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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.”
Sales Ops and RevOps managers can build a pipeline velocity dashboard showing average stage duration, rolling velocity trends and stalled deal alerts by importing Salesforce Opportunity and OpportunityFieldHistory data into Google Sheets or Excel using Coefficient’s Salesforce connector. Salesforce native reports cannot calculate how long opportunities spend in each stage across your whole pipeline, identify which stage consistently creates bottlenecks or track whether velocity is improving or declining over rolling time windows.
A common challenge for sales leaders: they know deals are slowing down somewhere in the funnel but cannot identify exactly where without pulling field history data that Salesforce reports cannot aggregate into rolling averages.
How to build a pipeline velocity and stage bottleneck dashboard
Step 1. Import OpportunityFieldHistory with stage change events
Open Coefficient in Google Sheets or Excel and select Import from Salesforce. Use From Objects and Fields and select OpportunityFieldHistory. Pull OpportunityId, StageName, CreatedDate, OldValue, NewValue and CreatedById filtered for Field equals StageName. Set an hourly or twice-daily refresh to keep velocity metrics current. This gives you every stage transition your team’s deals have made.
Step 2. Calculate average stage duration and identify bottleneck stages
Sort your field history data by OpportunityId and CreatedDate. Add a formula column calculating days between each stage change event. Use AVERAGEIFS to build a summary table showing average days spent in each stage, both overall and broken down by rep or team. Highlight stages where the average exceeds your target in red using conditional formatting. These are your bottleneck stages.
Step 3. Build rolling 30, 60 and 90-day velocity views
Add a date filter parameter cell and build separate AVERAGEIFS calculations scoped to deals that changed stage within the last 30, 60 and 90 days. Showing all three windows side by side reveals whether velocity is improving or declining. A stage that averages 12 days over 90 days but 18 days over the last 30 is getting slower, which is the insight that triggers action before it shows up in results.
Step 4. Flag stalled deals and set automated alerts
Add a formula column flagging any open opportunity that has been in its current stage for longer than 150 percent of the historical average for that stage. Apply conditional formatting to surface these deals at the top of your view. Set up a Coefficient Slack alert to notify sales managers each morning with a count of deals that crossed the stall threshold overnight, so coaching conversations happen before deals go cold.
What you get
Sales managers know which stage is slowing the pipeline down and by how much, updated every morning without anyone pulling a manual report. Stalled deals surface automatically before they miss the quarter. Velocity trends over rolling windows show whether process changes are actually working.
Start tracking your pipeline velocity automatically at coefficient.io/get-started.
