📌 Project Title

Hotel Booking Cancellations Analysis

📖 Overview

This project analyzes hotel booking data to uncover patterns in bookings and cancellations. The dashboard visualizes trends based on guest type, room status, and seasonal patterns. It helps identify key factors influencing cancellations and can assist hospitality businesses in improving strategies to reduce cancellations.

📂 Dataset

Source: Hotel Booking Demand Dataset on Kaggle

File Used: hotel_bookings.csv

Description: The dataset contains booking information for City Hotels and Resort Hotels, including:

Booking status (canceled or not)

Guest type

Room status

Arrival dates

Other booking details

🛠 Tools & Technologies

Excel: Data cleaning and visualization

Kaggle: Dataset source

📊 Dashboard Highlights

Total Bookings: 119,390

Total Cancellations: 44,224

City Hotels have more cancellations compared to Resort Hotels

Majority of cancellations occur for desired rooms

Peak cancellations during September and October

Couples are the dominant guest type with high cancellations

🚀 How to Use

Download the dataset from Kaggle

Open Excel and load the dataset

Use Pivot Tables and Charts to create similar dashboards

✅ Key Insights

Cancellations are higher in City Hotels

Desired rooms have more cancellations compared to undesired rooms

Seasonality plays a big role: peak cancellations happen in late summer and early autumn

Build an interactive dashboard using Power BI or Tableau

Predict cancellation likelihood using Machine Learning