Hotel Booking Demand
Completion Date:
Project Overview
In order for a hotel to accurately forecast revenue, room occupancy, and availability as well as to conduct appropriate and timely marketing strategies, it’s important to understand the many factors that contribute to a booking being fulfilled. Understanding the variables that may cause a customer to cancel their room is vital for success in the hospitality industry. To understand the key features of booking demand, I used a Hotel Booking Demand dataset that contains information from two hotels in Portugal; a city hotel in Lisbon and a resort-style hotel in the region of Algarve.
Role:
Problem Statement
For Hotels, it is essential to forecast revenue, room occupancy accurately, and availability and conduct appropriate and timely marketing strategies. In addition, understanding the factors that may cause a customer to cancel their room is vital for success in the hospitality industry. Some of the factors are types of hotels, time of the year, country, room size, and quality of service. In this project, I used information from two hotels in Portugal; a city hotel in Lisbon and a resort-style hotel in the region of Algarve. The two hotels were Resort Hotel and City Hotel, with 40060 and 79330 observations, respectively. The data were collected over three years, from July 2015 until August 2017. However, I used only a portion of this dataset. The project\\\'s main focus was to find the key features within the data that would increase the likelihood of a canceled booking for either of the two hotels. From the data, it can be easily seen that there were maximum bookings and cancelations done during summer, particularly in August and June. The Average Daily Rate (ADR) variable has positive percentage changes over the two years.
Executive Summary
Data Dictionary
