Free Tool

Hotel Demand Forecast Tool

Generate a 30-day occupancy demand curve based on seasonality, events, lead time, and market signals. See how Propeter’s AI forecasting engine thinks — powered by XGBoost + LSTM methodology.

90-Day

Forecast Horizon

XGBoost

+ LSTM Ensemble

6 AI Agents

Orchestration Pipeline

±4.2%

Mean Absolute Error

Forecast Parameters

Configure your property and market signals

Property Type

Base Historical Occupancy 68%

20%60%100%

Season

Market Competitiveness Medium

LowMediumHighly Competitive

Demand Signals (select all that apply)

Major Conference / MICE in Market Sporting Event / Concert Public Holiday Week Favourable Weather Forecast Active Hotel Promotion Running Competitor Hotel Unavailable / Sold Out

Average Lead Time (days out) 21 days

Same-day30d90d

Total Room Count

📊

Your Forecast Appears Here

Configure your property parameters on the left and click Generate to see a 30-day occupancy demand curve with AI signal breakdown.

How Propeter's AI Forecasting Engine Works

Six specialised AutoGen agents collaborate to generate a demand forecast — not a single black-box model.

Agent 1

Data Ingestion Agent

Pulls PMS history, OTA pace, web bookings, competitive rates every 4h

Agent 2

Market Intelligence Agent

Ingests Lighthouse rate data, web-scraped competitor pricing, event calendars

Agent 3

Demand Forecast Agent

XGBoost + LSTM ensemble: 90-day occupancy curve with confidence intervals

Agent 4

Price Elasticity Agent

Log-log model: calculates rate sensitivity at each occupancy decile

Agent 5

RevPAR Optimisation Agent

Solves RevPAR maximisation curve across occupancy vs. rate trade-off

Agent 6

Strategy Agent

Synthesises final recommended rate strategy, explains reasoning in plain language

Why Forecast?

Guessing Demand Is Costing You Revenue

Hotels that price reactively — responding to occupancy only after bookings come in — leave an average of 12–18% RevPAR on the table each month. Predictive demand forecasting lets you price ahead of the curve.

✔
Price before demand peaks — Raise rates 7–21 days before an event, not after rooms are gone
✔
Avoid panic discounting — Low-demand windows are identified early so you can launch targeted promotions
✔
Protect your floors — Guardrails prevent automated pricing from ever dropping below your minimum
✔
Quantify opportunity cost — See exactly how much revenue was left on the table last quarter

What Propeter Forecasts

Daily occupancy curve90 days out

Room-type demand splitPer category

Rate elasticity by datePer night

Competitor pace comparisonDaily refresh

RevPAR optimisation targetPer strategy

Cancellation risk scorePer booking

See Your Real 90-Day Demand Forecast

This tool uses simplified signals. Propeter’s live platform ingests your actual PMS data, booking pace, competitor rates, and local events to produce a property-specific 90-day forecast — updated every 4 hours.

Enhance customer engagement with our intelligent chatbot solutions. Seamlessly automate conversations and elevate user experiences with cutting-edge AI technology.