# Booking-dataset-samples

A sample dataset of 1001 Booking listings

A Booking dataset sample of over 1000 records. Dataset was extracted using the Bright Data API.

Some of the data points that are included in the Booking dataset:

• link: Link to the property listing
• location: General area or destination of the property
• check_in: Check-in date for the booking
• check_out: Check-out date for the booking
• adults: Number of adults included in the booking
• children: Number of children included in the booking
• rooms: Number of rooms booked
• id: Unique identifier for the listing
• title: Title or name of the property
• address: Full address of the property
• city: City where the property is located
• review_score: Average review score from guests
• review_count: Total number of reviews for the listing
• image: Link to the property's image
• final_price: Total price after discounts and taxes
• original_price: Base price before discounts
• currency: Currency used for the pricing
• tax_description: Details about applicable taxes
• nb_livingrooms: Number of living rooms in the property
• nb_kitchens: Number of kitchens in the property
• nb_bedrooms: Number of bedrooms in the property
• nb_all_beds: Total number of beds available
• full_location: Complete address with detailed location information
• no_prepayment: Indicates if prepayment is not required
• free_cancellation: Indicates if free cancellation is available

And a lot more.

This is a sample subset which is derived from the "Booking listings" dataset which includes more than 30.4K records.

Available dataset file formats: JSON, NDJSON, JSON Lines, CSV, or Parquet. Optionally, files can be compressed to .gz.

Dataset delivery type options: Email, API download, Webhook, Amazon S3, Google Cloud storage, Google Cloud PubSub, Microsoft Azure, Snowflake, SFTP.

Update frequency: Once, Daily, Weekly, Monthly, Quarterly, or Custom basis.

Data enrichment available as an addition to the data points extracted: Based on request.

Get the full Booking dataset.

What are the Booking datasets use cases?

1. Market analysis

Businesses analyze and forecast travel trends using Booking.com datasets. By examining booking volumes and patterns, companies can identify popular destinations, predict peak travel times, and optimize their offerings. Tourism agencies and hospitality businesses can leverage this data to customize travel packages.

2. Competitive Analysis

Businesses use Booking.com datasets for competitive benchmarking, comparing their performance against competitors by analyzing pricing, property ratings, and customer reviews. This helps them identify areas for improvement and better understand traveler preferences.

3. Dynamic pricing

Hotels and travel businesses acquire Booking.com datasets to optimize revenue and create dynamic pricing strategies. By analyzing booking data, they adjust prices in real-time based on changes in demand, market conditions, and competitor pricing. This approach helps maximize revenue per available room (RevPAR).

Free access to web scraping tools and datasets for academic researchers and NGOs

The Bright Initiative offers access to Bright Data's Web Scraper APIs and ready-to-use datasets to leading academic faculties and researchers, NGOs and NPOs promoting various environmental and social causes. You can submit an application here.