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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
Configuring Y-axis for multiple metrics in HubSpot’s unified dashboards fails because the platform can’t handle different metric scales, data types, and units within single visualizations. HubSpot forces all metrics onto one Y-axis scale, making smaller values invisible or creating misleading visualizations.
The solution is preparing data specifically for multi-metric visualization with proper scaling and metric groupings.
Prepare data with proper scaling for multi-metric Y-axis configuration
CoefficientHubSpotHubSpot’sprovides sophisticated Y-axis configuration through data preparation by importing all relevant data fromand creating separate data ranges for metrics requiring different Y-axis scales. You can build normalized versions of metrics, create metric hierarchies, and prepare multiple data ranges with consistent dimensions, unlikelimited automatic scaling options.
How to make it work
Step 1. Create separate data ranges for different metric scales.
Import all relevant HubSpot data using Coefficient and create separate data ranges for metrics requiring different Y-axis scales. For example, create one range for revenue amounts and another for conversion percentages, while maintaining consistent date and dimension columns for synchronized filtering.
Step 2. Build normalized metric versions.
Create calculated columns that convert metrics to comparable scales when appropriate. Convert revenue to thousands, percentages to decimals, or create index values and percentage-of-target calculations that enable unified scaling across different metric types.
Step 3. Establish metric categories and hierarchies.
Create clear metric categories (volume metrics, rate metrics, currency metrics) with standardized scaling and build metric hierarchies with primary and secondary indicators for dual-axis chart preparation. Use conditional formatting to identify which metrics need secondary Y-axis treatment.
Step 4. Set up automated scaling maintenance.
Use Coefficient’s scheduled refreshes to maintain proper scaling as data values change over time. Create validation checks to ensure Y-axis scaling remains appropriate as data ranges evolve, and build documentation columns explaining transformation logic for each metric type.
Enable proper multi-metric visualization with controlled Y-axis scaling
Start buildingPreparing data specifically for multi-metric visualization eliminates Y-axis configuration issues and enables meaningful comparisons.unified dashboards that properly handle multiple metric types with appropriate Y-axis scaling.
