Django Stars highlight the top machine learning and AI trends in travel

Django Stars recently published an insightful blog post, Benefits of the Use of Machine Learning and AI in Travel. Their article highlights the trends of machine learning in the travel industry and also discusses the importance of machine learning to provide users with the best UX.

Because travel is a highly emotional experience with many different options, travelers want to receive the right suggestions for their travel needs. If they aren’t finding what they want on one site, they’ll likely switch to a different one.

“88% of leisure travelers will switch to a different app or website if yours isn’t meeting their needs.”

Luckily, booking travel i.e hotels, flights, and car rentals have become mainly an online purchase. This provides a great opportunity for travel companies to leverage their data for machine learning. For example, our ML Predicitive Intelligence Platform provides real-time predictions on a users likelihood to convert. This allows companies to make better designs for their onsite experience.

According to Django Stars, the most successfully realized implications of AI and ML in travel are:

  • Predictions
  • User experience management
  • Chatbots
  • Recommender systems
  • Content curation

“Travel companies are actively implementing AI & ML to dig deep in the available data and optimize the flow on their websites and apps, and deliver truly superior experiences.” Django Stars

An important highlight made in the post is the necessity to harness your data. Quality matters. Building an entire system from datasets can be a big bite to chew, but working with the right third party that has the expertise and data science background can be conducive to the overall success of your business goals.

Click here to read Django Star’s blog post in full. The post also provides a great overview of the AI and ML ecosystem.

Interested in how <intent> provides real-time predictions for your site traffic? Click the learn more button below.

LEARN MORE