Now Live in Van der Valk Hotels

Know which bookings
will cancel before they do.

Occupado scores every reservation with a cancellation risk percentage — updated daily. Your revenue team stops reacting and starts deciding.

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40-day pilot No contract No setup fee
High-risk flagged
J. Martens · arrival in 6 days · 82%
occupado — today's risk report
Tonight's arrivals 12 bookings
JM
J. Martens
2 nights · 1 adult · €243
82%
SW
S. De Wolf
1 night · 2 adults · €189
51%
AV
A. Vandenberghe
3 nights · 2 adults · €410
12%
3
High risk
€1.2k
At risk
80%
Accuracy
Deposit collected
€380 secured from at-risk booking
Trusted by Van der Valk Hotels
Van der Valk Mechelen Van der Valk Brussels Airport
Real hotel data — Belgium
Cancellation rate — EU average 28%
No-show rate — EU average 11%
At-risk revenue flagged early +76%
€476k
lost per year
at a real Belgian hotel
The problem

Every empty room is money you'll never recover.

The average European hotel loses 15–30% of bookings to cancellations and no-shows — and most revenue managers find out on the day the guest doesn't arrive.

See which bookings will cancel 2–6 weeks before arrival

Collect deposits from high-risk guests before they walk away

Oversell strategically — recover no-show revenue without walking guests

Works with your existing PMS — no IT project, no API required

What you get

Built for revenue managers
who want to outperform every competitor

From individual booking scores to full-portfolio analytics — Occupado fits how hotels actually work.

Per-booking risk score
Every reservation gets a 0–100% cancellation probability — calculated from 12 booking signals and updated whenever details change. No guesswork, no spreadsheets.
Risk factors
Lead time
72
Prev. cancellations
55
Special requests
20
Rate
38
J. Martens — 82% risk Arriving in 6 days. Deposit not collected.
K. Pieters — 54% risk 3-night stay. 2nd cancellation this year.
Van Dyck family — 11% risk Repeat guest. No action needed.
Daily risk alerts — no dashboard required
Your revenue manager gets a clean daily email with every flagged booking. Sorted by risk, annotated with context. Read it with your morning coffee, act before noon.
Overbooking optimizer
Know exactly how many rooms to safely oversell each night. Occupado calculates the predicted no-show count based on your historical patterns — so you can fill every room.
Room availability — Fri 28 Mar
Booked
At risk
Safe oversell
How it works

Live in days,
not months.

No developers, no IT project. Occupado connects to your existing PMS workflow in an afternoon.

01
Export your PMS
Download your booking data from Shiji, Opera, Mews or any system. Standard Excel export — no API setup needed.
02
Occupado scores each booking
Our model processes 12 risk signals per booking and returns a cancellation probability in under 60 seconds.
03
Your team gets the report
A clean daily email lands in your revenue manager's inbox. Red flags at the top, context included, no dashboard required.
04
Revenue recovered
Deposits collected, rooms safely oversold, no-shows predicted. Empty rooms become booked rooms.
80.5%
Prediction accuracy on real Belgian hotel data
€476k
Annual revenue at risk per Belgian hotel tracked
123k
Real bookings used to train the scoring model
40
Day free pilot — no contract, no commitment
"

Occupado flagged three high-risk bookings on a Tuesday morning. By Thursday we had collected deposits on all three. One of them cancelled Friday — we kept the deposit. That's exactly what a revenue tool should do.

Revenue Manager
Van der Valk Hotel Mechelen  ·  Pilot participant
Live demo

See exactly how it works.

The same dashboard Van der Valk Mechelen uses every morning.

occupado.up.railway.app/dashboard
Van der Valk Mechelen
JM
J. Martens
Arriving today · 2 nights · Booking.com · €243
82%
AI Analysis — why this booking is high risk
Short lead time (4d)
+78
No deposit collected
+62
1 prev. cancellation
+44
Repeat guest
−22
LD
L. De Smedt
Arriving today · 3 nights · Booking.com · €312
77%
KP
K. Pieters
Arriving today · 1 night · Direct · €189
54%
AV
A. Vandenberghe
In house · dep 29 Mar · Corporate · €410
12%
2
High Risk Today
€555
Revenue at Risk
85.6%
Model Accuracy
0
high-risk bookings in the next 6 months
0
≥70% risk
0
40–69% risk
0
<40% risk
High-risk arrivals by month
Apr
May
Jun
Jul
Aug
Sep
Top 20 High-Risk Bookings
Sorted by cancellation probability · Updated daily
#GuestArrivalNightsChannelRisk %
1J. Martens28 Mar2nBooking.com82%
2L. De Smedt28 Mar3nBooking.com77%
3R. Claes2 Apr1nDirect74%
4S. Wouters5 Apr2nBooking.com71%
5K. Pieters28 Mar1nDirect54%
20 rows · occupado_highrisk_20260328.xlsx
Get started

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No contract. No setup fee. Your first 40 days are completely free.

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Joining hotels across Belgium and the Netherlands.