We helped a leading European Cruise Ferry automate and fool-proof their processes around passenger booking, flex pricing and vehicle management, and demand forecast.
In 2018 a European cruise ferry company looked for assistance with pricing and improved management of demand forecasting to enhance their efficiency of utilizing available capacity on their sailings. Expanding the price ladder to offer a wider range of flexibility in fares meant that constraints as to fixed pricing per season could be removed, and sailings managed individually based on their specific demand.
The Problem
Without automation, managing the number of price points across different products and seating configurations would require significant effort, and additional headcount, and still allow missed opportunities due to human error.
The Challenge
Covid severely delayed the final interface development which would provide full 360 communications between RTS Velocity and the booking system, But with its launch in 2021, the client was able to fully utilise the functionality offered by the new pricing structure, and the automation required to implement this. This was achieved without disruption to existing booking processes or demand.
Our Solution – RTS Accelerate
As part of the decision process, detailed studies on potential ROI, cost, cost savings, and resource savings were conducted, which justified the selection of the RTS Velocity solution. Several aspects were considered in the decision process, particularly RTS’s experience and history in the cruise ferry market, as well as the range of features specifically designed to address the cruise ferry industry challenges.
Our Process
Implementation commenced late 2018 with RTS project managing the process, initiated with the preplanning and scoping study. Price structure changes were identified and agreed, and relevant interfaces with the bookings systems specified.
Since the booking system provider schedules for data provision and interfaces were longer than initially envisaged, alternative approaches to obtaining historical data were implemented, which allowed for an extended calibration period whilst live feeds were developed. This allowed the client time to understand the data in detail, and based on the analysis make some modifications to the pricing structure prior to production launch.
The Results
The client is now able to manage passenger, vehicle and accommodation demand and pricing, and is able to flex pricing across a much larger range than was previously feasible, all on a fully automated basis.
