Unit 3 · Creating Your Pricing Strategy · Lesson 3.5
Defining the length of a step
The length of each step comes from one chart: length of stay plotted against booking window, in your market dashboard with your comp set applied. Strip out the long stays that inflate night counts without adding bookings, feed the remaining totals into the strategy sheet, and it returns start and end days for the hedge, control and test steps. Revisit it monthly, because the data behind it covers the past 30 days.
The full lesson text below is an edited transcript of the video, published 2026-08-24. The complete course is free at the playbook.
Where the data comes from
The lengths of the hedge, control and test steps are decided by a single chart: length of stay plotted against booking window. It sits in your market dashboard, with the comp set you built for your listing applied so the data describes the listings you actually compete with, and it is the second of the charts under the dashboard’s length of stay and booking window trends.
It arrives as a bar chart. Each bar is a booking window, running from bookings made 0 to 1 day before arrival out to bookings made more than six months ahead, and the height of each bar is the number of nights booked in the market within that window. Those bar totals are the input the strategy sheet needs.
Filtering out the long stays
Before those totals are usable, one distortion has to be dealt with. In short-term rentals the outlier data is the long stay, anything from a week up to a full month. The chart counts nights, not reservations, so a single month-long booking contributes thirty nights to whichever window it landed in while representing one piece of booking activity. Left in, long stays overstate demand in that window, and the step lengths derived from them inherit the error.
The chart can be re-cut to show booked nights by length of stay and booking window. That colour-codes and segments every bar by stay length, with a legend beneath the chart naming each segment. The ones to watch are the segments covering week-long through month-long stays, and resting on a bar reveals the nights booked in each segment.
Which segments to remove is a judgement call rather than a rule. In the sample market the 7 to 14 night stays were kept and only the 15-plus and 29-plus segments were taken out. The reasoning is booking frequency. Within the 2 to 4 month booking window, 48 nights were booked as 7 to 14 night stays, which cannot be fewer than four separate bookings. The 5 to 6 night stays in that same window totalled 36 nights, which is at least six bookings. Comparable frequency, so the longer segment represents a real slice of demand worth catering to.
The 15 to 28 and 29-plus segments were a different case. They were visible on the chart only because of how long each stay was, not because many guests were booking them. Deselecting them from the legend takes them out, and the bar totals that remain describe the market’s actual booking activity.
Putting the totals into the sheet
Each bar total, the nights booked in that booking window, goes into the matching nights booked field on the length of stay tab of the strategy sheet. There is a way of doing the entry that keeps the outlier subtraction visible instead of hiding it in mental arithmetic.
Put the long stays back onto the chart first, and enter their nights into each field as negative values inside a formula. Then return the chart to its unfiltered view and add the full window total in front of them. Every cell then reads as the whole booking window minus the long stays you decided to exclude, so the exclusion stays legible and correctable rather than baked into a number nobody can explain later.
In the sample market the unfiltered totals ran 98 nights in the 0 to 1 day window, 96 in the 2 to 6 day, 75 in the 7 to 13 day, 147 in the 2 to 4 week, 152 in the 1 to 2 month, 159 in the 2 to 4 month, 76 in the 4 to 6 month and 65 beyond six months. The long stays to subtract were 40, 16, 30 and 18 nights in the first four of those windows, none in the 1 to 2 month, 18 in the 2 to 4 month, none in the 4 to 6 month, and 21 beyond six months.
Then validate the entry. The strategy sheet draws its own bar chart from the numbers you typed, and its shape should follow the chart in PriceLabs window by window. If you excluded outliers, compare against the filtered version of the chart; if you did not, compare against the unfiltered one. Two charts with the same profile is the confirmation that the data went in correctly.
Reading the recommended step lengths
With the numbers in place, the bottom of the length of stay tab returns a recommended length of step for the hedge, the control and the test, given as start and end days. The allocation logic behind it is simple: a small portion of the market’s booking activity is assigned to the hedge step, and the remainder is split evenly between the control and test steps.
In the sample market that produced 0 to 2 days for the hedge step, 3 to 45 days for the control step, and 46 to 365 days for the test step. Your own result may look similar or nothing like it. Booking behaviour belongs to a specific location and to what that market has been doing recently, so a wide spread of recommendations between markets is exactly what to expect.
When the hedge step comes back short
A very short hedge step is common, and a recommendation of 0 to 0 days is not an error. It says the market books heavily even on the day of arrival, and that dropping your price at the last minute gives you a real chance of picking up those bookings.
A new listing, or one struggling with occupancy, may reasonably prefer to play it safer by holding lower prices open for longer. The lever is the percentage of nights booked allocated to the hedge step, which sits at 10% by default. Raise that percentage and more of the market’s booking activity falls inside the hedge step, which lengthens it.
In the sample market, moving from 10% to 15% turned a 0 to 2 day hedge step into 0 to 4 days, and moving to 20% stretched it to a full week. Twenty percent is about as far as this is worth pushing, and 15% is the more defensible of the two adjustments, if an adjustment is wanted at all: a 0 to 4 day hedge step already covers the healthy activity showing in the 0 to 1 day and 2 to 6 day booking windows, which is where the last-minute bookings actually sit.
One caution travels with the lever. The control step is where the majority of your booking activity should come from. Lengthening the hedge step to compensate for a control step that is not producing bookings treats the symptom rather than the cause: if the control step is not working, its pricing is what needs the attention.
Review it every month
The data underneath all of this reflects your comp set’s booking activity over the past 30 days, which makes the length of step strategy a rolling decision rather than a fixed one. Review it monthly. Markets move, and a seasonal one moves sharply, so the booking windows carrying the activity a month ago may not be the ones carrying it now.