Next-generation Revenue Management from Sqills brings early demand signals to rail and bus operators
The next-generation Revenue Management from Sqills gives operators access to data they normally can’t see, by capturing early demand signals that show up even before demand is reflected in initial patterns and booking curves.
Revenue management has helped rail and bus operators fill more seats for decades, by predicting demand and setting the best price for each seat. However, most systems still predict demand relying mostly on past bookings. Sqills takes this a step further, providing early demand signals that are normally hidden from revenue management systems.
This is possible because the next-generation Revenue Management from Sqills is native to S3 Passenger, where reservations, tickets, timetables, inventory, fares and customer data already live. This gives it direct and real-time access to richer and broader data, not just past bookings. S3 Passenger handles around 10.5 billion journey searches a year, providing operators with valuable data that is usually not accessible to standalone revenue management systems.
“Most revenue management systems rely on bookings to forecast demand. Our solution takes revenue management to the next level, by working with look-to-book data, journey searches and cart abandonments. This allows operators to see the demand build up while it’s still forming. They have more data to extract new insights from, and can act faster and more accurately to optimise booking curves. After all, a revenue management solution is only as good as the demand signals it can capture, and how quickly it can act on them,” said Kasper Walraven, Chief Commercial and Delivery Officer at Sqills.
The new Revenue Management module from Sqills will offer features such as:
- Real-time price optimisation – until the very last minute. Because it’s native to S3 Passenger, the module has real-time access to the operator’s data and can optimise prices until the very last minute before departure.
- Demand forecasting beyond single departures. The module forecasts demand for every single origin-destination and type of seat, based on modelling actual traffic patterns across the network.
- Access to hidden data patterns. Providing proper look-to-book data to model how the addressable market behaves, and optimise accordingly.
- Continuous pricing. It identifies the optimal prices based on the current addressable market and forecast demand, making sure they are shown at the right moment, for the right passenger, every single minute of the day.
Sqills’ Revenue Management module was built from the ground up, and it’s a natural next step for S3 Passenger, which has been providing Inventory Management for 20+ years, currently serving 60+ operators worldwide. The platform also includes dynamic pricing features to help operators set up pricing based on multiple input variables. Now, the module, with its AI and machine learning enabled forecasting, works with the rest of the platform to equip operators with a feedback loop to provide continuous pricing, improved yield and revenue optimisation.
With the right dynamic pricing strategies and revenue management solution, operators typically see revenue uplifts of 5-15%, by optimising based on broad demand signals and acting on them as they happen. All this in one single platform, instead of running separate systems that see less and move slower.
As a result, operators achieve higher load factors for their trains and buses, and more revenue from every sold seat.
