Data analytics for understanding passenger behavioural trends and impact on non-aeronautical revenues
Data analytics to identify passenger behaviours
Date: 4 December 2018
This presentation will analyse how the fusion of airport-related information and data sources can achieve the segmentation and identification of airport passenger behavioural patterns by applying Big Data management paradigms and analytics. This is achieved via the use of a combination of passenger descriptive models and flight schedules, which enables the prediction of when each segment of passengers (business, economy, groups, domestic, international, etc.) will arrive at the airport, what the identified flow patterns are within it, and how these can be used to analyse and assess the impact to non-aeronautical revenues.