Hotel Booking Data Analysis

Welcome to our Hotel Booking Data Analysis Project!

In this data-driven journey, we embark on a comprehensive exploration of real-world hotel bookings from a city and a resort hotel spanning the years 2015 to 2017. Our main objective is to understand and visualize datasets from both the hotel's and customer's perspective.

Defining the Problem and Objectives:

Our project begins by defining the key problem areas we aim to address. We seek to uncover the reasons behind booking cancellations across various parameters, identify the best time to book a hotel, and determine peak tourism seasons.

Data Collection and Preprocessing:

We have meticulously gathered relevant data from kaggle, ensuring its completeness and suitability for analysis. Before delving into the data, we perform thorough data cleaning and preprocessing, handling missing values, outliers, and formatting issues. We normalize, scale, and encode categorical variables, priming the data for insightful analysis.

Key Insights and Relationships:

Through our analysis, we unravel intriguing relationships between key factors. We observe that as lead time increases, the ratio of cancellations to successful bookings rises, shedding light on customer booking behavior. Additionally, we discover that while the "no deposit" type is popular, it also experiences a higher number of cancellations, while the "non-refundable" type shows higher customer commitment. We also uncover the impact of market segments on cancellations and reveal a link between past cancellations and the likelihood of future cancellations.

Price Variations and Tourism Peaks:

By meticulously analyzing hotel prices over the years, we identify the peak tourism periods, particularly in the months of July and August. During these periods, average daily rates soar, reflecting the increased demand for hotel bookings.

Conclusion and Recommendations:

As we conclude our journey, we summarize our key findings and draw actionable insights from the data. Armed with these insights, hotel management and stakeholders can optimize booking strategies, minimize cancellations, and enhance customer satisfaction.