Visualize data using color-coded representations to identify patterns and trends effectively.
Plan Availability | All plan types |
Permissions | Solution Creators and Workspace Admins: Create, configure, and manage Heatmap Charts. |
Related Reading |
Overview
A Heatmap Chart visually represents data using a color-coded system, making it easier to identify clusters, trends, and variations in values. This chart type is ideal for quickly spotting patterns and understanding large datasets at a glance.
Key Features and Enhancements
Consistent Sorting: Ensures data is systematically ordered for clarity.
Drill-In Enabled Values: Click into segments for deeper insights.
Refined Color Scale: Enhances differentiation of value variations.
Configurable Sort Order: Customize sorting for both X and Y axes.
Labeled Axes: Clearly displays field names from source data.
Creating a Heatmap Chart
Adding a New Chart View
Open a table where you want to create the heatmap chart.
Click "Add View" to create a new view.
Select "Chart View" from the available view types.
Selecting Heatmap Chart
In the chart settings section, choose "Heatmap Chart" as the chart type.
Configuring Chart Settings
Value Field: Select the field that provides values for the heatmap cells.
X and Y Axis Fields: Choose fields that define the heatmap’s X and Y axes.
All fields work and X and Y’s except for Dependency, Files & Images, SmartDoc, Checklist, and Sub-Items.
Adjust Sort Order:
Configure X and Y axis sorting using "First to Last" or "Last to First" options.
Example: Heatmap with Single Select, Multi-Select, and Sum
A heatmap can visualize data across multiple selection fields while summing numerical values for deeper insights.
Practical Use Cases and Scenarios
1. Sales Performance Tracking
Scenario: A sales team wants to analyze performance across different regions and time periods.
Solution: Create a heatmap chart to visualize high-performing regions and key sales months.
Outcome: Quickly identifies trends and allows drill-in analysis for deeper insights.
2. Customer Support Analytics
Scenario: A support team wants to monitor ticket volume trends.
Solution: Use a heatmap to track high-activity periods and common issue categories.
Outcome: Improves resource allocation and enhances customer service efficiency.
3. Website Traffic Analysis
Scenario: A marketing team needs to understand peak traffic times.
Solution: Create a heatmap displaying traffic patterns by hour and day of the week.
Outcome: Helps optimize content publishing schedules and ad placements.
Example: Heatmap with Single Select, Multi-Select, and Sum
A heatmap can visualize data across multiple selection fields while summing numerical values for deeper insights.