We’re creating a more connected travel industry, underpinned by sustainability and long-term investor relations.
Previously, I listed 5 ways the travel industry uses predictive analytics. These ranged from recommender systems to fraud detection and conversion optimisation. The travel industry also uses predictive analytics in a number of other capacities as listed below:
Historically, forecasting engines embedded in revenue management systems considered only past bookings. However, what happens if some elements are changed? (e.g., a new "fare family"), what happens if an airline move their flight from 9:00AM to 8:00AM? What is the impact on demand if the price of flight tickets increases 10%? New generation forecasting systems are based on “factors” (price, schedules, etc.) in addition to simply time-series, thus allowing them to optimise revenue.
What do you think? Are there other ways the travel industry could use predictive analytics?