When the Netflix approach doesn’t work: Personalized Travel Recommendations
Mar 18, 2024
The Challenge
The customer needed to personalize hotel and travel offers to their customers across their entire portfolio. Crucially, very little information about the customers was available. In particular no Login was being captured, so typical recommender approaches didn’t quite work.
Results
Kineo.ai implemented a machine learning Algorithm using Factorization machines that was able to provide highly personalized travel recommendations, based on very few features such as place of origin, number of people and travel destination and duration. In addition we could make use of contextual features, such as location, week day and time of year.
The project leverages big data level amounts of data through the usage of Spark and a S3 Data Lake.
Weitere Use Cases
contact us
Realize your AI plans now
We look forward to getting to know you with a no-obligations conversation. Contact us now and we will get back to you immediately.
Your enquiry
We'll get back to you as soon as possible.
In the meantime, have a look at the other pages.