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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.”
Setting up two date filters that control different data series requires proper multi-series data preparation and independent control architecture. While visualization tools implement the dual filter interface, your data structure determines how effectively those filters work with different series.
Here’s how to prepare multi-series datasets that enable independent date filtering for different data series within the same graph.
Prepare multi-series data using Coefficient
Coefficient excels at preparing multi-series datasets that enable independent date filtering for different data series within visualization tools. Proper data preparation makes dual filtering work smoothly across different series.
How to make it work
Step 1. Create independent data streams for each series.
Set up separate Salesforce imports for each data series with distinct date filtering. Configure Series A import with dynamic filters pointing to “Series_A_Start_Date” and “Series_A_End_Date” cells, and Series B import pointing to “Series_B_Start_Date” and “Series_B_End_Date” cells.
Step 2. Add series identification with Formula Auto Fill Down.
Use Formula Auto Fill Down to add series identifiers to each dataset. This creates clear separation between revenue data, conversion data, or other series types. Series identification enables visualization tools to apply different date filters to different data series effectively.
Step 3. Build unified data structure for comparison.
Combine multiple series into a single comparison-ready dataset. Structure data with Date, Series_ID, Metric_Name, Value, and Date_Filter_Group columns. This unified structure supports complex multi-series visualizations while maintaining independent filter capabilities.
Step 4. Configure advanced series management.
Set up different refresh schedules per series – revenue data might update daily while conversion rates update weekly. Use Snapshots to preserve historical series data for consistent comparisons. Append New Data maintains series continuity while adding current updates.
Step 5. Enable independent control benefits.
Structure data so each series can have different date ranges without affecting others. Automated updates maintain series accuracy independently, and conditional logic can trigger different actions per series. This creates the foundation for visualization tools to implement independent date filtering.
Build effective multi-series filtering
Independent date filtering works best when your multi-series data is properly separated and consistently maintained. Salesforce provides the source data while Coefficient handles complex multi-series preparation. Start building better multi-series datasets today.
