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European Hotel Booking Behaviour Study
Data Science and Analytics
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About
Presents detailed information concerning 119,390 hotel reservations made across two specific locations in Portugal. The data allows for detailed analysis of customer behaviour, booking patterns, and cancellation rates within the hospitality sector. It covers bookings made at a City Hotel located in Lisbon and a Resort Hotel situated in the Algarve region. This resource is excellent for understanding demand fluctuations, market segment dynamics, and the key factors influencing reservation outcomes.
Columns
- hotel: Specifies the type of establishment the booking was made for (e.g., City Hotel or Resort Hotel).
- market_segment: Identifies the origin or channel through which the reservation was acquired (e.g., Online Travel Agent, Offline Travel Agent/Tour Operator).
- deposit_type: Describes the nature of the deposit taken for the booking (e.g., No Deposit, Non Refund).
- lead_time: Indicates the number of days elapsed between the booking date and the scheduled arrival date.
- previous_cancellations: Records the total count of previous cancellations made by the customer.
- previous_bookings_not_canceled: Tracks the total number of prior bookings made by the customer that were successfully completed.
- days_in_waiting_list: Measures the duration, in days, that the booking spent on a waiting list before confirmation.
- booking_changes: Counts the number of modifications the customer made to the reservation after the initial booking was recorded.
- total_of_special_requests: Records the volume of special requests submitted by the customer regarding their stay.
- is_canceled: A binary flag (1 or 0) indicating whether the booking was ultimately cancelled.
Distribution
The data set features 119,390 distinct records, with each entry representing a single hotel booking observation. The file is streamlined, containing 10 pre-processed features. The typical data file format for platform listing is CSV.
Usage
- Predictive modelling to determine the probability of a reservation cancellation.
- Conducting detailed seasonality and demand forecasting studies for hotel management.
- Developing customer segmentation models based on advance booking duration and previous transaction history.
- Evaluating the effectiveness and profitability of different sales channels and market segments.
Coverage
The data focuses exclusively on the hotel industry in Portugal. The scope includes reservations for two types of hotels: a Resort Hotel situated in the Algarve and a City Hotel located in Lisbon. The time range covered spans from 1st July 2015 through to 31st August 2017. Note that all personally identifiable elements pertaining to hotels or customers have been deliberately removed.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Data Scientists and Machine Learning Engineers: For building predictive models concerning consumer travel behaviour and risk assessment.
- Revenue and Pricing Managers: To optimise pricing strategies and inventory management based on cancellation likelihood and lead time.
- Academic Researchers: Those interested in econometric analysis of tourism demand and consumer choice models.
Dataset Name Suggestions
- Portuguese Hotel Booking Demand Analysis
- Lisbon and Algarve Hotel Reservation Patterns
- European Hotel Booking Behaviour Study
- 119K Portugal Hotel Bookings Data
Attributes
Original Data Source: European Hotel Booking Behaviour Study
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