2025 Competition Topic: Destination Recommender
2025 Competition Topic: Destination Recommender
In today’s travel industry, finding the perfect destination can be overwhelming due to the vast number of choices and diverse traveler preferences. For American Airlines, understanding a passenger’s “next travel” is crucial to both enhancing customer service and maximizing revenue.
Building a destination recommender for AA is valuable for several reasons:
Increasing flight bookings
Boosting revenue
Enhancing customer satisfaction
Fostering customer retention
The challenge is to develop a model that predicts up to five possible destinations an AA customer is likely to visit next. This prediction will be based on key factors such as the customer’s residence, their search history on the AA website, and their recent travel experiences.
Datasets and further instructions will be made available upon successful registration. Click here to register.
FAQs
Where can I register?
A/ Click here Only the team lead needs to register. Information about other team members should be provided during the registration.
When should I get the datasets?
A/ The data will be made available once registration is successful.
Will I get more information on the dataset?
A/ Yes, detailed information will be provided about the dataset. Also, a question and answer session (Q&A) will occur in
March 2025.
Which language or package should I use?
A/ Whichever you prefer.
What type of model should I build?
A/ Whatever you feel most comfortable building.
Which features should I use?
A/ You are free to decide which columns are best to use. However, you can attend the question and answer (Q&A) session that will be in March 2025.
What are the expectations of a sucessful prediction?
A/ Your model may predict up to five possible destinations. If any of these five match the target variable, we will consider this a successful prediction.
Who should I contact for further questions and clarifications?
A/ You can contact Dr. Yanshuo Sun (y.sun@eng.famu.fsu.edu) or JohnPaul Adimonyemma (johnpaul1.adimonyemm@famu.edu)