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Python-Hotel-Booking-Data-Analysis-Project

This is an end-to-end data analysis project to investigate the variables that affect hotel reservation cancellations

Business Problem

In recent years, City Hotel and Resort Hotel have seen high cancellation rates. Each hotel is now dealing with a number of issues as a result, including fewer revenues and less than ideal hotel room use. Consequently, lowering cancellation rates is both hotels' primary goal in order to increase their efficiency in generating revenue and for us to offer thorough business advice to address this problem.

Research Questions

  1. What are the variables that affect hotel reservation cancellations?
  2. How can we make hotel reservations cancellations better?
  3. How will hotels be assisted in making pricing and promotional decisions?

Suggestions

  1. Cancellation rates rise as the price does. In order to prevent cancellations of reservations, hotels could work on their pricing strategies and try to lower the rates for specific hotels based on locations. They can also provide some discounts to the consumers.
  2. As the ratio of the cancellation and not cancellation of the resort hotel is higher in the resort hotel than the city hotels. So the hotels should provide a reasonable discount on the room prices on weekends or on holidays.
  3. In the month of January, hotels can start campaigns or marketing with a reasonable amount to increase their revenue as the cancellation is the highest in this month
  4. They can also increase the quality of their hotels and their services mainly in Portugal to reduce the cancellation rate. ​

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This is an end-to-end data analysis project to investigate the variables that affect hotel reservation cancellations

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