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A last-minute discount is a price cut that applies automatically when a guest books close to check-in. On Airbnb you can set it for any window from 1 to 28 days before arrival, alongside its minimum stay restrictions.
In PriceLabs you set it under Last Minute Prices. The tool now decides the size of the cut from live market data unless you override it, following its own last-minute options.
Get this wrong and you give away money on nights that would have sold anyway. Get it right and you fill the gaps that would otherwise stay unbookable without dragging your average rate down. This guide covers the decision, the exact setup on both platforms, and how to check afterwards whether the discount paid for itself.
It is a rule, not a one-off price change. You tell the platform how close to arrival a booking has to be, and by how much to drop the rate. The system applies it to every open night in that window. This is one of the oldest levers in how dynamic pricing works for short-term rentals.
The opposite rule is a last-minute premium. You raise the rate as check-in approaches instead of lowering it. That is the right call in a market where supply runs out before demand does, and it is one of the pricing mistakes worth avoiding to assume otherwise.
Both are the same setting. Only the direction changes.
Three things decide it. Demand in your market, how much supply is still open, and when your guests actually book. Work through them in that order, because the third one changes the answer more often than hosts expect. Each is a standard input in vacation rental revenue management.
An empty calendar is not evidence of weak demand. It might be evidence that your listing is priced above the market, or buried in search results. Pull the market view first and see whether everyone nearby is empty too, which is what a market dashboard is for.
If the whole market is soft, a discount will not create demand that is not there. It will hand a cheaper rate to the few guests who were going to book regardless, and it will drag your occupancy rate up for the wrong reason.
Count the comparable listings still available for the dates you care about. If there are plenty, a discount improves your odds of being the one that sells. If almost everything is gone, raise the rate instead. Guests with few options pay more, which is why watching competitor rates beats watching your own calendar.
You need a defined comp set of similar listings to read this properly. Comparing a two-bedroom cabin against studio apartments will give you a number that means nothing.
Your booking window is the gap between when guests book and when they arrive. If your typical guest books 21 days out, a discount that starts at 7 days is arriving after the decision has already been made.
Look at your last twelve months of reservations and find the point where most bookings land. Set your discount window to start slightly before that point, not after it. Your core rental KPIs will show you where the cluster sits.
Seasons shift this. A ski property books months ahead in January and days ahead in April, so check your seasonal profiles rather than assuming one window works all year.
If you have decided that holding your rate is the better move, the playbook on protecting ADR instead of cutting rates covers the alternatives in detail, including stay restrictions and merchandising.
Airbnb keeps this in the pricing settings for each listing. The discount applies to reservations booked between 1 and 28 days before check-in, and you can stack more than one tier. It sits near the other listing settings worth reviewing.
A common setup is 10 percent inside 14 days and 20 percent inside 3 days. That gives you a gentle nudge early and a stronger one when the night is nearly worthless. Pair it with a sensible base price for the listing so the percentages come off a number that made sense to begin with.
The last-minute discount is not available while Airbnb Smart Pricing is switched on. If you cannot find the option, that is usually why. You can still apply one to specific dates through a rule set, which behaves much like date-specific overrides do in PriceLabs.
The second rule is a visibility one. At 10 percent or more, Airbnb strikes through your original rate and flags the deal in search results, the way a well-set base price shapes everything below it. Below 10 percent the guest sees a lower number but no signal that it is a discount.
That visibility flag matters given how the Airbnb algorithm surfaces listings.
That threshold is worth planning around. A 9 percent discount costs you revenue and buys you nothing extra in visibility.
Airbnb is not the only place to do this. Promotions and special offers work differently and can be combined, and Booking.com and Vrbo each have their own equivalents.
PriceLabs handles this under Last Minute Prices in the customizations panel. The default changed with the newer algorithm, so anything you read before 2025 is likely describing the old behaviour. The customization hierarchy decides which rule wins when two overlap.
If your listing runs on Hyper Local Pulse, the default is Market Driven (Balanced). It applies the same last-minute movements PriceLabs observes across your competitors, and the numbers change day to day as the market moves. That comes from the same neighbourhood market data behind your rates.
Listings still on the old algorithm get PriceLabs Determined instead, which is a gradual 30 percent discount over the next 15 days. You have to move to Hyper Local Pulse before the Market Driven options become available.
Market Driven comes in three strengths. Balanced matches your competitors, Conservative discounts less than that, and Aggressive discounts more.
