Solutions
- Airlines
  - Amadeus for Airlines
  - Products
- Airports
  - Amadeus for Airports
  - Products
- Border Authorities
  - Amadeus for Border Authorities
  - Products
- Corporate Travel & Expense
  - Products
  - Capabilities
  - Integrations
    - Travel & Expense Solution for Microsoft Teams
- Travel Sellers
  - Products
  - Content
- Hospitality
- Payments & e-invoicing
  - Outpayce
  - Voxel: B2B Payments and e-Invoicing
- Traveler behavior is changing at every touchpoint.
  
  Explore bold ideas, lead with cutting-edge tech, build powerful partnerships, and contribute to lasting impact.
  Discover more
Support & Training
- Support
- Training
- Already a customer?
  
  Log into Amadeus Service Hub for product news, learning materials, and customer support.
  Login
Partners
- Amadeus Partners
  
  At Amadeus, we value strong partnerships with different players across the travel ecosystem. Gain access to our solutions to develop your portfolio, reach new customers and add to your bottom line.
- Landmark partnership between Amadeus and Google Cloud
  
  Learn how this collaboration strengthens Amadeus' multi-cloud approach and AI innovation to improve efficiency, reliability and growth in travel.
  Read more
Resources
- Trending Topics
- Connected journeys: How will technology transform travel in the next decade?
  
  From AI-driven planning and biometric check-ins to smarter disruption management.
  Read the report
- Six travel trends that will redefine how we travel in 2026 and beyond
  
  Amadeus, in collaboration with Globetrender, unveils the tech, policy and innovation coming to transform the face of travel.
  Discover now
Company
- About Amadeus
  - About us
  - Leadership
  - Awards
  - Locations
- Careers
- Innovation
- Sustainability (ESG)
  
  Learn how we’re working to make travel a force for good.
- Amadeus Global Report 2024
  
  Get an overview of our company in 2024 from a business, financial and sustainability perspective.
  Access report
- Latest financial results
  
  Amadeus published its financial results for Q3 2025.
  View the results

Blog

5 more examples of predictive analytics in the travel industry

April 14, 2016

Last updated: July 17, 2018

2 min read

Available in other languages

EN DE

Rodrigo Acuna Agost

Head of AI Research, Amadeus IT Group,

Share it!

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:

Dynamic offers of travel products

Travellers are increasingly searching for personalised experiences. Without predictive analytic this task is impossible. In few milliseconds systems need to predict what the customers wants and then adapt the offer accordingly. For example bringing together a flight, extra baggage, a hotel, while also slightly adapting the price dynamically and considering competitors offers in real-time.

Segmentation and clustering of passengers

A basic segmentation of travellers is based on their trip purpose (e.g., leisure or business). This is a well-known driver to explain customer behaviour (e.g., price sensitive vs product quality) and then used to adapt travel products accordingly. Supervised classification algorithms can be used to segment people in well-known classes. On the other hand, clustering algorithms permit discovery of new kinds ofbehaviours; the ones that cannot be classified by hand easily. This is akey feature to segment customers from new generations and dissimilar cultures.

Fraud Detection

There are more than 3 billionair passengersper year worldwide. This generates a large number of online transactions that need to be validated in real-time. The losses coming from fraud in payments and other related transactions are significant. Predictiveanalytics playan important role detecting frauds and even cyber-attacks on travel systems. The main challenge on these kinds of applications is to balance the trade-off between the number of "true" detected issues against the "false positive" cases. You may know cases of credit card rejections when traveling abroad, well...this is a "false positive" that should betaken into accountto improve these algorithms.

Passenger and other travel data enrichment

Analysis of records coming from different travel systems have shown that data is not as rich as we would like: many database fields are not commonly filled (e.g., large presence ofmissingvalues). Similarly there is other important information that is not coming from raw data and are available only by integrating other data sources. Predictive analytics is useful to infer missing data and also matching different sources bringing new capabilities to travel systems.

Forecasting (eg., for revenue management systems and demand analysis)

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"), whathappensif an airline move their flight from 9:00AM to 8:00AM? Whatis 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?

TO TOP