build interactive, comparative visuals that reveal where you’re hitting targets—and where performance gaps exist.

Why Compare Actual vs Target?

Benchmarking performance is essential because it helps answer questions such as: Are we meeting expected sales this month? Which product categories are underperforming? Which states or cities generate high profit but low revenue (or vice-versa)? Where should we focus our marketing, promotion, and inventory efforts? Visual comparison makes patterns instantly clear, helping users assess performance at a glance, without combing through large tables or spreadsheets.

Part 1: Comparing Sales vs Targets Using Dual-Axis Charts About Dual-Axis Charts A dual-axis chart overlays two independent measures on the same chart—often using different chart types. This is ideal when comparing two related but separate measures, such as: Actual vs Target Actual vs Forecast Current Year vs Previous Year Let’s walk through a real example.

Problem Statement A supermarket owner wants to understand which product categories met their sales targets so they can adjust inventory, promotions, and strategy for the next quarter. You have three data sources: List of Orders Orders Breakdown Sales Targets Your goal: Visualize category-wise performance vs targets month-by-month using a dual-axis chart.

Step-by-Step Guide

Step 1: Load and Join the Data Load the Excel workbook into Tableau. Drag all three sheets into the data model. Tableau will automatically join them based on shared fields. This initial join enables you to visualize historical sales behavior.

Step 2: Bring in the Target Data (Using Data Blending) Because the target data is structured differently, you will bring the Targets sheet as a secondary data source using data blending. Once imported, Tableau will show: Primary data source (orders data) Secondary data source (targets) You can now blend the two using shared fields like: Category Month Year This creates a consistent relationship between actuals and targets.

Step 3: Plot Actual Sales by Category Over Time Start by plotting the monthly sales: Drag Order Date (set to Month/Year) to Columns. Drag Sales to Rows. Drag Category to Color or Rows for comparison. This gives you a timeline of how each category performed month-by-month. However, at this point, the chart only reflects actual performance.

Step 4: Build the Relationship Between Actuals & Targets To compare actual vs target, create a custom data relationship: Open Data → Edit Relationships Select: Primary source: Orders Secondary source: Sales Targets Map fields such as: Category → Category Month → Month Year → Year This ensures the targets line up correctly with the corresponding actual values.

Step 5: Add the Target to the View Drag Sales Target (from the secondary source) into the Rows shelf. You will now see two separate charts: Actual Sales Sales Target But they are not yet integrated visually, so comparison is difficult.

Step 6: Convert the Targets to an Area Chart To create visual distinction: Click the Sales Target mark. Change the chart type to Area. This makes the target appear as a shaded region behind the actual line.

Step 7: Enable Dual-Axis to Combine the Charts Right-click the second “Sales Target” axis → select Dual Axis. Now both measures appear on the same canvas. This instantly enables visual comparison.

Step 8: Synchronize the Axes Since the values may scale differently: Right-click the secondary axis → Synchronize Axis This ensures the lines align correctly, making the comparison meaningful.

Final Output: You now have a clean dual-axis chart where: Area Chart = Target Line Chart = Actual Sales At a glance, the supermarket owner can see: Which months exceeded targets Which categories are underperforming Seasonal patterns Gaps that require attention

Part 2: Comparing Performance Using Dual-Axis Maps Dual-axis maps allow you to overlay two different geographical layers on top of each other—helping you compare regional performance. For this example, you will visualize: Profit by State Sales & Profit by City This lets executives understand performance not just at a high level (state), but at a granular level (city).

Step 1: Load and Join the Dataset Load the Excel file with Orders and Order Details. Tableau will automatically create an inner join.

Step 2: Plot Profit by State In Sheet 1: Drag State to Detail. Drag Profit to Color. Drag Longitude and Latitude fields to build the map. This displays a shaded profit map of the U.S.

Step 3: Build the City-Level Profit Layer Duplicate Longitude into the Columns shelf to create a second map. You need to calculate city-level metrics: LOD City Profits (Include City) LOD City Profits (Exclude City) These Level-of-Detail expressions help compare profit distribution across regions. Then: Plot the city-level profit layer using circles. Use profit to size the bubbles.

Step 4: Merge Using Dual-Axis Map Right-click the second “Longitude” → Dual Axis. Now the maps overlay: State colors (profit intensity) City bubbles (profit volume)

Step 5: Add Detailed Tooltips For deeper analysis: Add Sales Add Profit Add Category Add City Now when a user hovers over a bubble, they see complete city-level performance details.

Final Dual-Axis Map Interpretation The final map reveals: Which states are overall profitable Which cities drive the highest revenue Where profits lag despite high sales Geographic imbalance that needs business attention This empowers executives with a clear, intuitive view of performance across multiple dimensions.

Conclusion

Dual-axis charts and maps are incredibly powerful when comparing actual vs target or actual vs benchmark performance. Tableau makes it easy to combine multiple views into one, enabling users to see patterns that would be invisible in spreadsheets. Whether you’re analyzing: Product category performance Geographic trends Monthly targets Profitability patterns Or any business KPI Dual-axis visuals help translate data into decisions—quickly and effectively. As the saying goes, “A picture is worth a thousand words.” With Tableau, a well-constructed dual-axis chart could be worth a thousand decisions. At Perceptive Analytics, we help organizations accelerate decision-making with data and AI. Through our AI consultation services, we guide teams in adopting intelligent solutions that improve forecasting, automate workflows, and unlock operational efficiencies. Our experienced Power BI Consultants build scalable dashboards and reporting systems that deliver clear, actionable insights. With deep expertise across analytics, BI, and AI, we empower businesses to turn data into a competitive advantage.