RevOps/No. 03/6 min read
Why your “sales cycle” metric is lying to you
Most sales cycle numbers are built on three timestamp errors that make your cycle look shorter and cleaner than it is. Here’s the property structure that surfaces where deals actually stall.
Ask a revenue team for their average sales cycle and you'll get a confident number. 47 days. 62 days. Whatever it is, it's almost certainly wrong, and it's wrong in the direction that feels good: it makes your pipeline look faster and tidier than it really is.
That matters because you forecast on this number, you set rep expectations on it, and you tell the board with it. A sales cycle metric you can't trust isn't a vanity problem. It's a planning problem.
Three timestamp errors cause almost all of it. Here's each one and the property structure that fixes it.
Error 1: You're measuring from the wrong start
The most common mistake is measuring cycle time from contact or lead creation instead of from the moment a real opportunity exists. So the clock starts when someone downloads an ebook, then runs for the four months they ignored you, then keeps running through the actual three-week sales process.
Now your "sales cycle" is mostly marketing nurture time wearing a sales costume. Worse, it's wildly inconsistent, because how long someone sat in nurture has nothing to do with how long it takes your team to close a deal.
The fix is to define the start as a deliberate event, not a default one. Cycle time starts when a deal is created, or when it enters your first real sales stage. Capture that as its own timestamp and measure from there. What happened before the opportunity existed is a separate metric: that's your lead-to-opportunity lag, and it belongs to marketing, not to sales cycle.
Error 2: You're only counting the deals that closed
The second error is survivorship. Most cycle reports quietly measure only closed-won deals, because those are the ones with a clean start and end date. Deals that died get dropped from the average.
So your number describes your winners and ignores everyone who stalled, ghosted, or went dark for two months before closing-lost. You're measuring the happy path and calling it the average. The deals that actually reveal where your process breaks are the ones missing from the report.
The fix is to measure cycle time across both outcomes and segment them. Won deals have one cycle profile. Lost deals usually have a longer, uglier one, full of the stalls that tell you where the process is leaking. If you only ever look at winners, you will never see the stage where deals go to die, because by definition the deals that died there aren't in your sample.
Error 3: You have no per-stage timestamps, so you can't see the stall
The first two errors distort the total. The third is why the total is useless even when it's right: a single number can't tell you where the time goes.
"Our cycle is 47 days" is not an actionable sentence. "Deals sit an average of 19 days in Proposal, three times longer than any other stage" is. The difference is whether you captured a timestamp every time a deal entered a stage. Most accounts don't. They have a create date and a close date and a black box in between.
The fix is structural. Stamp a date property every time a deal enters a stage. In most CRMs you do this with a simple automation: when deal stage changes to X, set "Date entered X" to now. Once those properties exist, stage duration is just subtraction, and the black box becomes a map. You stop reporting a cycle length and start reporting a bottleneck.
What good looks like
Put the three fixes together and the metric starts earning its place:
- Cycle measured from opportunity creation, so it reflects selling time, not nurture time.
- Won and lost deals measured separately, so you see the full picture instead of the happy path.
- Per-stage timestamps, so you can name the exact stage where deals stall instead of guessing.
Now the number survives a follow-up question. When someone asks "why is our cycle 47 days," you can answer "because deals sit in Proposal for 19 of them, and here's what we're doing about it." That's the difference between a metric you report and a metric you can act on.
Most of this is a property and automation problem, not a sales problem. The selling isn't necessarily slow. The measurement is just blind. Fixing the structure underneath is the kind of work we do in nearly every Marketing Operations & CRM engagement, because you can't improve a cycle you can't see.