RevPARGenius pricing guides · Worked example series
Reviewed by Mark Joefer, Hotel Market Intelligence Researcher · 13 October 2026 · 9 min read
Hotel booking lead time is the number of days between when a booking is made and the arrival date. In our worked example (synthetic data, stays from 14 Oct 2026), the median confirmed booking was made 14.5 days ahead, half within 6 to 30 days, and 14.3% within three days of arrival. Those late bookings are the ones a rate change can still reach.
The booking figures in this post come from a worked example with synthetic data for a fictional 40-cabin New Zealand holiday park: a reservation sample of 640 bookings (580 confirmed) for stays in the 90 nights from 14 October 2026, plus a separate nightly file. The two do not reconcile exactly, so we never add them together. Its "market middle" figures are illustrative assumptions. No real property is described.
Ask a GM when their rooms sell and you will usually get a feeling, not a figure. "Mostly last minute" or "people book months ahead" are both common answers, and both can be wrong for the same property.
This guide shows how to pull lead time from a PMS export, how to read it in bands, and what it means for pricing the last few rooms. It uses a worked example, the reservation sample of a fictional 40-cabin NZ holiday park.
What is booking lead time and how do you pull it from your PMS?
Lead time is the arrival date minus the date the booking was created, in days. A booking made on 1 November for a stay starting 15 November has a lead time of 14 days. Same-day bookings have a lead time of zero.
Most PMS platforms can export a reservations list with both dates. You need four columns: booking created date, arrival date, status (confirmed, cancelled, no-show) and channel. Add the rate if you can. Then:
- Calculate lead days for each booking as arrival date minus created date.
- Keep confirmed bookings for the main view. Look at cancellations and no-shows separately.
- Group into bands: 0–3 days, 4–7, 8–14, 15–30, 31–60 and more than 60.
- Count and share each band, and find the median, the 25th and the 75th percentile.
Use the median, not a simple mean. A handful of bookings made six months ahead would pull a mean upwards and hide the fact that most guests book within a few weeks.
What does the lead time profile look like in the worked example?
The reservation sample holds 640 bookings: 580 confirmed, 47 cancelled (7.3%) and 13 no-shows (2.0%). For the 580 confirmed bookings, the median lead time is 14.5 days. A quarter were made 6 days or less before arrival, and a quarter 30 days or more.
| Lead time band | Confirmed bookings | Share | Running share |
|---|---|---|---|
| 0–3 days | 83 | 14.3% | 14.3% |
| 4–7 days | 86 | 14.8% | 29.1% |
| 8–14 days | 121 | 20.9% | 50.0% |
| 15–30 days | 150 | 25.9% | 75.9% |
| 31–60 days | 107 | 18.4% | 94.3% |
| More than 60 days | 33 | 5.7% | 100.0% |
Read the running share column. Half of all confirmed bookings arrive within two weeks of their booking date. Nearly three in ten (29.1%) arrive within a week. Only 5.7% book more than two months ahead.
The sample is mostly domestic: 61.4% of confirmed bookings are from New Zealand guests and 14.3% from Australia, with the rest from the US, UK, Germany and other markets. The data does not split lead time by guest market, so we cannot say whether international guests book earlier here. Your own PMS can, and it is worth checking.
When do the last rooms actually sell?
The nightly file shows the park running at 93.2% occupancy over 90 nights. On 40 cabins that leaves about 2.7 cabins unsold on a typical night. Those are the last rooms, and the lead time profile suggests when the rooms just before them were sold: about one booking in seven arrives within three days.
If the last rooms keep selling in the final few days at the same rate as the first, the price is not responding to how full the night already is. That may mean the earlier rooms sold too cheaply, or that late bookers are a price-sensitive group who need the lower rate. Your own data decides which.
Two checks separate those stories. First, compare the rate paid by lead time band. If bookings made 0–3 days out paid the same as bookings made 31–60 days out, nothing in the pricing reacts to how close arrival is. Second, look at how full each night was when the late bookings came in. Late bookings onto a night that was already 90% full are a different signal from late bookings onto a night that was 60% full.
