Page 151 - Building Big Data Applications

Chapter 8 Travel and tourism industry applications and usage 149

Real-time conversion optimization

By leveraging internal and external data, hospitality businesses can achieve razor sharp
targeting, reduce customer acquisition costs, and increase customer lifetime value.
The best partdall of this can happen in nearly real time.
According to Skift, companies’ leveraging traveler data tends to:

Reduce customer acquisition costs by 21%.
Generate a 17% increase in hotel/vehicle reservations.

By pairing internal marketing data with external sources, hotels can improve
operations even further. The simplest example would be leveraging weather data to
adjust the current offerings and estimate the possible bookings. A skiing-based property
can proactively outreach to customers with personalized offers whenever more snow is
expected. Or, on the contrary, pitch additional leisure activities and offers to guests when
not much powder is available on the slopes.
More analytics with data will lead you to capitalize on micromoments happening in
nearly real time. A popular midtier hotel chain estimated that around 90,000 passengers
in the United States were stranded every day due to flight cancellations. Their marketing
teams developed an algorithm to track flight disruptions in real time and trigger targeted
mobile search ads for nearby property locations. This “micromoment” based campaign
generated a 60% increase in bookings.

Optimized disruption management

Today weather and disruptions caused by the same to travelers is an everyday and
multiple times in a day occurrence. In this realm of affairs, data science is a powerful tool
to deliver instant help and response to affected travelers. The algorithms can be trained
to monitor and predict travel disruptions based on the information at handdweather,
airport service data, and on-ground events such as strikes and so on.
The application will be executed 24 7 365 and the system will be trained to alert
travelers, staff, and management about the possible disruptions and to create a
contingency action plan in response.
The same application can be executed at the travel agency, and it will setup chatbots
and automatically assign personal assistants who will be able to assist affected travelers
and help them adjust their travel plan. According to a PSFK travel debrief survey, 83% of
industry experts say that control over their own travel experience through real-time
assistance will be very important for travelers. Airlines can also ramp up their
disruption management plans with the help of data analytics.
A leading Australian airplane company was among the early adopters of a third-party
schedule recovery system, driven by neural networks and machine learning algorithms.
The system was used to report inclement weather and predict potential cancellation of
flights. The system once put into production helped them reduce the number