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MakeMyTrip Hotels Dataset
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About
This dataset presents detailed information for approximately 20,000 hotels listed on MakeMyTrip.com, a prominent online travel portal in India. It serves as a pre-crawled subset derived from a significantly larger dataset, which originally encompassed over 615,000 hotel records. The data was collected through a dedicated web-crawling service developed by PromptCloud. This resource is particularly valuable for conducting in-depth analyses of hotel reviews, ratings, and property descriptions, offering insights into the Indian hospitality market.
Columns
- area: The specific geographical area of the hotel's location.
- city: The city where the hotel is situated.
- country: The country of the hotel, primarily India.
- crawl_date: The date on which the data for the hotel was extracted.
- highlight_value: Key highlights or distinguishing features of the hotel.
- hotel_overview: A general overview or textual description of the hotel.
- hotel_star_rating: The official star rating assigned to the hotel.
- image_urls: Links to images associated with the hotel.
- in_your_room: Details concerning the amenities or features provided within the hotel rooms.
- is_value_plus: A boolean indicator related to value-added services or features.
- latitude: The geographical latitude coordinate of the hotel property.
- longitude: The geographical longitude coordinate of the hotel property.
- mmt_holidayiq_review_count: The number of reviews sourced from HolidayIQ and displayed on MakeMyTrip.
- mmt_location_rating: The rating given for the hotel's location on MakeMyTrip.
- mmt_review_count: The total count of reviews for the hotel on MakeMyTrip.
- mmt_review_rating: The overall rating based on reviews on MakeMyTrip.
- mmt_review_score: The calculated review score from MakeMyTrip reviews.
- mmt_traveller_type_review_count: Categorised counts of reviews based on traveller types such as families, couples, business travellers, solo travellers, and friends.
- mmt_tripadvisor_count: The number of TripAdvisor reviews associated with the hotel on MakeMyTrip.
- pageurl: The direct URL to the hotel's listing page on MakeMyTrip.com.
- property_address: The complete postal address of the hotel.
- property_id: A unique identification number assigned to each hotel property.
- property_name: The registered or commonly known name of the hotel.
- property_type: The classification of the property, e.g., 'Hotel' or 'Lodge'.
- qts: Query Time Stamp, indicating when the query was processed.
- query_time_stamp: The timestamp when the data query was originally posted.
- room_types: Descriptions or names of the various room types available at the hotel.
- site_review_count: The number of reviews gathered from other review sites.
- site_review_rating: The aggregate rating from other review sites.
- sitename: The source website for the data, identified as 'makemytrip'.
- state: The state in India where the hotel is located.
- traveller_rating: Ratings provided by travellers across various aspects like location, hospitality, facilities, cleanliness, value for money, and food.
- uniq_id: A unique identifier for each individual record within the dataset.
Distribution
This dataset is provided in CSV format as
makemytrip_com-travel_sample.csv, with a file size of 37.83 MB. It details approximately 20,000 hotel entries and encompasses 33 distinct columns. While this represents a significant collection, it is a subset of a much larger dataset exceeding 615,000 hotel records.Usage
This dataset is ideally suited for a diverse range of analytical and practical applications, including:
- Performing market analysis to discern trends and patterns within the Indian hotel industry.
- Conducting sentiment analysis on hotel reviews to understand guest perceptions and satisfaction.
- Developing pricing strategies or demand forecasting models for hotels.
- Executing geospatial studies to map hotel distribution and identify competitive clusters.
- Gaining competitive intelligence on hotel offerings and performance within the Indian online travel agency market.
- Building or refining hotel recommendation systems for travellers.
Coverage
The dataset's geographic coverage is focused on India, detailing hotels across various cities, including New Delhi and NCR, Goa, and different states such as Rajasthan. The temporal coverage for the data collection, as indicated by the crawl and query timestamps, primarily spans from January to September 2016. While the dataset does not target specific demographic groups for collection, the
mmt_traveller_type_review_count column offers valuable insights into review contributions by different traveller types, including families, couples, business, solo, and friends. It is notable that some columns within the dataset do contain missing values.License
CC BY-SA 4.0
Who Can Use It
This dataset is highly beneficial for:
- Data Scientists and Analysts: For in-depth quantitative analysis of hotel performance and market dynamics.
- Researchers and Academics: Engaging in studies related to hospitality, e-commerce, and consumer behaviour in the travel sector.
- Travel and Tourism Businesses: Seeking to understand market trends, competitor offerings, and customer preferences to inform business strategies.
- Software Developers: Building applications that leverage hotel data, such as booking platforms or analytics dashboards.
- Marketing Professionals: To identify target audiences and tailor promotional campaigns for the Indian travel market.
Dataset Name Suggestions
- MakeMyTrip India Hotel Listings
- Indian Hotel Travel Data
- MakeMyTrip Hotels Dataset (India)
- India Online Hotel Market Data
- PromptCloud Indian Hotels
Attributes
Original Data Source: MakeMyTrip Hotels Dataset
QUALITY