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Enterprise AI

ML in Travel and Tourism Industry | Complete Solution

Dr. Jagreet Kaur Gill | 09 Dec 2022

ML for Travel and Hospitality Management

Data relating to travel and hospitality can come from various sources and in different forms. It is beneficial in different ways from the perspective of data analysts and developers. Hotel and Airline Industry organizations can take advantage of a system that handles big data quickly and effectively and provides solutions. Using a generalized way of recording and storing information means collecting all data into one pool that can be manipulated and queried to identify problems, find patterns, and predict new outcomes.

Machine Learning Solution for Tourism Industry

  • With the help of xenonstack, one can build a predictive model of real-time data. That will help identify the reason for the cancellation of flights and the number of customers waiting for cancellations.

  • This will also help find revenue generated through different routes; for doing this, collect historical data of flights and customer reviews. One can predict revenue generated this year and % of customer satisfaction.

Why Xenonstack?

By clicking on the demo button, one can request a demo, and we will give a predictive model demo. The model will provide insights like the total amount of revenue generated by Travel and Hospitality through different routes and customers' count due to cancellation issues. This will predict the year's revenue and after changing service by what % customer's satisfaction with us.

Dashboard for Travel and Hospitality Industry

Travel and Hospitality Dashboard

Description of Travel and Tourism Dashboard

Described below are the features of the AI analytics dashboard for Travel and Tourism.

  • The dashboard represents Delhi to Kolkata, Mumbai to Kanpur, and Tamil Nadu to Allahabad, generating maximum revenue.

  • Customers lost by Cancellation KPI represented in March due to mechanical issues we lost maximum customers.

  • We can achieve our revenue generated as we can check through revenue generated by month and Customer satisfaction rate by month KPI.

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