To analyze the relationship between the number of property images and booking rates on Airbnb. The project aims to identify the minimum and optimal number of images required to maximize booking potential, helping hosts enhance their listings and increase bookings.
Airbnb is a global online marketplace that connects people looking for accommodations with homeowners willing to rent out their spaces. It has become one of the most popular platforms for short-term rentals, offering diverse lodging options worldwide.
Over the past five years, Airbnb has observed a clear trend: listings with fewer or no images often remain unbooked, leading to a high number of redundant entries on the platform. To address this issue, it is crucial to determine the optimal number of images that maximize booking potential while minimizing the risk of unbooked listings.
The dataset contains Airbnb listing data from the past five years, including both Regular and Superhosts. The analysis also includes daily data from August 2018 to August 2019, focusing on unbooked listings categorized by the number of images.
| Column Name | Description |
|---|---|
| Listing_Id | Unique identifier for each listing |
| Posting_Date | Date when the listing was posted |
| Posting_Time | Time when the listing was posted |
| Location | Geographical location of the listing |
| Images (number) | Number of images associated with the listing |
| Bookings | Number of bookings made |
| Host_Type | Type of host (Regular / Superhost) |
| Date | Date for open listings data |
| Open_Listings_0_2 | Count of listings with 0-2 images and no bookings |
| Open_Listings_3_5 | Count of listings with 3-5 images and no bookings |
| Open_Listings_6_10 | Count of listings with 6-10 images and no bookings |
| Open_Listings_11_15 | Count of listings with 11-15 images and no bookings |
| Open_Listings_16+ | Count of listings with 16+ images and no bookings |
| Property_Images | Number of images in different ranges |
| Total_Listings | Total active listings |
| Redundant_Listings | Listings with no bookings in the last year |
Dataset link: Airbnb Data
- Data Import and Cleaning
- Exploratory Data Analysis (EDA) with Tableau
- Visualization of image count vs. booking rates
- Comparison between Regular Hosts and Superhosts
- Identifying optimal image count for higher booking rates
- Insights and recommendations for hosts
- Data Visualization with Tableau
- Exploratory Data Analysis (EDA)
- Comparative Analysis between Regular and Superhosts
- Trend Identification and Interpretation
| File Type | Description |
|---|---|
| Tableau Dashboard | Airbnb_Analytics_Dashboard |
| PDF Report | Airbnb_Analysis_Report.pdf |
| Dataset | Airbnb Data |
Feel free to reach out for questions and suggestions !
💻Compiled by Samarth