Case study · anonymised
Mid-market hotel: pre-arrival auth drops no-shows from ~7% to ~3%
Mid-market property, ~80 rooms, urban location, mixed direct-and-OTA booking mix, pre-mitigation no-show rate ~7% (above typical 3-5% band)
The challenge
The property was running a high no-show rate driven primarily by direct pay-at-property bookings and a permissive cancellation policy. The team had tightened the cancellation policy modestly but did not want to make the property uncompetitive on flexibility. The financial impact was meaningful: at 80 rooms, 7% no-show on roughly 65% occupancy implied roughly 1,300 lost room-nights per year.
The approach
The team layered automated pre-arrival payment authorisation on top of the existing booking flow. The integration: at booking, a EUR 1 validation hold confirms the card works; 48 hours before arrival, the full one-night authorisation runs through the PMS payment gateway. Cards that decline trigger a guest message via the guest-journey platform with a payment-update link. The property kept the flexible cancellation policy but added a clear no-show fee tied to the authorisation. Stripe handled the auth-then-capture flow; the PMS posted the hold release automatically.
Measured outcomes
No-show rate
Before: about 7% pre-mitigation
After: about 3% post-mitigation by end of first quarter
Annual room-nights recovered (estimate)
Before: n/a
After: roughly 750 room-nights recovered at the new rate
Guest friction (complaints flagged at front desk)
Before: n/a (no auth)
After: minimal; pre-arrival message wording was the main lever
The failure pattern and the fix
The initial setup ran the full auth at booking, not 48 hours before arrival. About 12% of bookings failed at the booking step because of expired or low-credit cards, and the team lost meaningful direct revenue rejecting valid bookings. The fix was the two-step pattern: a EUR 1 validation hold at booking (card-works check only), then the full hold 48 hours pre-arrival (when the no-show window closes). Most processors support both calls; the PMS-native payment layer (Mews Payments and Cloudbeds Payments both do this) automates it.
What we took away
The 7% to 3% drop matches the band reported by D-EDGE research for properties moving from no-auth to authorised pre-arrival flows. The mechanism is not that the hold itself prevents no-shows; it is that the hold creates the option to enforce a no-show charge, which alone changes guest behaviour because the booking now carries a financial commitment. The platform choice mattered less than the timing of the auth (booking vs 48h pre-arrival).
Anonymisation note
This case study uses anonymised property data: segment, room-count band, market region, and outcome metrics. The property is not named. Operator-reported figures are presented with that framing; published industry benchmarks are cited inline.