Free tool
Hotel PMS ROI calculator
Estimate the annual revenue lift you would expect from a hotel-software change, on your own numbers and your own assumed uplift. No email gate, no fabricated multipliers.
Interactive · You control the assumptions
Hotel software ROI calculator
Plug in your property numbers and the uplift you think a better-integrated stack would deliver. The output is your scenario, not our claim. The assumptions section below explains how the numbers connect.
Your scenario
Current annual room revenue
Annual lift at your assumption
Per-room per-month equivalent
This is your assumption, not our claim. We do not promise a specific uplift; we let you set one.
How the numbers connect
- Annual room revenue = rooms × 365 × occupancy × ADR.
- Annual lift = annual room revenue × your assumed uplift %.
- Per-room per-month equivalent = annual lift ÷ rooms ÷ 12.
Background reading on hotel-technology ROI ranges: Hotel Tech Report industry trends. Use that as context for choosing your own assumed uplift; do not assume any specific number.
How to read the result
The lift figure is what your current annual room revenue would grow by IF the uplift you set were realised in practice. Whether that uplift is realistic depends on which workflows the change actually addresses (rate optimisation, channel mix, upsell, no-show reduction, post-stay review volume) and how cleanly they integrate with the rest of your stack. There is no neutral "industry average" we can defensibly pin here, so the calculator hands the assumption back to you.
What drives RevPAR uplift in practice
- Rate optimisation — dynamic pricing or rules-based adjustments that capture demand peaks the manual desk misses.
- Direct-booking shift — fewer OTA commissions when the booking engine and post-stay flow nudge return guests to the website.
- Upselling — pre-arrival room upgrades and add-ons the front desk does not have time to ask about manually.
- No-show reduction — pre-arrival authorisation flows that cut last-minute no-shows. Real operator data points (anonymised) are reported as roughly 3–4 percentage points of no-show-rate reduction in the first quarter after deployment.
- Operational hours saved — front-desk time not spent on repetitive guest messages and check-ins, redeployed to revenue-generating activity.
Comparison content
If you are weighing this calculation against a specific platform, the head-to-head comparisons walk through where Guestivo replaces a spend line versus where it adds one alongside an existing system: Guestivo vs Cloudbeds, Guestivo vs Mews, Guestivo vs RoomRaccoon.