A deal in stage for ninety days with weekly meetings is working. A deal in stage for fifteen days with no email, no call, and no note is stuck. Stuck time names the difference.
Pipeline stuck time is the number of days an open deal has gone without any logged activity, note, or stage change despite sitting in an active forecast stage. Unlike stage aging, which counts every day a deal has spent in its current stage, stuck time only counts days of silence. Modern CRMs flag stuck deals for manager review, and the share of pipeline that is stuck is one of the hygiene KPIs that separates a forecast you can trust from one you cannot.
Six things to know about stuck time, how it differs from aging, and why the hygiene number matters more than the raw count.
Stuck time starts the clock the last time a deal recorded any activity: a sent email, a logged call, a meeting, a note, or a stage change. It stops when the deal records a new one. A deal with weekly engagement never accrues stuck time, no matter how long it sits in a stage.
Three events reset the stuck-time clock on a modern CRM: a logged touch (email, call, meeting), a human note added to the deal, or a stage transition. If none of those three has happened in the configured window, the deal is flagged. Everything else, including dashboard views and opens, does not count.
Stage aging counts every day the deal has been in its current stage, including the days with activity. Stuck time counts only the quiet days. A healthy deal can have high aging and zero stuck days. An unhealthy deal can be new to a stage and already stuck. Both metrics matter, for different reasons.
Most teams flag a deal as stuck at fourteen days of silence for short cycles, thirty for longer enterprise cycles. The threshold is tuned to the typical touch cadence of a working deal in that segment. The point is not the exact number; it is to catch a deal before it rots quietly in the forecast.
Stuck percentage is the share of open pipeline value sitting in flagged stuck deals. A clean pipeline runs under ten percent stuck. Above twenty percent and the forecast is noise. The number is tracked per rep, per stage, and per segment because the root cause changes with each cut.
Every stuck deal gets one of three outcomes at the weekly review: a specific next step and a date to reactivate it, a reassignment if the owner is blocked, or a loss with a reason. Letting a stuck deal sit for another week is not an outcome. It is a quiet forecast lie compounding.
Sales teams used to track stage aging alone, which treats time in stage as a proxy for risk. That proxy is noisy: a six-month enterprise deal with a buying committee is not stuck at ninety days in evaluation. Stuck time was invented to separate time elapsed from time silent. Reading the two together is what turns a pile of open deals into a prioritized review list.
Starts the day the deal entered its current stage. Does not care about activity. Useful for comparing a deal against the typical cycle time of that stage. A deal in evaluation at ninety days with a thirty-day benchmark deserves a question even if it logged a call this morning.
Starts the moment the last activity, note, or stage change was recorded. Resets on every real touch. Useful for catching deals that have gone quiet regardless of how long they have been in stage. A deal that just entered proposal and has heard nothing in three weeks is stuck.
Low aging and low stuck days means the deal is moving on schedule and the rep is engaged. The review question is strategic, not hygienic: what is the next proof point, when is the signed contract, who else on the buying committee is in play.
Classic enterprise shape: a deal that has been in stage for a long time but has consistent touches. Not stuck. The review question is whether the deal is really advancing or just circling: who has to sign, what is blocking, is the champion still in seat.
The most dangerous shape and the easiest to miss. A deal that just advanced but has gone cold is almost always a reality check: the stage was advanced optimistically, the buyer is ghosting, or the next step was never real. These deserve the hardest conversation at the review.
Long time in stage and long time silent is the deal that is not going to close. The review question is how to kill it cleanly: either reactivate with a specific plan and a date, or close it lost with a reason so the team learns from the pattern instead of carrying the dead weight.
Stuck time is simple arithmetic on top of the activity log, but the configuration choices around it change what the number means. Which events count as a reset? What stages are in scope? How is the threshold set per segment? The decisions below are the ones every revenue operations team makes once, documents, and defends in the quarterly review.
The number of days between the current date and the most recent activity, note, or stage change on the deal. Logged in minutes but reported in days. Weekends count. Holidays count. The point is calendar silence, not working-day silence, because buyers do not stop existing on Saturday.
An activity record (email, call, meeting, task completion), a note from a human, or a stage change. CRM background syncs do not reset the clock. Dashboard views do not reset the clock. A rep opening the record and closing it does not reset the clock. Only real work shows up.
Stuck time is only tracked on open deals in stages that count toward the forecast. Deals in prospecting that have not qualified are noise. Deals already closed won or closed lost are history. The stuck list is what the manager can act on this week.
SMB deals might flag at seven days of silence, mid-market at fourteen, enterprise at thirty. Early stages often use a tighter window than late stages. The threshold is a knob on the stuck definition, not a universal constant. Revenue operations tunes it against the historical cycle time per segment.
