The perfect mobile booking flow, with the help of AI
In 1984 the world witnessed the launch of an Irish company that would shake the travel sector to its core. Ryanair was one of the first airlines that did not try to earn money by selling tickets, but with something else: ancillaries. Whether it’s extra luggage storage, an overnight stay in a hotel or a rental car: if Ryanair gets a fee for it, they’ll try to sell it.
Soon other airlines started copying this business model. In the race to offer the cheapest tickets, other revenue streams had to be explored. One of the most important things that caught the eye of the airline managers, was the sale of ancillaries. From hotel nights to an upgrade on the plane: the profit is more and more in these extras.
At In The Pocket, we are always searching to improve the ease of use in all our experiences. Crafting a good user interface can make the difference, especially when looking at transactional flows like booking a flight. In recent weeks we have analyzed the mobile booking flows of different airlines to see how they can boost the sale of ancillaries, offer better user experiences and propose the right info at the right time.
By gaining more knowledge about the user, airlines can succeed in doing this. It is of no use to suggest a customer to rent a car and book a hotel room and upgrade to business class and… We can help the user in the buying process by elevating on predictive UI, but in order to do that, all relevant variables must be correct.
Personal relevance: how?
To determine which flight or ancillary is most suitable, an airline can retrieve information from the various interactions that users have with their application. Three major domains determine that experience:
- The interactions with the product and company. Which trips has that customer booked before? Is it someone we should propose a convertible or just a family car? Should we give a discount? You can often retrieve this data from the profile that the customer has created when he downloaded the application.
- The context in which the interactions take place. Where is the user - physically as well as in the customer flow? Has he already booked his trip or not? Is he at home, on the go or maybe at the airport? This data is based on the flow itself and / or the location of the smartphone.
- The person himself. What are his emotions? What is his attitude towards specific topics? Retrieving this data is a lot more difficult. An option is to work with profiling based on social media - you can learn a lot from a Facebook connect. Another option is to create profiles yourself based on, for example, the behavior or, even more difficult, assess the stress level based on smartphone movements and vibrations.
By combining all this information, it becomes possible to be more personal relevant in the ancillaries that are offered. Try not to oversell it and don’t make it overly complex: the future is in quality, not quantity.