🏨 Hotel Management Data Analysis

This project presents a comprehensive analysis of hotel operations, customer behavior, and revenue trends using structured data. The goal is to uncover actionable insights that can help optimize bookings, improve service quality, and enhance overall business performance in the hospitality sector.

📊 Project Overview

• Dataset: Operational data including booking dates, room types, customer demographics, revenue, and cancellation status.
• Scope: Analyze booking patterns, revenue distribution, customer segmentation, and cancellation trends.
• Objective: Support data-driven decision-making for hotel management and marketing strategies.

🔍 Key Insights

• Booking Trends:

  • Peak booking periods identified across seasons.
  • Weekday vs. weekend occupancy rates compared.

• Revenue Analysis:

  • Highest revenue generated from premium room types.
  • Booking source impact on revenue performance.

• Customer Demographics:

  • Age and gender breakdown of guests.
  • Repeat guest behavior and loyalty indicators.

• Cancellation Patterns:

  • Cancellation rates by room type and booking channel.
  • Impact of lead time on cancellations.

📈 Features

• Cleaned and structured Excel dataset
• Pivot tables and dashboards for quick insights
• Visualizations: bar charts, pie charts, trend lines
• KPI metrics: Total Bookings, Revenue, Occupancy Rate, Cancellation Rate