Australian restaurants recorded a 1.41% no-show rate across 251,804 bookings in the year to July 2026, which works out at roughly 36 empty tables a year for an average venue. Skai Solutions uses measured booking outcomes here rather than the survey figures usually quoted, because the two measure completely different things and only one of them is a rate.
1.41%. That is the recorded rate across 251,804 reservations at 213 Australian restaurants between August 2025 and July 2026, published in the Resos No-Show Index 2026. It is lower than the global average in the same dataset, 2.33% across 3,768,761 bookings in twelve countries, and a long way below the numbers that circulate in hospitality media.
The gap is not because Australian data is flattering. It is because most quoted no-show figures come from consumer surveys that ask diners whether they have ever skipped a booking. That measures lifetime incidence per person. It is not a per-reservation rate and the two cannot be compared. Skai Solutions will not quote a survey number as though it were a rate, and neither should anyone selling you something on the back of it.
Two honest caveats before you use 1.41% anywhere. It is a recorded rate, so a staff member has to mark the booking as a no-show. Across the whole dataset only 72.9% of venues recorded a single one, and among venues that actively use the status the rate rises to 2.49%. Your real number is probably higher than what your system shows. And there is no New Zealand figure: New Zealand did not meet the publication threshold of 30 restaurants and 1,000 reservations, so any NZ number you see anywhere is an estimate, not a measurement.
A rate that small looks like rounding error until you multiply it by a year of trading. Three things make it bite.
It compounds nightly. The average restaurant in the dataset recorded about 36 no-shows a year, walking away from roughly 117 booked covers. Venues in the 500 to 999 bookings a month bracket ran at 3.17%, well above the average, because volume and rate move together.
It lands on your best service. The dinner no-show rate, 2.63%, runs 43% higher than lunch at 1.84%. Monday is the worst day at 2.69% and Wednesday the best at 2.09%. January is the worst month. The empty table is disproportionately the one you could have sold twice on a Saturday night.
No-shows are the visible half. The same dataset holds 566,049 cancellations, and 56% of them arrived within 24 hours of the booking or after it had already started. 7.1% landed after the start time, which for planning purposes is a no-show with paperwork. Counting both, venues lost about 405,000 tables in a year to guests who booked and did not come, roughly 168 per restaurant. If your policy only covers people who never call, it addresses less than half the problem.
One piece of received wisdom is simply wrong, and it is worth unlearning because it changes how you take bookings. Large parties do not no-show more. Parties of ten or more failed at 1.15%, against 2.63% for a table for two. But when a big table does go, it averages 13.44 covers against 1.96. Multiply the rate by the size and the ranking inverts: expected lost covers per booking is 0.154 for a party of ten or more and 0.051 for a table for two, so the big booking carries about three times the exposure. The right response is not refusing large groups. It is protecting them.
Do not use anyone else's dollar figure, including ours. Use four numbers you already have. This is Skai Solutions' own arithmetic, shown so you can put your own inputs through it.
| Input | Where to get it | Worked example |
|---|---|---|
| Advance bookings a month | Your booking system, not covers | 600 |
| No-show rate | Yours if you record it. 1.41% is the Australian recorded benchmark | 1.41% |
| Average covers per lost booking | Your average party size | 2.4 |
| Average spend per head | Total sales divided by covers | A$55 |
| Monthly exposure | 600 x 1.41% x 2.4 x A$55 | about A$1,117 |
Rate, party and cancellation figures: Resos No-Show Index 2026, 3,768,761 reservations at 2,417 restaurants, 1 August 2025 to 31 July 2026. Booking count and spend per head are Skai Solutions' assumptions for the worked example, not measurements. Substitute your own.
Then run it again with your recorded rate replaced by 2.49%, the rate among venues that actually mark the status. If the answer changes materially, your first problem is measurement, not diners.
1. Record the status properly. Free. You cannot manage a number you are not collecting, and most venues are not. Two weeks of disciplined marking will tell you whether you have a no-show problem, a late-cancellation problem, or neither. Most venues discover it is the second one.
2. Reconfirm the risky windows only. Cheap. The data points at where to spend the effort: bookings made 2 to 6 days ahead (2.67%), dinner service, Mondays, and parties of eight or more. Bookings made 30 or more days ahead are the safest in the dataset at 1.96%, which is the opposite of what most operators assume. Reservations with a delivered SMS reminder showed a 16% lower recorded no-show rate than reservations at the same venue without one. That is an observed association in operational data, not a controlled experiment, so treat it as a reason to try reminders rather than proof that they cause the difference.
