What is AirBnB Rental Data? Definition, Sources & Datasets to buy
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
What is Airbnb Data?
Airbnb data is information collected and stored by Airbnb, a popular online marketplace for lodging and vacation rentals. This data includes details about the properties listed on the platform, such as location, amenities, availability, and pricing. It also encompasses user information, such as guest reviews, host profiles, and booking history. Airbnb uses this data to facilitate bookings, improve user experience, and make informed business decisions.
Examples of Airbnb data include information about listings, bookings, reviews, host profiles, and pricing. Airbnb data is used for various purposes such as market analysis, property investment decisions, pricing strategies, and research on the sharing economy. In this page, you’ll find the best data sources for accessing and analyzing Airbnb data, including options for downloading historical datasets or purchasing specific subsets of Airbnb data.
Best Airbnb Databases & Datasets
Here is our curated selection of top Airbnb Data sources. We focus on key factors such as data reliability, accuracy, and flexibility to meet diverse use-case requirements. These datasets are provided by trusted providers known for delivering high-quality, up-to-date information.
Airbnb.com Data | Airbnb Listings | Airbnb Occupancy Rate | Active Listings | Travel & Tourism Daily Rate
AirBnB Listings Data | Realtime listings for rentals across data sources including AirBnB and VRBO
Airbnb data for research purpose
Airbnb Transactional E-receipt Data | Hotel, Travel, Hospitality
Airbnb data | 2021 Occupancy, Daily rate, active listings | Per country, city, zipcode
Airbtics - Airbnb Data - Business KPI Tracker for Europe, North & South America, Oceania
DATAANT | Travel Data | Dataset, API | Booking and Pricing Data: Hotel Websites, Flight Aggregators and Rental Aggregators | Global Coverage
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Top Airbnb Data Providers & Companies
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CrawlBee
CoverageUSAUK+247VI contacted CrawlBee's CEO, Ryan DeWitt through Datarade. Ryan is very flexible, friendly, and extremely helpful! he worked with me to get the mortgage data I need for my research project. The data is very thorough and accurate. I highly recommend CrawlBee as I truly had a very good experience!
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PromptCloud
CoverageUSAUK+247PromptCloud, a global leader in web data extraction, delivers tailored data solutions to fuel your business. Our services include Custom Web Crawling, Hosted Indexing & Live Crawls, catering to sectors like E-commerce, Finance, Healthcare, Travel, Marketing Research, Social Media, and more.Trusted byStart-ups to the Fortune 500sSupportPrompt support for clientsCustomizeCustom data, as per needs -
Airbtics
CoverageUSAUK+247We use a rigorous scientific approach to collect and process the data and validate them on a scale using qualitative research and AI.6 MillionAirbnb Data192Countries CoveredUnlimitedcustomised regions
Popular Use Cases for Airbnb Data
Airbnb Data is essential for a wide range of business applications, offering valuable insights and driving opportunities across industries. Below, we have highlighted the most significant use cases for Airbnb Data.
Main Attributes of Airbnb Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| String | The name of a city. | View 2 datasets | |
| String | The country code in Alpha-2 format (ISO 3166) | View 1 datasets | |
| String | The email address of a company or contact. | View 1 datasets | |
| Float | The latitude of a point on earth's surface. Commonly abbreviated as "lat". | View 1 datasets |
Airbnb Data Explained
How is AirBnB Data collected?
AirBnB collects data when users visit the website. It provides analytics on location interest as well as stay durations by documenting a property’s booking history. This gives a clear report of consumers’ interests and rental trends.
Consumer input is also important for AirBnB data collection. User-generated content like reviews and photos provide property data from a consumer perspective.
AirBnB market data provides insights on the short-term rental industry in general. Real estate market data is collected both by web scraping and compiling property report from a given area.
What are the attributes of AirBnB Data?
There are many different aspects to AirBnB data from both the consumer and host side of the operation.
Consumer-side data
This can include user-generated content like reviews and experiences shared in forums. More basic data includes average duration rate.
Host-side data
This includes property availabilities, property size and features as well as nightly rates. AirBnB data can also be refined to show data for a specific country or area to ensure that your property is actively competing against.
The best way to understand the attributes included in an AirBnB dataset is to ask for a data sample.
What is AirBnB Data used for?
AirBnB data is used by property owners and businesses to maximize their profitability. You can see which areas and property types are the most successful to ensure that your AirBnBs keep up in the busy market. This data can be useful for established renters or people looking to get started in the market.
For example, nightly rate data can show how your costs compare to those of properties around you. Likewise, reviews tell you what consumers are looking for, as well the local demand for AirBnBs. Businesses buy AirBnB data to see which areas gain the most interest and consumer footfall. From here, they can tailor their services to the visitors’ needs.
How is AirBnB Data used?
In practice, AirBnB data has a range of applications. One of the most frequent use cases is investment and market research. AirBnB investors use external datasets for real estate market analysis. With AirBnB data analysis, they can invest in a property which gives them the best ROI as a short-term rental home.
There are two stages in real estate market analysis: location research and property research. Location research is where the investor scouts out an area, like a given town or city. They aim to understand its demography, local amenities, transport connections and tourist attractions. These factors all play into how lucrative renting an AirBnB is. In the end, location research allows them to select an area which will make the most rental profit.
The second stage is property analysis. Here, an AirBnB database comes into its own. It shows the user details about individual properties. For example, recent sale price, energy efficiency, and occupancy rate.
Other users download AirBnB to make financial calculations. These include:
AirBnB Monthly Rental Income
Any AirBnB business needs to know how much potential income a property can generate. An AirBnB dataset ensures users balance cost vs revenue by showing investors and property owners monthly income.
AirBnB Cash on Cash Return
Cash on cash return is a way of measuring a property’s ROI. It considers debt and financing options to calculate profit from the AirBnB post-purchase.
AirBnB Cap rate
Another metric real estate investors use to determine property profitability is cap rate. Most AirBnB datasets include cap rate calculations as a data attribute. Cap rate = net operating income divided by current market value. Real estate investors know that the higher the cap rate, the higher the investment risk. So it’s an important metric for making decisions about AirBnB investing.
How can a user assess the quality of AirBnB Data?
It’s important to ensure that any AirBnB dataset you choose is up to date. This is because the short-term rental market, especially the AirBnB sphere, is constantly evolving. Always make sure to check the data provider’s reviews before buying AirBnB data. Lastly, consult a data sample before buying to ensure that the database matches your business’ needs.
Frequently Asked Questions
How is the Quality of Airbnb Data Maintained?
The quality of Airbnb Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Airbnb Data Updated?
The update frequency for Airbnb Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Airbnb Data Secure?
The security of Airbnb Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Airbnb Data Delivered?
Airbnb Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Airbnb Data.
How Much Does Airbnb Data Cost?
The cost of Airbnb Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Airbnb Data for your needs.
What Are Similar Data Types to Airbnb Data?
Airbnb Data is similar to other data types, such as Travel Intent Data, Travel Booking Data, Vacation Package Data, Ski Resort Data, and Trip Data. These related categories are often used together for applications like Real Estate Analytics and Real Estate Intelligence.