In a property that is nearly always full, as in this example, late bookings usually land on nights that are already busy. That is the classic case for testing a higher rate on the last few rooms. Our post on why high occupancy can hide a rate problem shows the break-even check to run first.
How should lead time change your pricing decisions?
Lead time tells you when a rate change can still matter. With a median of 14.5 days, a rate change made today mostly affects arrivals in the next two to four weeks. A change made in the last three days before arrival reaches only the 14.3% of bookings made that late.
- Set event rates early. In the example, a quarter of bookings come 30 days or more ahead. An event floor loaded a week before arrival has already missed most of them. Our event weekend pricing worked example walks through setting one.
- Use occupancy thresholds for the last rooms. Many properties add a step to the rate once a night passes a set occupancy, so the last few rooms sell at a higher price than the first.
- Watch cancellations. At 7.3% cancelled in the sample, a night that looks full a week out may reopen a cabin or two. Price those returns as last rooms, not as early ones. Our guide to what cancellations and no-shows mean for pricing covers how to read them.
- Keep the weekly view short. A short weekly check of the next 14 and 30 nights catches most of the decisions that lead time makes urgent.
Lead time is a property's own fingerprint. A coastal holiday park, a city business hotel and a wedding venue can all sit at 90% occupancy with completely different booking windows.
What should you do this week?
- Export 90 days of reservations with created date, arrival date, status, channel and rate.
- Calculate lead days and band them as above, for confirmed bookings only.
- Find your median and the share within 7 and 14 days. Write them at the top of your weekly rate sheet.
- Compare the rate paid by band. If late bookings pay the same as early ones on full nights, flag it.
- Check your cancellation share and how many cancellations come in the final week.
- Add lead time to your weekly review. Our weekly 20-minute hotel rate review template shows where it fits.
Our take
Lead time tells you which rooms a rate change can still reach, and that is most of what makes a pricing decision useful.
In this worked example, half of all confirmed bookings come within two weeks and 14.3% within three days, on a park that is full most nights. The question for the GM is simple: are those last cabins selling at a price that reflects how full the night already is?
Frequently asked questions
What is a typical hotel booking lead time?
It varies widely by property, location and guest mix, so the useful figure is your own. In the worked example, the median confirmed booking was made 14.5 days before arrival, with half falling between 6 and 30 days.
Should I use the mean or the median lead time?
Use the median. A few bookings made many months ahead pull a mean upwards and hide the fact that most guests book much closer to arrival. Add the 25th and 75th percentiles to show the spread.
Do cancellations change the lead time picture?
Yes. Cancelled bookings free rooms close to arrival, and those rooms then sell as last-minute inventory. Track cancellations separately and note how many come in the final week before arrival.
Should last-minute rooms be cheaper or more expensive?
It depends on how full the night is. On a nearly full night, the last rooms are scarce and many properties price them higher. On a quiet night, a late offer may help fill a room that would otherwise stay empty.
How often should I recalculate lead time?
Every quarter is usually enough for the overall profile, and before any major season or event. Booking windows can shift with school holidays, events and the mix of guests, so recheck when the calendar changes.
Lead time tells you when your rooms sell. RevPARGenius shows what nearby properties are asking for the same nights, so your last rooms are priced against a real reference.
Data sources: RevPARGenius worked example (synthetic reservation sample and nightly file for a fictional 40-cabin NZ holiday park, stays in the 90 nights from 14 Oct 2026; market middle column is an illustrative assumption). Analysis run October 2026. Last reviewed October 2026. RevPARGenius is a hotel market intelligence platform. It is not affiliated with any online travel agency or hotel chain.
Research methodology and disclosures: Market figures in this article are calculated by RevPARGenius from room rates publicly displayed on online travel agency (OTA) channels, on one search basis (1 night, 2 adults, 1 room, cheapest offer shown). We publish a market figure only where at least 15 properties were priced. The figures are advertised asking prices. They do not show occupancy, bookings, negotiated corporate rates or revenue achieved. Worked examples marked as synthetic use invented data. This article is general information, not pricing advice: each hotel sets its own rates independently. RevPARGenius and CloseMode are commercially affiliated platforms.
