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🛎️Hospitality-Analysis-Python

🏨 AtliQ Grands Hospitality Analysis

📝 Introduction

Welcome to the AtliQ Grands Hospitality Analysis project! This project aims to provide valuable insights into the hospitality industry, focusing on AtliQ Grands — a prominent hotel chain operating in multiple Indian cities. Through data analysis and visualization, we strive to address the challenge of declining revenue and market share, ultimately helping AtliQ Grands make data-informed decisions to enhance its financial performance.

❓ Problem Statement

AtliQ Grands faces a significant business challenge: a decline in revenue and market share. To overcome this, the hotel chain has decided to leverage data analytics. The primary objective of the project is to analyze booking data collected from various sources, including the company's website and third-party booking platforms. By doing so, we aim to:

  • Identify opportunities for revenue enhancement.
  • Enhance market competitiveness.

🛠️ Tools Used

  • Jupyter Notebook
  • Canva

🔄 Project Process

🔍 Data Cleaning and Transformation

Data quality is paramount in our analysis. This phase involves several critical steps:

  • Cleaning Invalid Data: Identifying and rectifying issues such as negative values for the total count of persons.
  • Outlier Removal: Ensuring data accuracy by detecting and eliminating outliers.
  • Creating New Columns: Crafting metrics like occupancy percentage (successful bookings to actual capacity ratio).

💡 Insights Generation

Our analysis has uncovered several noteworthy insights:

  • Presidential Popularity: "Presidential" rooms have the highest average occupancy rate (59.30%), highlighting their guest appeal.
  • City Standouts: Delhi leads with the highest average occupancy rate (61.51%), while Bangalore lags behind (56.33%).
  • Weekend Wonders: Weekends consistently outshine weekdays in terms of occupancy rates, suggesting opportunities for targeted marketing and pricing strategies.
  • June Insights: In June, Delhi (62.47%) and Hyderabad (58.46%) emerged as occupancy rate leaders.
  • Mumbai Reigns: Mumbai reigns supreme in revenue generation among cities.
  • Revenue Rollercoaster: Revenue fluctuates monthly, with July 2022 at ₹38,99,40,912 INR and May 2022 at ₹40,83,75,641 INR.

✅ What Can Be Implemented?

Our analysis points toward two key strategies:

  • Implement Weekend-Specific Promotions: Targeting weekends to attract more guests and increase revenue.
  • Invest in Delhi Expansion: Capitalize on Delhi's high occupancy rate by expanding the hotel chain's presence in the city.

🧠 Key Learnings

Throughout this project, we gained valuable skills and knowledge, including:

  • Pandas Library
  • Handling Null Values
  • Data Concatenation and Merging
  • Data Plotting with Matplotlib
  • Data Exploration and Understanding