3. Make releasing a table easy, then refill it. Since 56% of cancellations land inside 24 hours, the winnable version of this problem is not stopping the cancellation, it is reselling the table. A waitlist you can call through in five minutes is worth more than a sternly worded policy.
4. Deposits, last, and only on exposure. Bookings with a payment requirement recorded 0.80% against 2.47% without, but the publisher is explicit that this is a raw descriptive comparison and their matched study could not separate the feature from selection effects. Venues that take deposits are different venues. Apply deposits where expected lost covers are highest, which is large parties and peak service, and nowhere else.
Then the problem is probably not no-shows. Look at the bookings you never took. A venue turning 1.41% of confirmed tables into empty ones while the phone rings unanswered through service is losing more on the second count than the first, and only one of those losses appears in a report. A missed call leaves no trace anywhere in your system, which is exactly why it never gets managed.
That is the gap Skai Solutions works in: answering the calls your team cannot get to during a rush, taking the booking or the order, and handing over to a person when a caller needs one. If your phone mostly carries supplier calls and enquiries rather than bookings and orders, a basic message-taking plan is the right buy and it is not us. We would rather say that on a demo than sell you something that disappoints.
To turn an empty table into a dollar figure you need your own contribution margin rather than the menu price. A good food cost percentage for a restaurant works that out from the tax office bands, which put cost of sales at 32% to 39% of turnover for a small Australian restaurant. And if you are weighing a no-show policy against simply rostering another person, the Australian staffing numbers are not what most operators assume.
Two practical links between the two problems. First, a guest who cannot reach you to cancel becomes a no-show in your data even though they tried to do the right thing. Some share of every venue's no-show rate is really an unanswered phone at 5pm. Second, the reconfirmation call for a high-exposure booking is the single call most likely to be skipped on a busy day, because it is the one nobody is holding you to.
If you want the numbers on what covering the phone costs, they are published in full for Australia and New Zealand, with the wage comparison shown as arithmetic rather than a claim. If you are earlier than that and still working out what the category even is, start with what an AI receptionist does and does not do. For takeaway operators the relevant page is phone ordering into a POS, and the Australian market rates for the older alternatives sit on phone answering service cost in Australia.
Setup takes five days from the day you say go.
Most of these fixes start on the phone. Our guide to answering the phone at a restaurant has the six fields to capture on every booking call, in the order that makes a dropped call recoverable.
Somebody has to be there to take the cancellation. Restaurant receptionist duties and responsibilities covers who that is in a typical venue and where the role stops coping.
Fifteen minutes, your menu, your busiest Friday.
Book a Free DemoA large share of late cancellations arrive out of hours, which makes the recording that takes them part of your no-show plan. What your answering machine message should say covers how to word it so a cancellation actually reaches you.
1.41% of advance reservations, measured across 251,804 bookings at 213 Australian restaurants between August 2025 and July 2026 in the Resos No-Show Index 2026. It is a recorded rate, so the true figure is somewhat higher, because staff have to mark the booking.
Yes. Dinner ran at 2.63% against 1.84% at lunch in the same dataset, so dinner is about 43% worse. Monday was the worst day of the week at 2.69% and January the worst month at 2.62%.
No, they no-show less often: 1.15% for parties of ten or more against 2.63% for parties of one or two. But a large no-show averages 13.44 covers against 1.96, so expected lost covers per booking is about three times higher for the big table. Protect large bookings rather than refusing them.
Reservations with a delivered SMS reminder showed a 16% lower recorded no-show rate than reservations at the same venue without one. The publisher describes that as an observed association in operational data, not a controlled experiment, so it is a reason to try reminders, not proof they cause the improvement.
There is no published measurement. New Zealand did not meet the Resos publication threshold of at least 30 restaurants and 1,000 reservations, so any New Zealand no-show percentage you see is an estimate. Skai Solutions will not quote one as a measurement.
No, and that matters. In the same dataset 56% of cancellations arrived within 24 hours of the booking or after it had started, and 7.1% landed after the start time. A policy that only covers guests who never call addresses less than half the empty-table problem.