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Guest Experience & Pricing Dataset
Product Reviews & Feedback
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About
This dataset, titled "Hotel Dataset: Rates, Reviews & Amenities", offers an insightful look into the hospitality industry by providing crucial information on hotel rates, guest reviews, and available amenities. Drawing data from two prominent travel platforms, TripAdvisor and Booking.com, it serves as a valuable resource for analysing trends and understanding customer experiences. The dataset is designed to help stakeholders make informed decisions regarding pricing strategies, marketing efforts, and customer service enhancements within the dynamic hotel sector. Booking.com, founded in Amsterdam in 1996, connects millions of travellers with accommodations globally, supporting various property types and available in 43 languages. Similarly, Tripadvisor, a world-leading travel guidance platform, assists hundreds of millions monthly with planning, booking, and experiencing trips, featuring over a billion reviews across nearly 8 million businesses in 43 markets and 22 languages.
Columns
The dataset contains 9 columns, each providing distinct insights:
- Hotel Name: The name of each specific hotel.
- Location: The geographic location of each hotel, with a variety of unique places recorded.
- Rating: An overall rating for each hotel, presented on a scale of 1 to 10.
- Review Score: A qualitative assessment of hotel reviews, also on a scale of 1 to 10, often categorised (e.g., "Very Good", "Good").
- Number of: The total count of reviews associated with each hotel.
- Room Score: A specific rating for the quality of rooms within each hotel, ranging from 1 to 10.
- Room Type: Describes the specific type of room available, such as "One-Bedroom Apartment" or "Double or Twin Room".
- Bed Type: Specifies the kind of bed provided in rooms, for example, "2 twin beds" or "1 double or 2 twins".
- Room Price (in BDT or any other currency): The nightly price for each room, expressed in Bangladeshi Taka or an equivalent currency.
Distribution
The data is typically provided in a CSV file format. The dataset file,
booking_hotel.csv, has a size of 416.48 kB and consists of 9 distinct columns. It includes over 6,000 records, providing a substantial amount of information for analysis.Usage
This dataset is ideally suited for various applications within the hospitality and data analytics domains:
- Market Research: Identify emerging trends in hotel pricing, guest preferences, and service quality.
- Competitive Analysis: Benchmark hotel performance against competitors based on ratings, reviews, and amenities.
- Strategic Planning: Inform decisions related to optimising pricing models, developing targeted marketing campaigns, and improving customer satisfaction.
- Academic Research: Explore factors influencing guest experiences and hotel success.
- Predictive Modelling: Develop models to forecast hotel occupancy, revenue, or customer sentiment.
Coverage
The dataset offers a global scope, covering a wide array of hotels from numerous locations worldwide. It incorporates data from platforms like Booking.com, which lists over 28 million accommodations in 43 languages, and Tripadvisor, which aggregates over a billion reviews for nearly 8 million businesses across 43 markets. While specific time ranges or demographic breakdowns are not detailed, the broad data source coverage suggests a diverse representation of global travel experiences.
License
CC0: Public Domain
Who Can Use It
This dataset is highly beneficial for:
- Data Analysts and Scientists: For performing statistical analysis, developing predictive models, and extracting actionable insights.
- Hospitality Business Owners and Managers: To monitor performance, understand guest feedback, and make strategic business decisions.
- Marketing Professionals: To identify target demographics, tailor promotional content, and enhance brand positioning.
- Customer Service Teams: To pinpoint common guest issues and improve service delivery.
- Students and Researchers: For educational projects, academic studies, and exploring industry dynamics.
Dataset Name Suggestions
- Hotel Insights: Rates, Reviews & Amenities
- Global Hospitality Performance Data
- Travel Accommodation Analytics
- Guest Experience & Pricing Dataset
- Hotel Industry Metrics
Attributes
Original Data Source: Guest Experience & Pricing Dataset
QUALITY