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Average cycle times tell you nothing about a specific deal. A Deal Velocity Prediction Playbook reads stage-by-stage timing on the active deal, activity patterns, and historical patterns of similar deals to predict the close timeline per deal and flag deals slipping behind their expected velocity.
The Challenge
Sales ops reports an average cycle time of 64 days. Inside that average sit deals closing in 20 days and deals dragging past 180. The average tells planning nothing about which specific deals will close this quarter and which will slip.
A deal in stage 3 for 18 days looks fine if the average stage-3 time is 14. By day 30 it has clearly slipped, but the slip warning came too late for the rep to intervene. Without per-deal velocity prediction, slip detection is reactive.
The quarter-end forecast assumes deals in stage X will close within Y days. When velocity in segment A has shifted, the assumption breaks and the forecast misses. The pattern emerges as a quarter-end surprise rather than a manageable trend.
How eyko Solves It
A Deal Velocity Prediction Playbook reads stage-by-stage timing on the active deal, activity patterns (meeting cadence, content engagement, stakeholder coverage), deal-stage-fit signals, and historical patterns of similar deals to forecast each deal's close timeline. It surfaces deals slipping behind expected velocity early, attributes the slip to specific factors, and recommends targeted intervention while there is still time.
The Playbook scored 480 active pipeline deals on projected close timeline. 142 deals are tracking on expected velocity. 84 deals are tracking slower than expected, including 38 forecasted to close this quarter that will likely slip to next. The 38 slipping deals represent $4.2M in this-quarter forecast at risk. Early flagging on the 84 slower-than-expected cohort projects 24 saves through targeted intervention.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Deal Velocity Prediction forecasts each active deal's close timeline using stage-by-stage timing, activity patterns, deal-stage-fit signals, and historical patterns of similar deals. The Playbook surfaces deals slipping behind expected velocity, attributes the slip to specific factors, and recommends targeted intervention so reps act on signal rather than discover the slip at quarter-end.
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FAQ
Everything you need to know about Deal Velocity Forecast.
Deal Velocity Prediction is an AI-driven forecast of each active deal's close timeline using stage-by-stage timing, activity patterns, deal-stage-fit signals, and historical patterns of similar deals. The Playbook surfaces deals slipping behind expected velocity, attributes the slip to specific factors, and recommends targeted intervention so reps act on signal rather than discover the slip at quarter-end.
The Playbook reads from your CRM (deal records, stage history, opportunity activity), sales engagement platform (meeting cadence, email patterns, content engagement), calendar system (meeting attendance), and historical deal outcomes for similar deals at similar stages. At least 18 months of paired deal-stage-and-outcome data anchors the velocity prediction.
Average cycle time describes the cohort baseline. Deal Velocity Prediction is per-deal: it forecasts the specific close timeline for each active deal based on the signals visible right now. The two are complementary, but per-deal prediction is what flags slip risk early enough for intervention.
Yes. For each slipping deal the Playbook recommends a specific motion: rep briefing with the named slip driver, executive sponsorship on high-value slips, content delivery targeted at the weakening engagement signal, or competitive-positioning intervention where competitive pressure has surfaced. Each recommendation projects close-quarter pipeline retained.
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