The first move was to identify the current offer for travel inspirations, like other airlines companies, OTAs, Youtube videos, social networks, blogs, magazines and many more. The result was that each of them always provide users with the same boring “Top 10 destination” or too early details.
After a brief research, it was time to hear users’ opinion about how they find inspiration for travels. The survey was structured in order to obtain both quantitative and qualitative data in a limited amount of time.
Thanks to all the data gained from the questionnaire, it was possible to identify some mental models about how people plan their journeys without being sure on where to go. After that we created personas in order to understand who we were designing for.
Instead of searching for precise destinations, the concept wants to consider the emotional and sensational expectation of the user, showing moods, activities, sounds. In this way, the only question the user have to think about is: “How do I want to feel in this journey?”. Here, is where easyDream born.
EasyDream presents to users a sequence of landscapes, moods, sounds that he can dismiss or accept through a swipe gesture. This action also trains the Deep Reinforcement Learning algorithm which, once ready, presents the solutions tailored to user’s expectaions, highlighting the experiencial value.
Most of people travel with their friends, family or in couples who are normally difficult to agree with each other when talking about travels. EasyDream also has a group function. Once each member makes his own swipes, the system proposes some destinations that match with all participants’ expectations.
