Travel & transportation
Passenger demand forecasting
Anticipate passengers by route, station, flight, departure, and fare class.
Sound familiar?
- Full services turning passengers away while others run near empty
- Crowding discovered on the platform, not in the plan
- Disruptions that redistribute demand faster than operations can react
Passenger journeys
passengers / hour · Live forecast
Driver
Bookings
Driver
Searches
Driver
Schedule
Forecast horizon
Hours–26 weeks
Refresh cadence
Hourly or daily
Built for
Network planning · Revenue management
What you can predict
One forecast can answer several operational questions.
Use bookings, searches, service schedules, fares, weather, events, and disruption history to predict load and crowding throughout the network.
Passengers by service
Load factor
Station entries
Crowding risk
Questions teams need answered
- Which services will be full?
- Where will crowding occur?
- How much demand will shift after disruption?
- Which departures need more capacity?
Data that can improve the forecast
Start with the history you already have. Add internal or external drivers only when backtesting shows that they improve the forecast on held-out periods.
What-if planning
Test a change before committing to it.
Compare a proposed change with the current baseline. See the expected direction, timing, range, and the assumptions behind the result.
Add capacity to a departure
Estimate displaced demand and load factors
A route is disrupted
Forecast passenger redistribution
Passenger journeys
passengers / hour · Scenario comparison
What if
Add capacity to a departure?
Driver
Bookings
Driver
Searches
Driver
Schedule
From forecast to action
Keep the people making the decision in the loop.
01 · MONITOR
Forecast continuously
Refresh passenger journeys on a hourly or daily cadence as new data arrives.
02 · NOTIFY
Alert on meaningful changes
- Passenger demand exceeds capacity
- Crowding risk crosses a threshold
03 · DECIDE
Put the result to work
From the handbook
How the forecast is actually built.
Guide
Occupancy and travel demand
A hotel night and a flight seat perish at midnight. The forecast is pickup along a booking curve, not only yesterday’s occupancy. Price is a lever you set; remaining capacity is the constraint. Those two belong in the same conversation.
Guide
What is demand forecasting?
Demand forecasting estimates how much of a product or service people will want in a coming period, so you can buy, staff, and price before the rush — not after it has already walked in.
Guide
Time series forecasting, explained
Time series forecasting predicts the next values of something that was recorded in order — sales by day, load by hour, tickets by week — by learning from its own past, and from anything that regularly moves with it.
Build a passenger demand forecast with your data.
Start with sample data, connect your own history, or talk with us about your target, horizon, and production requirements.