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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.”
Creating time-series charts of coverage ratios requires historical data that HubSpot doesn’t retain. Without this historical context, you can’t visualize coverage trends over time.
Here’s how to automate historical pipeline data collection and build dynamic coverage ratio charts that reveal important patterns.
Build time-series coverage charts using Coefficient
Coefficient enables this by automating historical pipeline data collection from HubSpot and providing the foundation for coverage ratio snapshots in HubSpot spreadsheets.
How to make it work
Step 1. Set up automated data import.
Connect HubSpot to your spreadsheet via Coefficient and import deals with amount, close date, probability, and owner fields. Schedule hourly or daily refreshes to capture pipeline changes as they happen.
Step 2. Calculate coverage metrics.
Add quota data to your spreadsheet and create coverage ratio formulas using Weighted Pipeline Value divided by Quota. Include variations like stage-specific coverage or rep-level metrics for more granular analysis.
Step 3. Implement snapshot strategy.
Configure daily snapshots to capture coverage ratios at consistent times. Each snapshot adds a new row with timestamp and current coverage values, building a historical dataset spanning weeks, months, or quarters.
Step 4. Build time-series visualizations.
Use your spreadsheet’s charting tools to create line graphs with date/time stamps from snapshots on the X-axis and coverage ratio percentages on the Y-axis. Add trend lines to show coverage trajectory over time.
Step 5. Enhance your charts.
Create separate series for different pipeline stages, add target coverage ratio reference lines, include moving averages to smooth daily variations, and color-code periods of healthy versus concerning coverage.
Start visualizing coverage trends
This approach transforms static HubSpot data into dynamic pipeline coverage trends, revealing patterns like end-of-quarter degradation or seasonal variations. Begin building your time-series coverage charts today.
