Pricing fairly and competitively is a challenge when you don't know where and when your planes will be needed most. Your knowledge of the market is only as good as your model of it.
"We’re leaving money on the table because our mental models no longer work in such a dynamic environment” said Brad Stewart, XOJET's Chairman and CEO at our very first customer meeting.
We're the number one on-demand private jet company, we're a dominant player. In two or three months, our partner Noodle.ai gave us the ability to be razor-sharp in terms of the data, the insights, and then the action plan.
It’s not enough to depend on internal data for solutions to this problem when your service depends on accurate demand forecasting. XOJET and Noodle.ai created a strategy that pulled internal data, human domain expertise, internal industry knowledge, and external data signals together. Doing this allowed XOJET to better sense market demand ahead of time, ensuring more accurate deployment of assets. This, in turn, created better pricing models based on real data in real time. Better pricing models and demand forecasting creates more stability in availability and consistency in scheduling for customers.
Enter Noodle.ai. Our Demand Signal AI application mines data from XOJET's revenue management system and blends it with sources like ARGUS and industry events to construct a demand signature for each day. The application uses historical bookings and conversion rates to generate price elasticity coefficients, then constructs a pricing curve for each type of demand signature. This empowers revenue management to dynamically price and schedule.
Using our application, XOJET implemented dynamic pricing based on predictive demand forecasts from region to region, leading to increased revenue and reduced deadheads.