Three numbers show up on the manager dashboard. Count of stuck deals. Total value of stuck pipeline. Stuck percentage, which is stuck value divided by total open pipeline. The percentage is the headline KPI because it normalizes across deal sizes and makes trend lines across quarters comparable.
A single stuck percentage is a snapshot. The useful view is the trend over the last six to twelve weeks, overlaid on the forecast attainment of the following period. Teams that trend down on stuck percentage usually trend up on forecast accuracy a quarter later. The relationship is tight enough to coach to.
Flagging a deal as stuck is cheap. Resolving it is the point. The weekly rhythm below is what separates teams that use stuck time as a working tool from teams that stare at a red dashboard tile every Monday and change nothing. The goal is not zero stuck deals; it is a list that is actioned every week with a reason attached to each decision.
The sales manager pulls the stuck list before the Monday pipeline review and sorts it by value. Every deal on the list gets a quick triage: reactivate, reassign, or lose. The decisions get captured on the deal record so the next review is faster and the trend is traceable.
Reactivating a stuck deal means more than firing off a check-in email. It means a specific action the rep will take, a specific person the buyer will hear from, and a specific date it will happen by. The deal record gets the new next step logged, which resets the clock.
If a rep is overloaded, out of pattern on a segment, or stuck in a champion gap, reassignment is the honest move. A new owner with a fresh perspective and a warm handoff from the manager often reopens a deal the previous rep could not. The reassignment itself is a signal to track.
A stuck deal that cannot be reactivated gets closed lost with a specific reason: budget, timing, no decision, competitor, product fit, champion left. The lost reason is the raw material of the quarterly review. The small discipline of forcing a reason is what turns stuck deals into institutional learning.
Strkr AI surfaces the stuck list, highlights the biggest-value stuck deals, and suggests likely root causes drawn from similar past deals. The suggestions are prompts for the review, not verdicts. The rep and manager make the call; the tool just makes the pattern easier to see at the start of the meeting.
Stuck percentage broken down by stage, segment, and lead source tells a story that a single number cannot. If the same stage keeps generating stuck deals, the stage definition is probably loose. If one source feeds the stuck list every quarter, the source is not qualifying well. The breakdown is where coaching lives.
Strkr tracks stuck time on every open deal, surfaces the list for weekly review, and lets Strkr AI rank the biggest-value stuck deals with likely root causes. Managers get one working view instead of a side spreadsheet, and the forecast finally lines up with what the pipeline is actually doing.
Pipeline stuck time is the number of days an open deal has gone without any logged activity, note, or stage change despite still sitting in an active forecast stage. It is a hygiene metric that catches deals which look alive on the dashboard but have actually gone cold. Most modern CRMs flag a deal as stuck once stuck time crosses a threshold, usually fourteen to thirty days depending on the sales cycle.
Stage aging counts every day a deal has been in its current stage, including the days with activity. Stuck time counts only the days of silence since the last activity, note, or stage change. A healthy enterprise deal can have ninety days of stage aging with zero stuck days because it is being worked every week. A new deal can have five days of aging and already be stuck if nothing has been logged since it advanced.
Three event types reset the stuck-time clock: a logged activity like an email, call, meeting, or completed task, a human-added note on the deal, or a stage change. Background syncs, dashboard views, and opening the record without taking action do not count. The clock is designed to measure real work on the deal, not casual contact with the CRM interface.
A clean pipeline typically runs under ten percent of open pipeline value in stuck deals. Between ten and twenty percent is a warning zone that deserves a weekly review focus. Above twenty percent and the forecast is unreliable because a meaningful share of the pipeline is not actually being worked. The target varies by segment and cycle, but the direction of the trend matters more than the absolute number.
Most modern CRMs expose stuck deals through a filtered view or a dedicated manager dashboard tile. The filter is open deals in forecast stages where the last activity, note, or stage change is older than the configured threshold. In Strkr the stuck list is a one-click view on the pipeline Kanban and the manager dashboard, sorted by value so the biggest-impact deals surface first.
Stuck time matters because it exposes the gap between what the pipeline looks like and what the pipeline is doing. A deal that has not been touched in a month is not advancing, regardless of what stage says. Catching stuck deals early lets the team reactivate them before they rot, reassign them when the owner is blocked, or close them lost cleanly instead of carrying dead weight into the forecast.
Weekly, before the pipeline review meeting. The manager pulls the stuck list, sorts by value, and triages each deal with a reactivate, reassign, or lose decision. Any deal left on the list for a second week without a change in state is a sign the review discipline is slipping. The weekly cadence is tight enough to catch issues before they compound and loose enough to let real deals develop.
The flagging is automated. The resolution is not. Strkr AI surfaces the stuck list, ranks it by value and risk, and suggests likely root causes based on patterns in similar past deals. The rep and manager still own the decision to reactivate, reassign, or lose the deal. Treating the automated flag as a prompt for human judgment, not a verdict, is the practice that keeps forecast quality high.
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