Sales Cycle

When nobody counted how long a deal took, quarterly planning always started a week late. Open a new deal after the quarter has already begun and it won't close inside that quarter. But with no figure for how many weeks it takes, there was no way to know when opening had to start.

So the last three weeks of every quarter looked the same. A team realizes the gap to target is large, pulls a fresh list, and starts calling. Meetings get booked. Demos happen. Then the quarter ends. Those deals close in the first month of the next quarter, by which point this quarter's number is already fixed. The same thing repeated for four quarters running without the cause being visible.

A sales cycle exists to turn that duration into a number and move the starting line forward. With an average of sixty days on record, the fact that a deal opened in the final sixty days of a quarter is not this quarter's revenue becomes arithmetic rather than hindsight. After that, the job in the last three weeks changes from pulling a new list to pushing the deals already open, which is work with a much better return at that point in the quarter.

For every closed-won deal, take the difference between its start date and its close date, then produce one representative figure from the set.

Three things have to be settled first.

1. The start point. Some companies use the date of the first email; others use the date the deal was confirmed as having budget and intent and added to the tracked pipeline. The first runs long and the second runs short. Either works as long as the whole team uses the same one — mixed, the average means nothing.
2. The end point. Use the signature date, not the date of verbal agreement. In a company where signature takes another three weeks, treating a handshake as the end produces a figure three weeks short of reality, and every plan built on it slips by three weeks.
3. What the representative figure is. Mean and median diverge. Ten deals at 30, 32, 35, 34, 31, 33, 36, 30, 33 and 210 days give a mean of 50 and a median of 33. One 210-day deal pulled the mean up, so the median is the better input for planning.

Two separations keep the number usable.

Count only deals that closed won. Closed-lost deals get read separately, because a loss is a different kind of event rather than a slower version of the same one. In a market averaging ninety days, a lot of deals dying at twenty days is a signal that the list itself is wrong.

Split by customer size. Pagedeck's team-level contracts average thirty-four days and its enterprise contracts run past ninety. Blend them into a sixty-two day average and neither side can plan with it: the rep working team deals starts needlessly early, and the rep working enterprise deals starts a month too late.

There is no benchmark for the absolute value. A $40-a-month tool gets bought on a card in three days; a $75,000-a-year contract takes four months passing through security and legal review. Four months isn't a bad number. It's what a purchase of that size costs in calendar time at that company, and no amount of selling technique removes a security review.

Three things are worth reading.

1. Movement within one segment. If team contracts ran thirty-four days last quarter and fifty-two this quarter, something changed. Break it down by stage and the location shows up. Growth between demo and proposal means technical follow-ups are backing up; growth between proposal and signature means time spent waiting because nobody asked about the customer's approval process.
2. Spread. Values clustered around thirty-four and values scattered between twelve and ninety are not equally useful even at the same average. When they're scattered, look at the list criteria or the stage definitions before the number.
3. The company it keeps. Cutting duration alone often shrinks deals. Average deal size, the mean value per deal, and win rate, the share of worked deals that close, have to sit beside it before a shorter cycle can be called an improvement.

The figure also feeds planning directly. At a median of sixty days, deals opened in the final sixty days of a quarter aren't this quarter's number. When pipeline coverage — the multiple of the target sitting in open deals — has to be full by is a date this metric produces.

"Team deals run thirty-four days, enterprise past ninety. We track those two separately."

A rule against blending segments.

"Our cycle is sixty days, so anything we open now is next quarter's number."

Drawing a planning boundary with the duration.

"The mean is fifty days but the median is thirty-three. One long deal is dragging the mean."

The wrong representative figure is distorting the picture.

At Pagedeck, Grace breaks the figure down by stage every quarter: first contact to demo, demo to proposal, proposal to signature. Last quarter enterprise deals went from ninety days to 112, and the breakdown put all twenty-two added days after the proposal. The cause was nobody asking about the customer's procurement process in advance.

Since then Sofia confirms the procurement process as negotiation opens on enterprise deals. What she doesn't do is treat the number itself as a target. Handed an instruction to shorten the cycle, a rep moves toward not opening slow deals at all, and the large contracts disappear with them.

The most common reading is that shorter is better. A shorter cycle means more selling in the same period, which is a natural enough inference. But the figure also moves when the mix of deals changes. Stop working four-month enterprise contracts and take only small ones and the cycle drops from ninety days to thirty-four while revenue drops alongside it. An organization watching the number alone files that as an improvement. Duration only means something read next to average deal size and win rate.

The other frequent error is averaging closed-lost deals in with the rest. Counting every worked deal looks fairer and gives a larger sample. But lost deals come in two shapes: ones that were never a fit and die at two weeks, and ones that drag for six months before closing. When the first kind dominates, the average comes in shorter than reality, and a plan built on it opens deals too late. Counting only won deals and reading lost ones separately leaves both legible.