Most people should start on Balanced and only move once they have data, not after one slow week. A data-led approach to management beats a reactive one here.
If you want to set the numbers yourself, four options replace the automatic one. The maximum window for any custom last-minute setting is 90 days, which is far wider than the 28 days Airbnb allows. These sit with the rest of the pricing customizations.
Gradual is the one most operators land on, because it mirrors how the value of a night actually decays. The research on last-minute and far-out pricing shows that decay is steeper in some markets than others.
Here is the detail that trips people up. You cannot build a tiered structure inside Last Minute Prices. If you want different discounts at 30, 14 and 7 days out, that is the Step Last-Minute Discount profile inside occupancy based adjustments.
Occupancy based adjustments look at how full your own calendar is, not just the market. That makes them the better tool when your performance is out of step with everyone around you, or with the rest of your comp set. They are also the home of off-season booking tactics.
There is a separate Minimum Last Minute Price that applies only inside your last-minute window. You can set it below your normal minimum to fill aggressively, or above it to stop the discount cutting into a night that still has a chance. It works much like a pricing offset in that respect.
Set this before you set the discount. It is the difference between a controlled markdown and a rate that runs away from you, and it works alongside the other advanced minimum price settings.
One more interaction to know. If a night is both an orphan night and a last-minute night, and both rules are discounts, PriceLabs applies the larger of the two rather than stacking them. The guide to filling orphan gaps covers that setting on its own.
Nothing here is permanent. You can change any of it from the pricing calendar and see the effect on your rates before anything syncs to the channels.
Working out your own numbers takes about ten minutes with your booking history open. The setup sheet below walks you through it and gives you the four values you need to type into PriceLabs, including your minimum stay position and your floor. It is quicker than working through every customization. Send it to whoever on your team owns pricing.
Fill in one row per property, or one per group if you manage similar units together. It pairs well with the wider customization and goal tracking approach.
Step 5 is the one people skip. A discounted night that does not cover the cleaning cost of the turnover is worse than an empty night, because an empty night costs you nothing to service.
Occupancy is the wrong metric here. A discount will almost always raise occupancy, which is exactly why it feels successful when it is not. Watch RevPAR, which is your revenue divided by every night you had available, whether it sold or not.
If RevPAR goes up, the discount bought you nights you would not otherwise have sold. If RevPAR is flat or down while occupancy climbs, you discounted nights that were going to sell anyway. That pattern shows up most often in shoulder season.
Give it a full booking cycle before judging. Two weeks tells you nothing.
Compare against the same period last year rather than last month, because month-to-month movement is mostly seasonality rather than anything you did.
Watch your average rate alongside it. The pairing of occupancy against ADR tells you more than either number on its own, and a healthy last-minute strategy moves occupancy up without moving ADR much.
If the numbers stay bad across a full cycle, the problem is probably upstream of pricing. Check whether it is a demand problem or a listing problem before cutting further.
Start it just before your median booking lead time. If most guests book around 21 days out, begin the discount at 24 or 25 days. Starting later means the discount arrives after most people have already chosen. Starting much earlier discounts nights that had plenty of time left to sell at full rate.
You can, but they compound. Airbnb takes its percentage off the rate PriceLabs has already reduced, so a 20 percent PriceLabs discount plus a 20 percent Airbnb discount lands near 36 percent off. Pick one place to control the last-minute logic and switch the other off.
Airbnb Smart Pricing is almost certainly turned on. The two features cannot run together on the same listing. Turn Smart Pricing off and the discount option reappears in your pricing settings. You can also apply a last-minute discount to specific dates using a rule set instead.
It depends on your algorithm. Listings on Hyper Local Pulse default to Market Driven (Balanced), which follows what competitors are doing and changes daily. Listings still on the old algorithm default to a gradual 30 percent discount spread over the next 15 days from today.
A 10 percent or larger discount usually helps visibility, because platforms flag the deal in search. Repeated deep discounting is the risk. It trains your market to wait and it drags the whole area down, which is why the floor price in step 6 matters.
Setting the rule takes five minutes. Working out the right numbers takes an hour with your booking data, and it is worth the hour. Start with the setup sheet, then check your configuration against the Last Minute Prices documentation.
If you manage a larger portfolio and want the distribution side of this rather than the settings, the guide to filling calendar gaps without losing ADR covers specialised last-minute channels.
And if you are setting this up for the first time across many listings, the step by step setup walkthrough covers the order to do things in.
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