https://github.com/shivamsharma32/airbnb-dataset-analysis-powerbi
Problem Statement: Airbnb company wants to engage more customers by analyzing Customer's Preferences. Approach: Conducted in-depth analysis of AirBnB data using Power BI, uncovering insights on listing information, booking patterns, pricing dynamics, and customer preferences.
https://github.com/shivamsharma32/airbnb-dataset-analysis-powerbi
Last synced: 2 months ago
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Problem Statement: Airbnb company wants to engage more customers by analyzing Customer's Preferences. Approach: Conducted in-depth analysis of AirBnB data using Power BI, uncovering insights on listing information, booking patterns, pricing dynamics, and customer preferences.
- Host: GitHub
- URL: https://github.com/shivamsharma32/airbnb-dataset-analysis-powerbi
- Owner: shivamsharma32
- Created: 2024-02-25T09:35:36.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-03-11T07:26:11.000Z (about 1 year ago)
- Last Synced: 2025-02-07T22:23:09.558Z (4 months ago)
- Homepage:
- Size: 538 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# AirBnB Dataset Analysis
# Data Source
https://www.kaggle.com/datasets/dgomonov/new-york-city-airbnb-open-data
# 🏠 Listing Information:
- Most common property types are Entire room/apt, Private room, Shared.
- Popular neighborhoods include Manhattan, Brooklyn, Queens, Bronx, Staten Island.
- Superhosts tend to have higher booking rates.
# 📈 Booking Patterns:
- Peak booking months are June and July.
- Weekends are typically busier than weekdays.
- Longer booking durations result in lower nightly rates.
# 💰 Pricing Dynamics:
- Average nightly rate varies by property type and neighborhood.
- Discounts for longer stays are common.
- Prices tend to increase during peak seasons and events.
# 🧑🤝🧑 Customer Preferences:
- Guests prioritize cleanliness and location when selecting properties.
- Positive reviews significantly impact booking rates.
- Amenities like free parking and Wi-Fi are highly valued by guests.
# Key Learnings:
- Optimizing listing descriptions and amenities can attract more guests.
- Adjusting pricing strategies based on seasonal trends can maximize revenue.
- Maintaining high cleanliness standards and providing exceptional customer service are crucial for positive guest experiences.
# Dashboard
